“Kmart has plenty of awareness, so what?”

-Purple Cow by Seth Godin

I hear the term “brand awareness” all the time, but to be honest, I don’t really know what it means.

On its surface, it’s somewhat obvious: it’s the amount of people who know about your brand.

But that simple, stupid Google search definition doesn’t do it for me.

I have more questions:

• Which people?
• Is “brand awareness” a relative metric that you need to compare to others to make sense like IQ, or is it an absolute metric like average order value?
• How do you determine their awareness? Is it based on recall, recognition, something else? What does “awareness” actually mean?

From a common sense perspective, of course brand awareness as a concept matters, if we’re defining it as “knowing about your brand” (though that seems properly circular to me – of course you need to “know” a brand before you buy it).

What perplexes me is the metric known as brand awareness. When it comes to measurement, I know what conversion rate means. I can explain how it is logged and what its significance is. Heck, I can even talk about bounce rates with enough clarity to know they don’t really matter.

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If I’m putting in the effort to measure and analyze a metric (even taking action on it), then I want to get crystal clear what the metric actually means, both as a construct and as a practical consideration for business decisions. “Brand awareness” suffers from a lack of clarity to me.

So is brand awareness one of those important things that isn’t measurable (these things do exist!)? Or is there an actual way to measure it, and it’s just very ambiguous how to do it?

And if we measure it, can we do anything with it, or is just a “nice to know” kind of metric?

I went down a rabbit hole and read a lot of academic papers as well as shitty blog posts that rank well on Google [1], and asked a lot of respectable marketers, to try to figure out.

What is Brand Awareness?

Brand awareness is a measure of a brand’s relative cognitive representation in a given category in relation to its competitors.

That’s it. It’s measured by how many people, when asked, know your brand.

Now, you can measure this a few different ways (which we’ll get into).

You can measure it actively by asking people to pick which brands they have heard of from a list. You can ask actively by asking them to tell you which brands they’ve heard of. You can pull brand awareness from passively available data on search, analytics, and social.

Brand awareness is not:

• Brand equity
• Brand preference
• Brand loyalty
• Corporate identity
• Brand engagement

All of those things are distinct measures, though all normally fall roughly under the brand marketing department.

Of all the above, the two that are most commonly confused with brand awareness are brand equity and brand loyalty.

Brand equity is basically the value of your brand in relation to other brands in your space. It’s why people will pay a bunch of money for Apple products, and it’s why a posh wine will actually subjectively taste better to an unsuspecting wine drinker.

Brand loyalty is the tendency for customers to keep buying from a brand instead of switching to a competitor. I like to frame that one in the inverse, actually, and instead look at it as the unwillingness of a customer to switch to another brand despite attractive feature parity or pricing.

Mind share (or share of voice or consumer awareness) is a similar term to brand awareness. There are legitimately too many jargon-y terms in this space, so it’s no wonder so many people are confused about it all means.

In any case, someone needs to be aware of your brand before it becomes valuable, and it needs to become valuable before they’re loyal to it.

Let’s talk about measuring that brand awareness.

How to Measure Brand Awareness

The way you measure this depends on your industry as well as your market.

If you’re P&G advertising general consumer packaged goods, brand recall surveys aren’t the worst thing in the world. [2]

If you’re selling live chat software, it’s probably a horrible way to measure brand awareness, unless your surveys are incredibly well-targeted as well as conducted longitudinally and in relation to a similar cohort of competitors (after all, the context is what matters with these surveys, not a generic metric).

In my opinion, how you measure brand awareness should have two main criteria:

1. It should be sampled from those who are actually in your target market
2. It should be actionable. Knowing your number should help you make better decisions.

I’ll outline all the ways people measure brand awareness below, and I’ll explain why most of them aren’t actually measuring what we think of as “brand awareness” at all.

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The metrics below aren’t inherently good or bad, but the important thing is to have the discussion internally of what the metric actually means to your business before you conduct the campaign.

If everyone thinks it’s something different, it’s a bad metric, and if you’re post-hoc storytelling, than you’re causing collateral damage to your company’s culture.

Direct Traffic

First and foremost, if you primarily operate digitally (i.e. people come to your website to complete most important actions, rather than in-person), direct website traffic is a common indicator of brand awareness.

The logic behind this is pretty tight: the number of people who type in [yourwebsite.com] reflects the number of people who are “aware” of your brand (and they show that by remembering to type in your brand specifically).

It’s common for performance campaigns (e.g. paid ads) to have an effective on this direct traffic as well, which supports the idea that there are at least some partially untrackable second order effects to many types of campaigns.

As an aggregate metric, this is a pretty good directional indicator of brand awareness.

(Acquisition > Channels > “Direct”)

The problem, however, lies with how direct traffic is attributed on most analytics platform.

Essentially, Google Analytics attributes traffic that it can’t otherwise attribute to “direct.” This means your numbers are likely inflated, even more so if you aren’t properly tagging campaign links, especially via channels like email and potentially social as well.

Similarly, you don’t necessarily know that everyone who comes to your site directly is a potential customer in your target market. They could be:

• Employees (if you haven’t set up IP filters)
• Competitors doing research
• Current users coming to logging in (though a higher number of these isn’t a bad thing either)
• Random voyeurs checking out your site after some press

In essence, direct traffic is like a thumb in the wind or a weather vane, but it’s not a very precise metric (and you can’t do much with the number once you know it – it’s not an actionable metric).

Track direct traffic, but don’t worry too much about its brand awareness implication or ever use it as an argument to back up a failed campaign.

Branded Search Terms

Branded search volume is like direct traffic, except instead of tracking people who directly type in your URL, you’re tracking people who search for your branded terms in Google or other search engines.

E.g. it’s the difference between someone typing in alexbirkett.com and someone searching Alex BIrkett.

In my opinion, branded search is a better way to measure brand awareness over time, specifically because there is less muddiness around attribution. You’re isolating people who are specifically searching for your brand, and you’re not including all kinds of different channels due to failed analytics attribution.

Still, it’s a very directional metric, and search volume data is often only an estimate, never truly granular. A good portion of brand searches can also be attributed to product users looking to sign in (if you’re in Saas). Of course, seeing that number go up is never a bad thing – it’s just not tracking what you think of as top of the funnel brand awareness.

I do find it to be a particularly good thermometer or gut check when doing competitive analysis though.

For instance, if you’re looking at the top email marketing software vendors, you can very quickly see how much search volume each brand gets:

At the very least, this is actionable in that it helps you determine which competition is the biggest threat, how to position yourself in the market, and how much space you have to overcome to catch up to the biggest names in the space.

These numbers aren’t going to change in the course of a month or a quarter, and you might see a little wiggle over the course of a year. So as far as actionability goes, it’s best used as a periodic audit or marketing research tool.

If you’re tracking branded search of your own company you can just use Google Search Console and get much more accurate numbers.

Brand Owned Terms

Often when you launch a campaign, it is with a new “brand owned term.”

This could be an advertising tag line, or it could be a new industry framework, such that you find frequently used in B2B.

For the former, think something like “Got Milk?” and for the latter, something like “Inbound Marketing” or “Skyscraper Technique.”

I like these because, rather than the amorphous concept of your entire brand or company, brand owned terms hone in on a specific idea or campaign.

My rule of thumb is that the narrower the scope of a metric, the more useful it is as a predictive or decision making tool.

You can’t do much with the idea that X number of people search “HubSpot,” but you can infer a lot about the effectiveness of an ad campaign if people start searching for the phrase, “grow better.”

The problem with brand owned terms is that, unlike your actual company name/brand, the volume for these phrases tends to be unnervingly low.

It’s like when social media managers pick a hashtag and start using it all the time, only to analyze several months later and discover that, lo and behold, barely anyone else used the hashtag.

We get trapped in our own bubbles as marketers, so we assume that everyone in the world is talking about “conversational marketing” or the “skyscraper technique.”

However, in the broader world, these campaigns tend not to make a big splash.

So unless your brand and your campaigns are truly mainstream, the amount of search data you’ll have on your brand owned terms will probably be very low, and highly variable, and thus very difficult to extract value from.

That doesn’t mean you shouldn’t track them; they correlate highly with brand search terms as well. And if you’re going to work on making an idea stick, you should track how often people use the term and search it organically.

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Brand Recall/Recognition Surveys

Ironically, brand recall surveys are probably one of the only methods on this list that actually measure what we consider “brand awareness,” and they’re probably the least useful for 99%+ of brands.

Brand recall surveys are the tried and true method for the large and consumer facing and the Fortune 500.

How do you determine whether you have a greater brand awareness than Pepsi if you’re Coca-Cola? Get a big enough sample of participants, and ask them which brands they know.

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The problems with this method are many. Of course, for startups, the level of granularity required in your population sampling would be almost impossible. You can probably find a representative sample if you’re selling deodorant, but not if you’re selling sleep tracking rings or conversion optimization courses.

Alex McEachern put it well in a Smile.io article:

“Many articles out there focus on attempting to measure brand awareness, but I will save you the trouble and tell you that most methods aren’t actually measuring it all. They rely on surveying customers and anonymously asking if they can recall seeing your brand before, which is actually just brand recall.”

Keep in mind, also, that just because I can recall that Spectrum is indeed an internet service provider, doesn’t mean I pay them for their services (regrettably, I’m an AT&T customer). I can name Pepsi in under a second, but I haven’t had a Pepsi in probably a decade.

Social Media Mentions

A super popular method is to look at how many brand mentions you have on social media.

I hate this method.

First off, it’s very difficult to determine the relative importance of a given social media mention using only quantitative metrics. So what does it mean to say 5,000 people have mentioned your brand in the last month? The context could be quite different if you had launched a new product versus your CEO had a scandal.

There is, of course, sentiment analysis, which aims to quantify to some extent the sentiment, or emotional directive, of your social media engagement.

Not only does this have construct validity problems (we’re not quite sure what constitutes a positive or a negative sentiment, realistically), but it might have external validity problems, too (i.e. what people say on Twitter probably doesn’t have a ton of relation to what people say or do in the real world).

Also, who gives a shit if lots of people are talking about you on social media if you’re not selling products? I know that’s not the most academic or polite way to put it, but I’ve not seen concrete evidence that there is even a relationship between the two variables (social engagement and sales).

So the question here is, do you want to be rich or do you want to be famous? [3] If you want to run a business, measure business metrics. If you want to be an influencer, measure your social media mentions.

“Impressions”

This one is the worst. If you think “impressions” equal brand awareness, you’re wrong.

“Impressions” as a standalone metric are used to justify failed marketing campaigns.

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As Daniel Hochuli wrote:

“Ask yourself this question – How much ‘brand awareness’ impact did the last post that you didn’t engage with, have on you?

Do you even remember the last paid post that appeared in your feed? My guess is not, but you can bet that the marketer behind it is telling their superior that you do remember and is counting your ‘impression’.”

Real Estate for Categorical Search Terms

As I’ve mentioned, my ideal brand awareness gauge is both narrow and actionable. By that I mean that your sample exclusively includes your target market and you can actually do something about the number you get.

This metric is something we came up with at HubSpot to track our brand awareness for core product search keywords. This method is most useful for companies using search as an acquisition channel, but I think it’s a good gauge of how the market views you anyway.

Take a transactional or comparison product keyword with some significant search volume, like “best form builder,” and see how many sites that rank for the term mention your brand.

Out of the top 20 websites that rank for “best form builder,” for example, HubSpot is mentioned on 5 of them (or 25% of them):

Note: this data is calculated using a homebrew tool I built with R and hosted with Shiny. Email me if you’re interested and I’ll show you how I built it.

You can easily manually get this data if you only have one or two keywords, or you could hack together a crawl of the top 20 pages using Screaming Frog and Excel.

Again, this is especially impactful for those making their money with search, because you can impact the number. Not mentioned on many of the sites that rank? Start partnering up, producing content, and finding a damn way to appear on them! It’s where (potential) customers are looking to find solutions just like yours.

Even if you’re not using SEO to acquire customers, though, it’s a good temperature check for how important publishers think your brand is for a product category.

For example, here’s how often “casper” appears on the top 20 for “best mattresses”:

This data (like a lot of data) is even richer used comparatively. If you know how often your competitors are mentioned, it puts a good benchmark on the line for you to aim for.

Review websites

Review websites like G2 don’t only measure awareness. They also measure sentiment and show feature comparisons.

So they’re a bit more comprehensive, but they can still give a great indicator of where you stand in the market.

What I like about these sites: they’re 3rd party entities and they include qualitative data like the sentiment of your reviews. They also compare you to competitors, so you don’t just get an isolated number that you don’t know what to do with.

The big problem with most of these sites, though, is that most either operate on a CPC or an affiliate model, so they’re uncomfortably similar to bullshit extortion sites like Yelp is to small businesses.

The big exception is G2, which is an amazing resource for software buyers and businesses alike. If I were you, I’d keep a close eye on my G2 ratings:

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You seem skeptical, Alex. Is there anything valuable about brand awareness?

It all depends on our definition of the term. My beef is that we aren’t defining what we mean when we say brand awareness, so we’ve got a veritable tornado of different metrics that all serve only to obfuscate the customer journey, rather than to illuminate it.

I’ll repeat what I said above. Brand awareness metrics should adhere to two principles:

1. They should sample only those in your target market, the narrower it is defined, the better.
2. They should be actionable. Trivia is fun, but it has no place in business.

An addendum is that a great metric has context, both within the market and over a time-series. You should be able to stack your brand awareness against other competitors and you should be able to see if you are gaining or losing over time.

Also, maybe we shouldn’t expect metrics to solve every aspect of business decision making for us.

You’ve Just Gotta Believe!

In fact, I think one of the major problems in our data-driven age is when we try to apply science to problems of art.

In other words, if we can’t measure something, trying to do so is mostly wasted effort and storytelling to make ourselves feel good about being “data-driven.” It reminds me of little kids wearing suits and playing house – adorable but a naive facsimile of the real world.

Not all marketing can or should be driven or supported by data.

What can be, should be (particularly experiments and actions that have fast enough feedback cycles and predictive validity). In areas of uncertainty, however, we should be comfortable enough to take some risks and capture some of that elusive optionality.

There’s also always going to be an intangible aspect as to “why” people actually buy from you.

It’s the emotional, the unconscious, the hidden. Whether that’s driven by your company mission, the customer experience and service experienced, or because of the premium and luxurious look of your brand logo, it falls under the bucket of the emotional for me.

At HubSpot, we often talk about “winning hearts and winning minds,” where winning minds is the logical and the quantitative, the stuff we can attribute and track.

Winning hearts, then, constitutes things like being thought leaders, pushing interesting ideas into the ether, and inspiring people. You could bucket this into “brand awareness” if you’d like, but I think that term is overly myopic and doesn’t describe the depth and talent that goes into winning hearts.

So really, just eat the humble pie and realize you’ll never be able to attribute every marketing touchpoint to an end sale, and be okay with that.

Clearly brand messaging and awareness level campaigns have an impact, let’s just not play house and pretend that a failed webinar was actually not a failure because it had a lot of impressions or whatever post-hoc justification we use.

Structurally, I like to frame as an 80/20 rule, which I’ve borrowed from Mayur Gupta:

“Do your growth efforts and performance spend benefit from a strong brand (efficiency and/or effectiveness or organic growth)? Are you able to measure and correlate?

Think about the 80–20 rule when it comes to budget distribution — if you can spend 80% of your marketing dollars on everything that is measurable and can be optimized to get to the “OUTCOMEs”, you can spend 20% however you want. Because 100% of marketing will NEVER be measurable (there is no need).”

Also, don’t do brand marketing if you’re a startup.

Final thoughts on brand awareness

“Brand awareness” is a term used loosely and blithely to describe top of the funnel marketing activities, but in reality, many of the methods we use for tracking it actually measure distinct things entirely.

Campaigns without directly attributable conversions can be impactful. That’s why smart companies and growth teams bucket their actions into a portfolio like Mayur Gupta suggests – 80% trackable spend, 20% however you want. 100% of marketing will never be measurable.

Yes, you have to be aware of a product in order to try it (which is somewhat of a tautology), but brand awareness may also be an emergent property of doing a bunch of other things really well.

In the words of Bob Hoffman, “Well, I’m afraid I have a very old guy opinion. You want customers raving about your brand? Sell them a good fucking product.”

[1] The “SEO-ification” Test

First off, when I started researching the topic of brand awareness to see what others think of it, it immediately struck me that every search result was carefully formulated to rank for the term “brand awareness.” In search results like this, you’ll notice a few common themes:

1. First, almost all of the content is relatively similar. Sure, titles are a bit different, and maybe one is longer than the other. But for the most part, reading 6 articles in one of these search results doesn’t give you 6x the value of reading one; it doesn’t even give you 20% more value. It’s basically like reading the same one over and over again.
2. Second, all the content is kind of…vague. I can’t find the word for how I want to describe this content; the closest thing I can do is borrow Benji Hyam’s “mirage content” concept. It looks like a duck, quacks like a duck, but for some reason, it’s just not a duck. There’s no substance, and you can tell the author is just rehashing others’ information.

Terms with search results don’t mean that the term itself isn’t to be trusted. For example, “conversion optimization” has been super SEO-ified, but obviously, conversion optimization (the real definition) is a legitimate practice. It’s just that the stew has been poisoned by know-nothing opportunists (ie lazy marketers).

Similarly, brand awareness could be a tangible and important concept. But with search results like these, it’s wildly difficult to figure out what exactly that concept is.

[2] Who Do We Deify?

Another heuristic I’ve come up with when researching marketing topics is what the example landscape looks like. In other words, in a random blog post, which companies and case studies are chosen, how diverse are the examples, and what does that mean for the generalizability of a topic?

In “brand awareness,” everyone seems to talk about Coca-Cola, Apple, and P&G products.

This would seem, then, that “brand awareness” as a concept either mostly relates to or mostly benefits large consumer brands. There are few, if any, case studies are “brand awareness” with regards to quiet but successful B2B software brands.

[3] Fame vs Fortune

Matthew Fenton wrote a great essay on brand awareness (I’m mostly saying that because I agree with all of it, and it is very cynical about the objective). I love this quote:

“You know who has great awareness? Martin Shkreli. So too does Travis Kalanick. They’ve both found themselves in the headlines throughout the year — but does mean you’re going to be doing business with them?

As a consumer, you’re aware of hundreds of brands that you have no opinion about. Or just don’t like. Or bought once and would never buy again.

Brand awareness isn’t that hard to achieve. You can get it with a big budget, shock value or simple longevity. But if you believe the adage that people buy from those they know, like and trust, then awareness only gets you the “know.” “Like” and “trust” are other things entirely.”

In this sense, “brand awareness” is noise that actually clouds the signal of what actually matters – customers and how much they like you and your business.

If you want to be well-known, maybe your brand should start a TikTok account or something.

The post Brand Awareness is Basically a Meaningless Metric. Here’s Why. appeared first on Alex Birkett.

The short answer: this type of content is pretty darn cheap to produce.

Don’t get me wrong, I’ve produced and directed a fair amount of these types of posts.

But this article will explain the cost of content production, and why that matters if you’re a marketing manager (or just a simple content reader).

The Cost of Content: A Sliding Scale

There’s a cost of creating content, and whether that cost is low or high has direct implications on how well you can trust the content, how competitive it is to create that type of content, and how easily you can produce that content (particularly at scale) if you’re a business.

What is the “cost” of content?

When I say content has a “cost,” I don’t necessarily mean that in a direct sense.

Of course, a blog post does cost something, and that cost is particularly apparent when you either a) hire a content marketing manager or b) contract with freelance writers.

In the former, you understand content “costs” based on the resource and time allocation of your employee. A content marketing manager, even a great one, only has so much time in a day to spend writing and editing content.

An in-depth research report “costs” more than a listicle in the sense that it takes more time to create, which leaves an opportunity cost wherein you could be publishing more or different content.

If you’ve ever hired freelancers, you know the qualitative difference between hiring a content farm and hiring a top notch writer. The secret, from a business perspective, is that both sides of the spectrum can and do work from an ROI perspective.

I also want to point out that there is another, indirect cost of content: a piece of content could be “costly” in the sense that it involved years of experience to come up with an idea or piece of knowledge (look at the Animalz blog or Paul Graham’s essays – they don’t happen overnight).

As Whitney Wolfe Herd said on Tim Ferriss’ podcast, “The most expensive currency in the world is experience.”

It could also incur a cost if there is a substantial risk to writing it.

For instance, if a well-respected conversion rate optimization expert publishes an article on their CRO strategy, the costs, in the event that it fails to land or if potential clients poke holes in the essay, are much larger than if a random writer publishes a CRO strategy article (they have no tree to fall from).

Cost can be in the form of time to production (including years of experience), reputational risk, or in actual monetary value of materials and resources to create something like video or a research study.

Another very important point: the quality or value of the content is exogenous to the cost of creating it. That is, while cost is correlated with quality (pricy content tends to be better), there’s nothing inherently better about content because it is costly.

I want to drive that point home here: “cheap” sounds like it means “bad,” but it really just means there’s a low cost of production and a low barrier to entry. It’s not necessarily bad, it’s just more likely to be bad because of that low cost and lower barrier to entry (which I’ll go over in a bit). In aggregate and categorically, quality and cost do correlate:

The Business Case for Cheap Content is Strong

In business, you should try to maximize the delta between the cost of an action and the reward that springs from it.

If you can produce a cheap piece of content that gets the same or better results than an expensive one, why would you waste the resources on an expensive one? That’d be bad business.

Here’s an example: product listicles do super well for us at HubSpot. Not only do they bring in a ton of traffic, but they are conversion generating machines as well. Compared to other content, they’re easier to produce as well:

I’d be remiss if I didn’t mention that the “cost” of this content is partially hidden. HubSpot has been investing in content, and thus their domain authority, for years, so what we see now is really a cumulative return based on all of the years of previous effort.

…which is actually partially the point I want to make here. Cheap content won’t work if you’re new. Cheap content has a pivotal business purpose if and when you have the ability to rank it.

Huh?

When you’re first launching a website and up until you have the ranking power of the biggest competitors, you have to compete on quality or differentiation. There’s no other way to break through the noise.

Essentially, in the beginning, you need to “do things that don’t scale,” which is the sweat equity you put into the later ability to rank cheap content (templatized, UGC, etc.). A blog post on Atrium.co outlined this perfectly, and this graphic sums it up:

While there’s no set point or clear milestone when you can start to rank cheaper content, there does seem to be a “takeoff point” where it gets easier. It does seem to hit an inflection point though. In my experience it looks a bit like this:

From working at a few content-heavy companies and with many clients, I’ve learned detecting that point is a mixture of two things:

• Analyzing the competition and making assumptions on feasibility (and building a growth model based on those assumptions)
• Publishing some content to get a gut feel to where you typically land on Google.

The former helps you architect the strategy before you start, and the latter is crucial for updating your priors.

I’ve found that for the analyzing competitors and assessing feasibility, this advice from Ian Howells in a GrowthHackers AMA is pretty great:

“I use a blend of search volume, intent, and “attainable position”. With any given project, I look to find the leader in the space. So if I was going to work on a site about outdoor/camping products, I’d likely toss REI into aHrefs and spit out all their keywords over 500 searches per month.

I’d then make an assumption about how close I could get to REI’s rankings – say (for sake of argument) I was assuming I can get to 4 spots lower than REI. I’ll just run a new column in excel/google sheets adding 4 to all of their rankings.

That new “attainable position” plus a CTR curve gets me a ballpark on the amount of traffic I could realistically hope to get for the site.

A pivot table to roll these up by page then gives me a map of what pages I need and what the potential traffic is per page. I’ll start with the biggest opp pages and just work my way down.”

You can find average CTR data on SERP positions here and make your own assumptions to build a model. It should be a pretty quick exercise, because when rubber meets the road, it’s rare that you’re very accurate.

However, when you do start to produce content, you’ll develop a fingerspitzengefuhl as to how much effort and resources you need to invest to outrank your competitors. It’s likely more than you had planned on upfront.

That’s why the key to content strategy, at least in the early stages, is in investing part of your strategy in building out link assets, top of funnel content, and highly socially shareable content. That’s the stuff that will build up your overall website presence and authority so that later on down the line you can write and rank cheap content (and also bottom funnel content and produce pages).

To recap, cheap content is economically smart for businesses to create, but it only works after investing time and effort into decidedly expensive content. Start with noteworthy, remarkable content in order to break through the noise, and then you can experiment with templatized content, UGC, etc.:

This is why content marketing is said to be a “flywheel.” You put some work in, that force remains constant, and the more effort you put in, the more returns you generate consistently with time.

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Beware the Barrier to Entry (Why Cheap Content May Not Be a Long Play)

The cheaper the content, the more competitive it will be to break through the noise. The barrier to entry is wildly low to write a roundup post (you don’t even need to write anything, really). Therefore, more people will enter that space, and you’ll have a harder time standing out.

Not only that, but you can be easily knocked off your pedestal by an upstart who’s willing to invest more in creating better content.

Easy example: everyone in the world can put together a loosely curated roundup post, but very few people can conduct original user experience research studies.

To go to an extreme length, if you and a team worked together on a project for two years, no one else but you and the team could tell the same story. Your cost to producing a piece of content in that regard is high, because you put in two years of work to get to the point of writing it.

That’s not to say that cheaper content formats are inherently low quality. A well-curated roundup post with true experts can be massively valuable (though I’ve rarely seen them, I have to say).

Similarly, expensive content can be poorly produced as well. Just because you worked on a project for two years doesn’t mean you’ll have anything valuable to say about the process (or especially that you’ll give an objective write-up of what you did).

That’s a sunk cost, and nobody else cares how much time you spent writing a blog post.

However, if done right, an expensive content strategy can be a powerful moat. The more expensive the content is to create, the harder it is for people to replicate what you’ve done. No one in the world can write the way Tim Urban does. You can’t compete.

This is often the case with powerful thought leadership and original research. Many will try to replicate it, but it’s very near impossible to beat the initiator.

Don’t hold onto expensive content as a silver bullet method to get early results, though. In the early days, we produced lots of UX research at CXL Institute. The result? They performed largely the same if not marginally better than a normal blog post.

I’ve touched very little upon business results and outputs of content, because that’s not the point I wanted to make here. But to point out the obvious; if you can get outsized rewards for producing the cheapest content possible, that’s obviously the best business decision you can make. It’s likely you won’t be able to do that, at least sustainably and at the beginning of your journey, but this is a business decision after all.

Now that we’ve got the business-side of this whole “content economics” thing out of the way, let’s dive into the fun and somewhat rant-y stuff from the reader side of the equation.

Cheap Talk and Teardowns: The Shortcomings of Cheap Content

A months ago, I randomly stumbled upon a blog post that was critiquing a campaign I had launched. It was all (mostly) praise. Still, it felt weird.

Some of the takeaways were questionable, but overall I felt flattered. It was nice being recognized.

I mentioned this critique to a friend, also in marketing, and he said, “dude, that type of content is super cheap to create. It’s easy to write those and get some quick social shares.”

That thought lead me to think about the value, accuracy, truthfulness, and benefits of writing (and more so, reading) critiques written by people looking in from the outside.

This seems especially pertinent now, as the new trend in content seems to be writing case studies on successful companies and how they got there (or what Ryan Farley calls “fake case studies.”)

This thought is really what led me down to the idea of “the cost of content production.” It started out as a cynical brush off towards bad content creators and led to a somewhat pragmatic angle on content marketing strategy.

However, I’d feel bad if I left out my thoughts on why cheap content may actually externalize its cost to the reader. In other words, cheap content is probably contributing to a worse world (or at least a noisier world) and many of us are complicit.

All Talk, No Walk (and Why You Should Value $ Over Opinions)

I’ve done a few landing page teardowns in my life.

There’s a nervousness to doing these, for me. I always wonder, if when presented the landing page or website, will I have anything useful to say? Without seeing any of the site’s data (or even if I could see their data), what gives me the right to critique their CTA color or copy?

Still, I’ve seen lots of landing pages, run a ton of A/B tests, read through hundreds of UX research papers and articles, and have a solid understanding (for a layperson at least) of behavioral science. This, at least, gives me some sort of justification for the remarks I make.

Consider this, though, before you trust my experience-based wisdom:

I may spend a few seconds talking shit about a website for not having a phone number on their homepage. Or having a CTA below the fold. Or having a vague headline. Or whatever best practice you want to talk about.

But in this context, I am not the customer, and I do not have my credit card out. My opinion is almost (almost!) worthless.

The Halo Effect and “Why X Company Grew”

Another thought experiment.

This one explains why even an expert, someone with years of startup experience, for example, could mess up a case study analysis. It’s called the halo effect.

It’s much easier to talk about “How Netflix Grew,” or “Why Casper’s Marketing Works” when you’re analyzing a winner. Everything looks great under that light! But what happened to all the losers who did the same things people attribute as success factors to the winners?

Let’s pretend we had a CRO or UX expert who had the exact same knowledge and skill level as any other top CRO or UX expert, but for some reason they had never heard of Amazon.

If you asked them to teardown Amazon’s website experience, given that absence of knowledge, how different would it look from a CRO or UX expert on planet earth who had heard of the gigantically successful company?

If our opinions and teardowns are valuable, then one should expect zero difference between the critiques. Thank god we have experimentation.

That’s why I have trouble respecting case studies written on “How [X Super Successful Company] Grew.” The halo effect is almost always going to ruin your hindsight view of what a company did right or wrong (how many companies did the same things as Airbnb but failed? We’ll probably never know).

That’s not to say you can’t learn things from breakdowns, case studies, etc. You definitely can!

In the context of landing page teardowns, people develop a type of fingerspitzengefühl for these things, and you can also learn a lot of underlying psychology and UX principles from these things. The author of a case study can interview the company in question. The author can simple pour tons of hours into truly understanding a given aspect and pulling insights from it. Running 1000 experiments gives you credentials to tell someone how to run their experiment.

But as the reader, you need to know whether that person has run 1000 (or 10, or 1) experiments, and you need to know just what level of knowledge and research went into that case study or breakdown.

Again, I’m guilty of a lot of this stuff.

I’ve given quotes on things I barely know anything about about.

I’ve written listicles, roundups, and other forms of cheap content. I like backlinks, what can I say?

But it’s an externalized cost, because the reader has to spend time and effort wondering, “can I trust the advice of this commentator?” while I get the backlink whether or not I know what I’m talking about. It’s the world we live in. (further reading: There Ain’t No Such Thing As Free Lunch in Content Marketing)

I’ve spent maybe $20,000 in my life on Facebook ads, hardly a huge expert

Here’s the rub: if you’re not skeptical (maybe even cynical) it’s hard to know who walks the walk and who talks the talk. The benefit to the content creator is the same whether they know what they’re talking about or not (more on that in a bit). It’s up to the reader to discern “fake news” from real value, which is a heavy burden.

This is actually a massive benefit to the content creator. In reality, it’s why the roundup post is so popular. There’s no risk; it’s only upside.

How to Write and Judge a Case Study

Bad case studies, in particular, can be dangerous to readers in ways that listicles aren’t. They’re often viewed as authoritative and sources of truth, when in actuality they can be surprisingly speculative.

I highly recommend reading Ryan Farley’s post on this. He nails it. Here’s a quote:

“So these case studies are cheap and intellectually dishonest.  But what makes them harmful?

They are harmful because they can mislead people, no matter how good their intentions.

I’ve been around the block long enough to recognize cheap content when I see it.  But four years ago, I didn’t recognize this.

I took this crap seriously.

When you produce this stuff, there’s a chance that someone actually tries to apply the ‘lessons’ you are teaching.

When answers are tough to come by, it’s easy to want an easy answer or to be able to simply adapt what another has found success with.”

When I say that the cost of cheap content can be externalized to readers that’s what I mean. The author/website ranks, it costs little in terms of time or reputational cost, but the reader may or may not waste days, months, or years implementing completely fallacious advice.

Great website on BS case studies. Visit here.

This BS case studies problem was something I was hyper aware of while working at CXL.

Bad case studies in the CRO space were (and still are) a plague, and they contributed to a poor understand of what CRO was actually about. Therefore, we were combative about bad case studies spotted in the wild, but also meticulous about how we published our own case studies.

So we put forth some maxims: if you’re going to publish a case study, you should publish the losing tests as well as the winning tests, the full data set (obviously keeping in mind client confidentiality), and your justification for doing what you did.

Here are the exact words Peep Laja, founder of CXL, wrote regarding A/B testing case studies, and what could make them valuable:

• Tell me how you identified the problem you’re addressing
• What kind of supporting data did you have / collect?
• How did you pull the insights out of the data you had?
• Show me how came up with all the variations to test against Control, what was the thinking behind each one
• What went on behind the scenes to get all of them implemented?

We were largely railing against sites like WhichTestWon (RIP), where they provide no context, only gamification and advice as insightful as “blue is better than green buttons.” But it applies more so when you consider the larger space of “case studies,” especially those written by people who don’t even work at the company they’re analyzing (!)

Professional writers have trouble filling books with this topic, so how can a blog post do it justice?

Here’s what I look for when reading these posts:

• Did the author work on the project?
• Do they have something to gain by writing the case study?
  • What is it?
• Do they have something to lose by giving bad advice or being wrong in their critique?
  • What do they have to lose?
• Is all the information present? Is there anything fishy with the findings?

Essentially, we can look for “skin in the game.”

If the owner of an SEO agency, someone with 10 years experience and many clients, writes a case study on SEO, they can still be wrong. They have a pretty good incentive to make their work look better than it is, but that’s an easy bias to spot.

But they also have a) something to gain (recognition), but also b) something to lose. Basically, if they give transparently bad advice or information, their reputation is harmed and they can lose clients or industry respect.

Conversely, a record of amazing content positions you in people’s minds as a trustworthy writer, consultant, voice, etc.

This is truer in some industries than others, which is why you’ll rarely get away with being a grifter in the analytics space, but you may be able to as a social media influencer (sorry if you’re a social media influencer, but a quick look at the conversations in those two industries makes the difference obvious to the eyes.)

This isn’t the case with a writer who is looking for social shares and backlinks when they write a breakdown on “How Trello Grew.” It’s all upside for them.

Other than Ryan Farley’s great article, if you want some help with identifying good vs bad case studies, specific to the CRO space, I suggest reading Justin Rondeau’s excellent piece on how to read a case study.

Be Wary of Content with Asymmetrical Benefits

People who make predictions for a living don’t suffer the same loss as those who follow the predictions they’ve made.

People who give advice for a living don’t suffer the same loss as those who follow the advice they’ve given.

Caveat emptor, as they say.

Here we have a rule, from Nassim Taleb’s ‘Skin in the Game’:

“Always do more than you talk. And precede talk with action. For it will always remain that action without talk supersedes talk without action.”

When consuming any content, think about the asymmetric risks vs. rewards involved with the person who created the content. If there is little downside for the creator, I’m not saying it’s certainly BS, but be wary.

Imagine a roundup post with three people on it: Peep Laja, me, and a writer who has never run an A/B test.

• Peep has many years experience in CRO and has run thousands of experiments.
• I have a few years experience and have run tops 80-100 experiments.
• Then the writer has never run a test and can’t say they’ve ever done true “CRO.” In fact, they’ve barely heard about CRO, save for a blog post written by Neil Patel a few years ago.

So it’s fair to say that is “cost” Peep more to give the advice in the roundup, simply because he had to invest more time and effort into gaining the knowledge and experience. Not only that, Peep has a reputational cost on the line, as he’s appearing in the same paper as a nitwit with no knowledge (not me, the other person!). The nitwit only has something to gain by being featured by those around him.

Yet we all get the same benefit: recognition and a backlink.

The audience gets a variable return: Peep’s advice is expensive, mine is less expensive, and the writer should have to pay you to give you advice. In fact, the cost of scrutiny is placed fully on the audience. This (in the broader world, not just in marketing) is part of the reason it sucks so much to read news: it’s so hard to parse out what is bullshit from what is true now.

Things that contribute to asymmetric benefit (and “penalty-free” content creation):

• HARO
• Roundup Posts
• Scaled out keyword-based content (think Livestrong or other 400 word post content farms). These do have the negative that Google’s algorithm seems to weed them out with time.
• Prediction posts (what will marketing look like in 2019?)
• Baseless, opinionated critiques and teardowns

What’s there to say? You have to play the game if you want to benefit from content and SEO, so there’s no way to disincentivize bad authors. Like I said, I’ve given quotes for things I don’t know very well.

Want a cynical end to this story? There’s probably no real way to solve the problem of opportunism and asymmetric risk in content marketing. Why would we take advantage of a backlink, exposure, traffic, or whatever, if we’re given the chance?

Instead, the solution to the discerning reader here seems to be the frustrating advice: caveat emptor. Read things with skepticism.

Conclusion

It’s hard to know what to trust online. There’s the new “fake news” thing, but there’s also a phenomenon of content that is “real,” whatever that means, but without value for the reader and without penalty for the writer. Mirage content.

You can never fully remove this asymmetry, as even knowledgeable authors can give bad advice and vice versa.

The solution seems to be a simple but difficult one: read with skepticism, and call out true charlatanism where it is evident. Additionally, read intellectually honest and rigorous authors more regularly and promote them to the world.

Further, I’ve found that opinionated pieces tend to be pretty valueless, in aggregate. How to pieces, walkthroughs, and data-driven content seem to be pretty important, especially when you’re trying to solve a specific problem.

I’ve found that if you put the blinders on to marketing ideology (other than the fundamentals), and just put your head down and do the work, share knowledge with others on your team and in your industry (informally and privately, even better, as there’s less incentive to posture – the best info I’ve ever learned is at the after party of a conference or meetup), things work out pretty well. You can safely ignore most noise on the internet, anyway.

Content producers: find your edge, weigh costs of production with the expected return and keep in mind barriers to entry (the lower it is, the less likely it is you’ll truly lift above the fray, unless you’re already way above the fray, then publish away) as well as long term moats.

Finally, outside of business, all good art is written with blood. You can’t half-ass masterpieces:

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The post The Economics of Content Creation (or Why Most Roundup Posts Are Awful) appeared first on Alex Birkett.

This is something I’ve focused on for years, mostly because all the companies I’ve worked for, from super early stage startups to HubSpot where I work now, have been largely supported by content marketing (in one way or another).

However, each company’s content marketing strategy was different, though all of them successful.

Most blog posts on content marketing strategy focus on what are assuredly tactical considerations – stuff like how many words your blog posts should be, what content format you should produce, and how to share on social to make shit go viral.

Even the good advice on content marketing strategy is usually too narrow – it comes only from the direction of the company giving it. If something works for Microsoft, that doesn’t mean it works for a startup, and vice versa.

If I were asked to come in and launch or consult on a content marketing strategy at a new company, this is how I’d approach it (this guide is also based on a training I give and is covered extensively in my content marketing strategy course).

Introduction to Content Marketing Strategy: What We’ll Cover

If you’re new to content marketing, read the whole thing. If you care about a particular section, jump around.

Sections:

• Preparing for Battle
  • Buyer Personas
  • Content Audiences (and Why It Isn’t Always Your Core Customer/User)
  • SWOT and Strategy Audits
  • Estimating Impact and Feasibility of Your Strategy
• The Economics of Content
  • Cheap vs. Expensive content
  • How much does it “cost” to rank?
  • Maximizing Resources & ROI
• Content Planning
  • How Buyers Search, and How Searchers Buy
  • Business KPIs and What to Track
  • Keyword/Topic research
  • Content Models (Pillar & Cluster Model)
• Content Creation
  • Link + Share hooks
  • Promotion tactics
  • Measuring Results
  • Content Optimization
• Content Auditing and Maintenance
  • Looking Forward & Changing Course

Yep, it’s gonna be a big guide. Let’s do this.

Preparing for Battle (the Building Blocks of Content Strategy)

“If you know the enemy and know yourself, you need not fear the result of a hundred battles. If you know yourself but not the enemy, for every victory gained you will also suffer a defeat. If you know neither the enemy nor yourself, you will succumb in every battle.” – Sun Tzu

Knowing yourself consists of knowing your strengths and weaknesses, and it also consists of knowing who your customer is and how you will reach them (and win their love and loyalty).

Knowing your enemy means knowing the competitive landscape as well as the content marketing space as a whole, and understanding how you can operate on an edge that you can win.

We can also say: know your landscape. This consists in knowing not only your customer and your competition, but the influencers, blogs, publications, and platforms you can use to distribute and amplify your content, and how you can use these tools to reach your potential customers.

You do all this before you ever put pen to paper, by the way; but you also refine this knowledge over time and with new learnings. These are the formative steps to take, before you ever begin your content marketing efforts, to come up with a master content marketing plan.

Buyer Personas (a Quick and Dirty Guide)

The first thing to think about when embarking on a content marketing program is who you’re hoping to reach, your target audience. Who is your buyer, how do they prefer to learn about products, and what type of language do they use to describe their problems and hopes?

For these questions, buyer personas can be invaluable. Creating buyer personas can help you answer questions like whether or not you’ll be able to reach your audience via search engines or social media (and which social media networks), which types of content they like to consume (are case studies even effective? How long should a given blog post be? Should we look into podcasts?), what their pain points tend to be, and in general, how best to formulate your marketing goals.

These aren’t just content marketing problems, of course. Personas are also helpful for product strategy and go-to-market strategy, among other things.

I’ll briefly cover the dos and don’ts of buyer personas here, but if you want a really robust method of doing personas, read this guide.

First, what is a persona? This is my favorite definition:

“Personas are fictional representations and generalizations of a cluster of your target users who exhibit similar attitudes, goals, and behaviors in relation to your product. They’re human-like snapshots of relevant and meaningful commonalities in your customer groups and are based on user research.”

I’ve bolded several parts, because I think ignoring them is largely why most personas suck and why they fail.

Fictional representations: Your persona isn’t a real person, so it shouldn’t be a successful customer or account you choose to profile. It’s a generalization that is used to help craft messaging, campaigns, and business decisions, so it needs to be somewhat loose and archetypical.

Cluster of your target users: Your persona won’t be a one-to-one match for each individual customer. Think about it as a mean – variance means that each individual data point (customer) will still probably vary from the average (your persona), but defining the average (the center of the cluster) will still help you reach each individual data point in the cluster.

In relation to your product: Your persona’s characteristics should map to things related to your product and the buying process that a customer goes through to reach your product and use it. The dimensions you define shouldn’t be stupid and irrelevant things like their eye color, gender, or if they like to ski (unless you sell skis).

Relevant and meaningful: I just wanted to repeat that your persona shouldn’t be a cheesy representation of a cartoon character with a cute name and hobbies and interests that aren’t relevant to what you’re doing with your business. Leave the superfluous character development to your novel writing side hustle.

Based on user research: Very important! Don’t make shit up! Do your research. Apply evidence-based personas, and you’ll make better decisions. Though you’ll never reach the perfect representation of your customer, you do want what you define to be accurate.

So a good persona might look like this:

A bad persona might look like this:

I’m not trilingual (yet), and it probably wouldn’t matter if I were (unless you’re Duolingo or teaching people how to learn Spanish). 3.23 blog posts is too specific to be useful, and it doesn’t matter that I’m male, 27 years old, or that I enjoy extreme sports, if what you’re selling is a SaaS tool to better manage your client proposals. And what an atrociously distracting stock photo

A good heuristic: if a model helps you make better decisions, it’s a good model. There’s no perfect model, but models should be consistently directionally accurate and useful. If your persona helps you reach your audience with content, it’s worth creating.

Another note: your personas aren’t static. Audiences change, and so do product strategies. Additionally, you’ll learn more about your customers as you progress, so take a look at your personas every three to six months and update them.

Content Audiences (and Why It Isn’t Always Your Core Customer/User)

Defining your customer is one thing, and it’s important. But it’s also important to note that, in content marketing strategy, your audience isn’t always your customers…

Huh?

See, sometimes your primary audience (who you produce content for) is different than the end audience (your customer). If SEO is your main model, then you’ll need backlinks to make it work, and very few of your customers will have the ability to give you authoritative backlinks.

Even if you’re drumming up awareness and educating an industry on a product they’ve never heard of (and didn’t know how to search for), you’re often speaking first to the influencers in the space, who then in turn speak to your customers.

So the question then becomes: who are your industries influencers? Sometimes, at least in SEO, we call these people the Linkerati (those in power with the ability to bestow powerful backlinks).

Your best bet is to do three things:

1. Know the landscape (understand who is powerful).
2. Make friends with the influencers.
3. Craft content so it appeals to their tastes.

If everyone did just these three steps, you’d hear far fewer people complain about poor results from their content marketing.

Here are five methods for mapping out your influencer landscape/Linkerati:

1. Ask your customers who they read/trust when you do persona research
2. Find top influencers using Buzzsumo (and other methods)
3. Find top blogs and publications using Ahrefs (and other methods)
4. Find “underground” channels where influencers congregate
5. Find the top conferences and meetups in your space

In my opinion, you should do all of these things. If you want content marketing to really work well, networking and relationships shouldn’t be an afterthought, but a core part of how you operate. As Robert Greene suggests, “Do Not Build Fortresses To Protect Yourself (Isolation Is Dangerous).”

1. Ask your customers who they read/trust when you do persona research

If you talk to your customers, ask them what they read.

I build this into my persona research. When I send out customer surveys, I include a few questions like:

• How do you learn new skills/info? (scale, followed by a bunch of factors like “blogs” and “conferences”)
• What publications do you read? (open ended)

You’ll sometimes find that different personas have different tastes in blogs and content. This is an important thing to note, as it can define how your form comarketing partnerships and PR launches.

2. Find top influencers

Apart from publications, you want to identify individuals who command a ton of influence and reach. Sometimes you’ll know these people just by knowing your space. For example, if you’re in the CRO or Analytics spaces, you know that Peep Laja and Avinash Kaushik are influential names.

But if you want to formalize the research process, BuzzSumo is a great tool for this:

You can also look for “top influencers to follow on Twitter lists,” but I wouldn’t stop at these, since they tend to be circle jerks that list the same people on every list. That means the people on the list are constantly getting hounded with requests, so they’ll be less likely to work with you (and probably not as effective anyway).

3. Find top blogs and publications

Content marketing almost always relies on SEO as a distribution avenue, so you’ll want to find the top blogs in your space. First and foremost, look at Ahrefs to find similar domains to your own and your top competitors:

I like to find which sites link to competitors content as well:

Second, you can use a tool like Growth Bot to find organic competitors to different blogs:

Third, you can scrape those awful software comparison aggregator sites like Capterra to find others in your immediate and secondary product categories.

Finally, you probably know a lot of the top blogs or you can search for them with queries like:

“Top [keyword] blogs in [year]”

Put all of these on a spreadsheet with their corresponding domain authority. A fast way to find domain authority is with a bulk domain analyzer such that Ahrefs has.

4. Find “underground” channels where influencers congregate

The people who matter usually talk to each other, and not always on public forums. Sometimes there are Slack groups, and sometimes there are Facebook or LInkedIn groups. Sometimes it happens in person. I can’t speak to the industry you operate in, but you need to get to know it well enough to know where these secret circles are and how you can get invited in. These are probably the most important piece.

5. Find the top conferences and meetups in your space

Gotta get outside and actually meet people face to face sometimes. I find this is my greatest leverage point, as most people just cold email behind a computer, but if you can share a beer with people you can form a true bond. Plus, the “off the record” conversations you have at conferences will far outweigh the value of any content that is written for a public audience.

SWOT and Strategy Audits

What works for one company doesn’t work for another. Backlinko, HubSpot, CXL, WaitButWhy, BuzzFeed, my personal blog – all different content strategies, all successful in their own right.

That means you should never copy someone’s strategy just because it works for them (or God forbid because you saw a representative give a talk at a conference).

In almost all cases, the best case scenario by copying someone’s strategic playbook is that you’ll hit some local maximum that lies somewhere near mediocrity.

HubSpot can publish a handful of articles on long tail search keywords every day and they’ll beat you all day at consistent content execution.

Brian Dean is uniquely suited to publishing infrequent, super comprehensive pieces specifically on the topic of SEO.

CXL didn’t invent research-based long form content, but we executed it to near perfect on a consistent basis. It’d be hard to outperform CXL mimicking that form of content production (at least if you’re also competing for conversion optimization search terms).

So you need to find your edge and exploit it.

How do you do that?

SWOT Analysis

If you’ve ever taken a business class, your eyes may be glossing over at my mention of SWOT Analysis. Or maybe you’re a nerd like me, and you actually enjoy this process.

Whatever the case, the SWOT Analysis is a helpful thought exercise.

How do you complete one? You create a 2X2 matrix, with quadrants representing the following quadrants:

• Strengths
• Weaknesses
• Opportunities
• Threats

Strengths and Weaknesses are polar opposites, but they’re both internal facing (what are your specific company’s strengths or weaknesses?). Similarly, Opportunities and Threats are yin and yang, but they are outward faces (what market conditions represent opportunities or threats?)

If we imagine a random SaaS company coming out of Y Combinator, one with a serial founder, we can fill out their hypothetical SWOT:

Estimating Impact and Feasibility

You also need to weigh your ability to rank for given keywords or compete in your niche. I’m diving into this deeper in the “content economics” section, but briefly, in your SWOT audit, you should think about the feasibility of your strategy.

HubSpot’s esteemed Director of Acquisition, Matthew Barby, said the following on GrowthHackers:

“The biggest hurdle of SEO is knowing what is realistic and what is not, and then being able to decide which is the right lever to pull at that moment. For a site like HubSpot.com, we have a TON of backlinks (which gives the site a load of authority). When we create new content around marketing/sales/service it will tend to rank a lot better than smaller sites because we’ve built up this authority over a number of years. That means we get WAY more leverage from ramping up content creation than a brand new (or even smaller) site.

For a new site, I generally try to shift the focus to building authority vs just publishing a bucket load of content. The questions I try to ask is, “how can I build a steady flow of backlinks into the website?” and “how can I grow the number of people searching for my brand name?” instead of “how can I create as much content as possible.” This sounds simple, but there’s a lot that goes into figuring all this out, and it’s where 9/10 misspent cash comes from.”

While most of this article will focus on SEO, and thus keywords, it’s important to note that’s not the only route to content marketing success and it’s not the only way to bring in customers. In some industries, say the SaaS management niche, buyer’s don’t know what they’re looking for. Or there’s no real word for the term yet, at least not one that is searched frequently.

In spaces like these, there are strategies as well, normally in the form of “thought leadership” style content (also called “movement first” content). Think about HubSpot’s early evangelization of “inbound marketing,” WaitButWhy, or how Paul Graham or Sam Altman write.

Anyway, if you can pull of that style of writing, the one where people simply search your name in Google so they can read your brilliant insights – well, you don’t really need my advice, just keep writing.

The Economics of Content

All content has a cost and an associated return.

Some content, such as roundup posts or listicles, is easy and cheap to produce (and therefore easy to replicate and scale).

Some content, such as original research or thought leadership based on years of experience, is hard and expensive to produce (and thus more difficult to scale, but also more difficult for your competitors to replicate).

In the early stages, it’s likely you’re going to need to work hard and spend more to outcompete the bigger players in your space. Because you have a low domain authority, you’ll need to make up for it in content quality.

Additionally, since you have no audience or build in brand recognition, you need to break through the ‘noise’ in the blogging space, of which there is a ton. Normally this means overindexing on “awareness” level content in the beginning, with the goal that you can eventually easy rank your “consideration” and “decision” stage content that actually brings in the bacon.

However, as you begin to produce content regularly and to learn more about SEO, you’ll likely learn what your “hotspot” is – the minimum effective dose required to rank blog posts and convert visitors. Any additional cost above this reduces your ROI, and especially at scale, incurs consecutive marginal costs.

Normally, it takes an ungodly amount of effort to rank in the beginning stages (up to a DA of about 50 or 60), and then the curve begins to flatten (though never completely) in the upper echelons of website authority. When your DA is that high, as long as your site architecture and technical SEO best practices are followed, you can rank posts with a slightly lower quality (though never too low).

Your long term goal in a content marketing program is to lower the cost of content production as low as you can without compromising on brand promises or return on content efforts.

At HubSpot, we’re roughly between the “templated content” and “user-generated” content stages. Now, we can produce comparison pages like this one:

We can also very quickly rank “consideration” level listicles, which are comparatively easy to produce and bring in a very high conversion rate for blog posts:

The effectiveness of templatized content only comes with scale and maturity though. For one, you need the domain authority to rank tons of posts without crafting individual promotion or link building campaigns for each (which would rapidly augment the costs of your content marketing program).

Second, you need a lot of production resources and infrastructure to make templatized content work at scale, especially if you’ll be running SEO experiments on them or hoping to do any conversion optimization on them.

Content marketing, like many facets of marketing, is a flywheel. The more you add to it and the more energy you put into it, the faster it spins (and the rewards compound with time). You put in the effort early in order to reap the rewards later.

So in the beginning, it may help to plan out your transactional pages and bottom funnel content. But don’t expect to rank that stuff incredibly quickly without having some solid strategy to build up your authority. Generally, you can do this through a) lots of high traffic/high interest awareness level content on the same topic b) a shit load of link building or c) being in an uncompetitive space.

…or some combination of the three. However, if you want to make content marketing work, in the beginning you should expect to invest a lot more time than you’d like to in awareness level content (it’s the leverage that gets you the returns down the line).

How Much Does it Cost to Produce Content That “Wins”?

• How much effort do you have to put into a piece of content to get it to rank?
• How many words is it?
• How long does it take your writer to write?
• How many hours of promotion, link building, and distribution do you need?

The potential “cost” here is infinite (just look at a WaitButWhy article). There’s usually a point of diminishing returns you want to aim for with production quality and cost. The tough part: it’s really hard to prescriptively say what that is for any given industry.

In B2B SaaS, it used to be that you could write a 2500 word article with an added infographic, because all the others were only 2000 words. It’s becoming harder to do that because of increased competition. Additionally, it’s not only about word count, but about content density.

Now, in B2B SaaS, you may actually have to invest in a “topic cluster” that consists of many slightly related blog posts if you want to have a chance ranking any of them, let alone all of them. It might require significant link building as well.

(More on constructing Pillars and Clusters below)

In general, the best way to gauge the content quality necessary to rank is to look at what’s currently ranking for keywords you want to go after. This can be as simple as a Google search (even better if you’ve installed Mozbar to see DA and backlinks):

You can also use Ahrefs’ keyword explorer to view the landscape of a search term:

Finally, after writing a few posts and seeing where they land after publication, you can get an intuitive sense of how strong your site authority is. This gives you a fingerspitzengefühl when it comes to content production.

Maximizing Resources & ROI

When you understand how much effort it takes to rank, you can model out what it would cost to achieve the goals your organization hopes to achieve.

Let’s say it takes, on average, a 5000 word pillar page to rank for super competitive terms (“customer satisfaction”) and 2000 words to rank for long tail and less competitive terms (“how to measure customer satisfaction”). Let’s say a 5000 word costs you $1000 and a 2000 word post costs you $300. In addition, you need to do some manual content promotion and link building, and let’s say that costs about $250 per blog post and $750 per pillar page.

Now, you can tie that in with any SLA or quarterly traffic and conversion goals you have. It makes it vastly easier to calculate a content budget, and it also helps you to realize if your plan, given the costs, will even potentially be able to hit your goals you’ve set.

Basically, just calculate your minimum viable production capacity as well as the maximum resources you could potentially allot to your content marketing program.

• What’s the average time to produce a piece of content?
• How many producers (writers, designers, etc.) can you put on task?
• What’s the average time of promotion and distribution?
• Given those numbers, how many pieces of content can your produce in 1 year (and 1 month)? Does that match up with your expectations in terms of traffic or conversions?
  • If not, which levers can you tweak to meet those goals?

Here is where knowing how to build a growth model helps a ton.

Ian Howells had an even more robust way to model out search traffic potential. Here’s a quote from his GrowthHackers AMA:

“I use a blend of search volume, intent, and “attainable position”. With any given project, I look to find the leader in the space. So if I was going to work on a site about outdoor/camping products, I’d likely toss REI into aHrefs and spit out all their keywords over 500 searches per month.

I’d then make an assumption about how close I could get to REI’s rankings – say (for sake of argument) I was assuming I can get to 4 spots lower than REI. I’ll just run a new column in excel/google sheets adding 4 to all of their rankings.

That new “attainable position” plus a CTR curve gets me a ballpark on the amount of traffic I could realistically hope to get for the site.

A pivot table to roll these up by page then gives me a map of what pages I need and what the potential traffic is per page. I’ll start with the biggest opp pages and just work my way down.”

Beautiful.

Content Planning: Creating a Roadmap and Course of Action

At this point, we have a rock solid strategic underpinning as well as a content growth model and expectations of how to hit our goals. Now how the hell do we plan and produce the actual content?

This section will cover keyword research (topic ideation), content production, and promotion.

How Buyers Search, and How Searchers Buy

We’ve touched on the idea of the buyer’s journey already, but generally speaking, it looks like this:

We start at a high level, attracting general readers who probably don’t know about your business yet. Through compelling content and search strategy, we hope to bring them down to the consideration and decision stages, where hopefully they’ll choose to buy from us.

In content marketing strategy, each stage has specific goals.

Awareness stage goals:

• Build links and domain authority + page rank.
• Cast a wide net and bring in relevant traffic (though it may not convert right away, except maybe to an email list or lead magnet).
• Build up your “topical authority” and expertise to help you rank commercial terms.
• Build relationships with influencers and movers and shakers in your field
• Build demand and interest.

Consideration/Decision stage goals:

• Convert traffic into users or customers.
• Rank for core business terms.
• Educate buyers and differentiate your business.
• Sell.
• Capture demand.

A proper content strategy includes all parts of the buyer’s journey. An unbalanced strategy will never produce the results that a holistic one will.

Business KPIs and What to Track

I’ll breeze through this part because your specific goals will depend on your business. Generally speaking though, you’ll want a way to track the following:

1. Website traffic data (traffic source, pageviews, etc)
2. SERP tracking (position, CTR, visibility)
3. Conversions and business metrics (average order value, email signups, etc)

Depending on your business, those business metrics could vary. Sometimes, it’s a simple as an email subscription. Sometimes, it’s a marketing qualified lead. Sometimes it’s a customer.

Who am I to tell you your business’s goals though? Jot these down before you begin creating content and make sure you have a way to track them.

Keyword/Topic research

To start with keyword research, I like to get a bird’s eye view of the space I’m trying to conquer. For this, you can use Ahrefs to analyze competitors’ sites and see what they’re ranking for. Start by plugging your own in (or if you haven’t started writing, your closest competitor):

You can then use their “competing domains” report to find others in the space.

Without fancy tools, you can also just do a quick Google search for blogs in your niche.

Compile all of these and list their corresponding domain authority in a spreadsheet.

Now, Ahrefs has a really cool tool called “content gap” analysis that lets you plug in a bunch of competitors and see what they rank for but you don’t:

The report looks like this, which you can simply export to CSV.

Or you can individually analyze each website.

If you choose that route, I like the “top pages” report. So much value here!

What you’re trying to do at this step is get a big ass list of keywords that a whole bunch of sites in your niche rank for, but you don’t. Don’t worry about curating the list at this point, just get a big list and put it in a spreadsheet.

Content Strategy Models (Pillar & Cluster Model)

Now that we have a big list of keywords, we want to organize this in some meaningful content model.

Even if we had unlimited time and resources, we’d still want to prioritize the list so we could rank for important keywords faster (thus reaping more of the rewards over time), and so we can strictly curate our site to build topical authority (which Google seems to like – depth over breadth).

Now, there are tons of content models. I like to combine two of them to make a workable content roadmap (or a search insights report, as we refer to it at HubSpot). To start, I like to map out my keywords based on user intent. This is a reflection of the buyer’s journey:

It depends on the business I’m working with what the exact discrete stages are, but I work from high traffic/low intent (awareness) keywords down to low traffic/high intent keywords. At HubSpot, I break normally break terms into “What,” “How,” “Considerations & Tool Discovery” and core decision keywords.

Now we’ve at least broken things down into discrete customer journey stages, but we still need to group things thematically. The goal of this is to internal link all related posts to show Google they are similar, which helps us build “topical authority.” The best framework I know for this is the Pillar and Cluster model.

Basically, you plan out a big pillar page topic (“Digital Marketing”) and then write several shorter posts that target longer tail keywords that related to the core term (“How to Become a Digital Marketer”).

Adding a step, I actually like to start from a core product term and work my way outwards. So in this case, my product page would be a “customer feedback software” tool, then I could build a pillar page on “the ultimate guide to customer satisfaction” and then create tons of related blog posts to help it rank.

Also note that you can have many clusters that tie-in together. For example, “digital marketing” is related to “lead generation” and “email marketing” as they’re all sort of under the umbrella of marketing. Here’s an example from our work on Hubspot’s Service Hub:

And here’s a URL map we planned for a “forms” cluster (though in reality it ended up being slightly different):

Eventually, I like to build up clusters that contain a product page, one pillar page, and several cluster blog posts.

Sometimes, if the website is mature enough and there are enough “decision” level terms, I like to add in “sub-product” or “sub-service” pages. These are children of a parent service. So if you have a product, “popup forms,” that is your parent product, then you may have sub-features that still get search volume like “exit intent popup” or “scroll trigger popup.” Thematically, they belong in the same cluster.

A good tool to use to group together similar keywords is Latent Semantic Analysis. You can do this in R (which is my preferred method), or you can use a tool like LSIgraph:

Another use case for a tool like this is to find related keywords that you can use in a big pillar page. In other words, if you’re writing a big blog post on “content marketing strategy” (*ahem*), you may want to include sections or phrases like “content marketing strategy checklist” and “what is content strategy.”

Or you may want to build them into separate posts if they have enough search volume.

Another tool to find related keywords is answerthepublic.com. This is one of my all time favorite content planning tools when it comes to actually writing the post:

Both of these tools are great at helping you fill out an outline for your pillar pages and ultimate guides:

Eventually, you’ll have a solid content calendar, at least in spreadsheet form, full of tons of different content types. In some cases, you may just want to work out of your spreadsheet (totally viable, we do that with our internal properties at my content marketing agency). If you have a bigger team or work with clients, however, you’ll probably want to use some sort of editorial calendar (I like Trello). This helps you assign different content pieces to different content marketers:

Content Creation: Production That Gets Results

Finally! Time to actually produce content.

The important point here is that we want to bake in promotion elements into the content itself so the piece does well upon publication. Publish and pray is not a strategy. “Quality content” or “great content” is a meaningless term outside of blasé publications like Content Marketing Institute.

With that in mind, especially for my “awareness” level content, I love to build in “link hooks” that help different the piece and make it easier to promote and pick up steam naturally. Most content needs a little extra effort on the margins to really pick up results.

Link + Share hooks

There are a million ways to differentiate content, but here are 7 I like:

1. Original images
2. Data & Research
3. Original Charts
4. New frameworks with made up names
5. Quotes from experts
6. Pros & Cons tables
7. Controversial Hot Takes

Aaaaand examples of each…

Original images

Data and Research

Original Charts

Frameworks with made up names

Quotes from experts

Pros and Cons tables

Controversial Hot Takes

Promotion tactics

Before I ever publish a post, I make sure I have a very clear idea of where I’m going to promote it. Most of the time, I like to build out a sort of “PR launch list” that includes blogs, influencers, and communities that fit into these three categories:

• Tier 1 is high authority and high relevance. A lot of the time, these sites are super competitive with the terms i’m going for, so very hard to snag a link from.
• Tier 2 is really where I spend most of my time. Complementary (noncompetitive) sites that aren’t insanely high authority. This is where you can get the most bang for your buck with link building especially.
• Then Tier 3 is mid to high authority but not as relevant. Here we can consider general marketing or business blogs like business2community.

I think it’s a great exercise for anyone to map these people and places out, even if you think you know your space super well. I guarantee you’ll find some good link/partner/promotion opportunities you hadn’t even considered. Other tools to find these targets:

• Onalytica
• BuzzSumo
• Scraping software comparison sites for key categories
• Find link roundups in your niche
• Work with agency partners or integration partners
• Find Slack groups in your niche

Don’t forget communities and social spread:

• Twitter
• Facebook
• Designer News
• Hacker News
• Reddit
• Growth Hackers
• Slack Groups
• Quuu

Then make sure you store all this in a spreadsheet (or even better, a CRM).

Now, I like to bucket promotion into two categories: Short Term + Long Term.

First, you want a short term spike to drive attention and traffic to your post in the first place.

This helps get the early adopters on board and it spurs a bit of organic social traffic. These things are secondary signals that may actually help your organic rankings later on (secondary because presumably they aren’t direct ranking factors, though they can bring influential people to your site who may share and link to it later).

For that, at least for my industry and content, I usually throw the posts on a few communities I’m active in.

I email it out to my list.

And I share on social.

That’s basically it. I really just want a short traffic spike, and I know that I mostly hate the promotion aspect of this sport, so I do the minimum effective dose. Then I focus all my core efforts on the long term promotion, which is really just link building and content optimization (which we’ll talk about in a few sections). For now, link building.

Sometimes, I’ll do cold email outreach, especially if I’m really trying to promote a piece (for example, my recent guide on A/B testing is something I’ve put more than normal time into). If you want a big guide on that, check this out.

Honestly, though, most of the time I just ask people I know well to put a mention in a post they have or I do guest posting. Relationships trump cheap tactics, especially when it comes to outreach.

Back to the point I made earlier about not isolating yourself. Get to know people in your industry and broader space as well. It’s all about digging the well before you’re thirsty.

Measuring Results

As I mentioned in a previous section, you want to measure the three big things:

1. Website analytics
2. Search metrics and rank tracking
3. Conversion & business data

While there are a million other things you can track nowadays, those are the core of any content marketing analytics approach.

As for website analytics, Google Analytics is really the gold standard. There are other tools, tons of them actually, but Google Analytics is the one I’m most used to and most comfortable with.

Bonus if you set up goals for things like email signups, and even better if you set up interesting event tracking, like scroll depth and behavioral stuff like banner interactions. I wrote a massive guide on content analytics, so check that out if you want to nerd out.

Next, if your content marketing strategy is search focused (which it probably should be), you’ll want to measure your rankings. The analog to this if your strategy is social focused would be some sort of social media monitoring tool like HootSuite.

For SEO, I like to use a combination of Ahrefs and Search Console, and also Screaming Frog for the occasional crawl.

Finally, make sure you can attribute business results to your content marketing. Often this can be done quite simply in Google Analytics using goals.

Sometimes, however, you’ll want to build a more robust data pipeline and data warehouse to create custom attribution models to weigh out the efficacy of your content.

That’s for fellow nerds though, most can get by with the data dashboards your marketing tool gives you…

All of these analytics solutions give you access to one of the most powerful (and underrated) levers in content marketing…content optimization.

Content Optimization

I’ve written a massive guide on this one already, but the gist of it is that you can and should look back at old content to improve it. The cost of doing so is much lower than creating net new content (and remember our content economics model…the lower the cost to achieve the same return, the better).

Two ways to improve content:

1. Boost rankings on content that almost ranks on page 1
2. Boost conversions on underperforming (but high ranking) content.

I won’t go deeply into the tactical ways of doing those two things here, but if you’re interested in content optimization, check out my guide. Also check out this list of content optimization tools. I believe every serious content program should do this at least once a quarter, and if run a program that is truly mature, you may want to have a person or team that works on this.

Content Auditing and Maintenance

“Whosoever desires constant success must change his conduct with the times.” – Niccolo Machiavelli

As suggested in the “content optimization” section, you need to stop and do a content audit every once in a while – but at a level even higher than simply asking what content pieces could be doing better.

Every six months to a year, I think it’s important to take a step back, look at your KPIs and your associated results, and ask, “how are we doing?” Are our content marketing goals contributing to our business goals? Can we experiment with the type of content we’re producing (webinars? New forms of social media marketing?)

Not only that, but you should redo your SWOT every once in a while, because strengths and weakness change rapidly in this space (and so do opportunities and threats).

For instance, as you build domain authority, you add the strength of being able to rank more and more templatized/cheap content. However, as you build traffic via search, a threat may be your overreliance on Google as a channel. As such, a strategic may look into diversification.

Looking Forward & Balancing Your Portfolio

Normally, when starting out, you need to be narrowly focused on an acquisition channel, and even more so a tactic within that channel, and exploit the hell out of it while it still gives you returns. Then, over time, either the returns slow down (the law of shitty click throughs), or your reliance on the tactic or channel leads you to a fragile position.

In either case, a mature program diversifies and rebalances the portfolio every once in a while.

There are many portfolio models you could use in the game of content marketing strategy, but the one I like the most, as you scale, is a variation of the Barbell Strategy of investing. The definition from Wikipedia:

“One variation of the barbell strategy involves investing 90% of one’s assets in extremely safe instruments, such as treasury bills, with the remaining 10% being used to make diversified, speculative bets that have massive payoff potential. In other words, the strategy caps the maximum loss at 10%, while still providing exposure to huge upside”

In other words, continue to pour the vast majority of your resources and efforts into your safe, stable channel (probably a strong SEO-driven content program) and then pull a smaller percentage of your resources to work only on high volatility, experimental programs.

This way, you can cap your downside, continue to reap the rewards of your cash cow, but encourage innovation before other competitors move in on your slow moving machine.

Conclusion

Content marketing strategy is a tough thing to learn, but with time and pressure, you can master it.

Reading a guide like this will help (hopefully), but as with anything meaningful, you’ve got to plunge into the deep end and just figure things out for yourself.

There’s so much domain specificity here, that even though I’m aware of and disappointed in biased advice, there’s almost no way I’m not writing with some sort of bias (however hidden from myself).

However, this guide should give you a good starting framework to operate from, even if the specifics are slightly different in your case.

The post Content Marketing Strategy: Everything You Need to Know to Build a Growth Machine appeared first on Alex Birkett.

At the same time, I don’t think we should hold the standards so high that you need a data scientist to design and analyze every single experiment. We should democratize the practice to the most sensible extent, but we should create logical guardrails so the experiments that are run are run well.

The best way to do that I can think of is with education and a checklist. If it works for doctors, I think we can put it to use, too.

So this article is two things: a high level checklist you can use on a per test basis (you can get a Google Docs checklist here), and a comprehensive guide that explains each checklist item in detail. It’s a choose your own adventure. You can read it all (including outbound links), or just the highlights.

Also, don’t expect it to be completely extensive or cover every fringe case. I want this checklist to be usable by people at all levels of experimentation, and at any type of company (ecommerce, SaaS, lead generation, whatever). As such, I’ll break it into three parts:

• The Basics – don’t run experiments if you don’t follow these guidelines. If you follow these, ~80% of your experiments should be properly run.
• Intermediate Topics – slightly more esoteric concepts, but still largely useful for anyone running tests consistently. This should help reduce errors in ~90% of experiments you run.
• Advanced Topics – won’t matter for most people, but will help you decide on fringe cases and more advanced testing use cases. This should bring you up to ~95-98% error reduction rate in running your tests.

I’ll also break this up into simple heuristics and longer descriptions. Depending on your level of nerdiness or laziness, you can choose your own adventure:

• Basics
  • Basics with Explanations
• Intermediate
  • Intermediate with Explanations
• Advanced
  • Advanced with Explanations

The frustrating part about making a guide or a checklist like this is there is so much nuance. I’m hyper aware that this will never be complete, so I’m setting the goal to be useful. To be useful means it can’t run on for the length of a textbook, though it almost does at ~6000 words.

(In the case that you want to read a textbook, read this one).

I’m not reinventing the wheel here. I’m basically compiling this from my own experiences, my mentors, papers from Microsoft, Netflix, Amazon, Booking.com and Airbnb, and other assorted sources (all listed at the end).

What is A/B Testing?

A/B testing is a controlled experiment (typically online) where two or more different versions of a page or experience are delivered randomly to different segments of visitors. Imagine a homepage where you’ve got an image slider above the fold, and then you want to try a new version instead showing a product image and product description next to a web form. You could run a split test, measure user behavior, and get the answer as to which is optimal:

Statistical analysis is then performed to infer the performance of the new variants (the new experience or experiences, version B/C/D, etc.) in relation to the control (the original experience, or version A).

A/B tests are performed commonly in many industries including ecommerce, publications, and SaaS. In addition to running experiments on a web page, you can set up A/B tests on a variety of channels and mediums, including Facebook ads, Google ads, email newsletter workflows, email subject line copy, marketing campaigns, product features, sales scripts, etc. – the limit is really your imagination.

Experimentation typically falls under one of several roles or titles, which vary by industry and company. For example, A/B testing is strongly associated with CRO (conversion optimization or conversion rate optimization) as well as product management, though marketing managers, email marketers, user experience specialists, performance marketers, and data scientists or analysts may also run A/B tests.

The Basics: 10 Rules of A/B Testing

1. Decide, up front, what the goal of your test is and what metric matters to you (the Overall Evaluation Criterion).
2. Plan upfront what action you plan on taking in the event of a winning, losing, or inconclusive result.
3. Base your test on a reasonable hypothesis.
4. Determine specifically which audience you’ll be targeting with this test.
5. Estimate your minimum detectable effect, required sample size, statistical power, and how long your test will be required to run before you start running the test.
6. Run the test for full business cycles, accounting for naturally occurring data cycles.
7. Run the test for the full time period you had planned, and only then determine the statistical significance of the test (normally, as a rule of thumb, accepting a p value of <.05 as “statistically significant”).
8. Unless you’re correcting for multiple comparisons, stick to running one variant against the control (in general, keep it simple), and using a simple test of proportions, such as Chi Square or Z Test, to determine the statistical significance of your test.
9. Be skeptical about numbers that look too good to be true (see: Twyman’s Law)
10. Don’t shut off a variant mid test or shift traffic allocation mid test

The Basics of A/B Testing: Explained

1. Decide Your Overall Evaluation Criterion Up Front

Where you set your sights is generally where you end up. We all know the value of goal setting. Turns out, it’s even more important in experimentation.

Even if you think you’re a rational, objective person, we all want to win and to bring results. Whether intentional or not, sometimes we bring results by cherry picking the data.

Here’s an example (a real one, from the wild). Buffer wants to A/B test their Tweets. They launch two of ‘em out:

Can you tell which one the winner was?

Without reading their blog post, I genuinely could not tell you which one performed better. Why? I have no idea what metric they’re looking to move. On Tweet two, clicks went down but everything else went up. If clicks to the website is the goal, Tweet one is the winner. If retweets, tweet number two wins.

So, before you ever set a test live, choose your overall evaluation criterion (or North Star metric, whatever you want to call it), or I swear to you, you’ll start hedging and justifying that “hey, but click through rate/engagement/time on site/whatever increase on the variation. I think that’s a sign we should set it live.” It will happen. Be objective in your criterion.

(Side note, I’ve smack talked this A/B test case study many times, and there are many more problems with it than just the lack of a single metric that matters, including not controlling for several confounding variables – like time – or using proper statistics to analyze it.)

Make sure, then, that you’re properly logging your experiment data, including number of visitors and their bucketing, your conversion goals, and any behavior necessary to track in the conversion funnel.

2. Plan Your Proposed Action Per Test Result

What do you hope to do if your test wins? Usually this is a pretty easy answer (roll it out live, of course).

But what do you plan to do if your test loses? Or even murkier, what if it’s inconclusive?

I realize this sounds simple on paper. You might be thinking, “move onto the next test.” Or “try out a different variation of the same hypothesis.” Or “test on a larger segment of our audience to get the necessary data.”

That’s the point, there are many decisions you could make that affect your testing process as a whole. It’s not as simple as “roll it out live” or “don’t roll it out live.”

Say your test is trending positive but not quite significant at a p value of < .05. You actually do see a significant lift, though, in a micro-conversion, like click through rate. What do you do?

It’s not my place to tell you what to do. But you should state your planned actions up front so you don’t run into the myriad of cognitive biases that we humans have to deal with.

Related reading here.

3. Base your test on a reasonable hypothesis

What is a hypothesis, anyway?

It’s not a guess as to what will happen in your A/B test. It’s not a prediction. It’s one big component of ye old Scientific Method.

A good hypothesis is “a statement about what you believe to be true today.” It should be falsifiable, and it should have a reason behind it.

This is the best article I’ve read on experiment hypotheses: https://medium.com/@talraviv/thats-not-a-hypothesis-25666b01d5b4

I look at developing a hypothesis as a process of being clear in my thinking and approach to the science of A/B testing. It slows me down, and it makes me think “what are we doing here?” As the article above states, not every hypothesis needs to be based on mounds of data. It quotes Feynman: “It is not unscientific to take a guess, although many people who are not in science believe that it is.”

I do believe any mature testing program will require the proper use of hypotheses. Andrew Anderson has a different take, and a super valid one, about the misuse of hypotheses in the testing industry. I largely agree with his take, and I think it’s mostly based on the fact that most people are using the term “hypothesis” incorrectly.

4. Determine specifically which audience you’ll be targeting with this test

This is relatively quick and easy to understand. Which population would you like to test on – desktop, mobile, PPC audience #12, users vs. non-users, customer who read our FAQ page, a specific sequence of web pages etc. – and how can you take measures to exclude the data of those who don’t apply to that category?

It’s relatively easy to do this, at least for broad technological categorizations like device category, using common A/B testing platforms.

Point is this: you want to learn about a specific audience, and the less you pollute that sample, the cleaner your answers will be.

5. Estimate your MDE, sample size, statistical power, and how long your test will run before you run it

Most of the work in A/B testing comes before you ever set the test live. Once it’s live, it’s easy! Analyzing the test after the fact is especially easier if you’ve done the hard and prudent work up front.

What do you need to plan? The feasibility of your test in terms of traffic and time length, what minimum detectable effect you’d need to see to discern an uplift, and the sample size you’ll need to reach to consider analyzing your test.

It sounds like a lot, but you can do all of this with the help of an online calculator.

I actually like to use a spreadsheet that I found on the Optimizely knowledge base (here’s a link to the spreadsheet as well). It visually shows you how long you’d have to run a test to see a specific effect size, depending on the amount of traffic you have to the page and the baseline conversion rate.

You can also use Evan Miller’s Awesome A/B testing tools. Or, CXL has a bunch of them as well. Search Discovery also has a calculator with great visualizations.

6. Run the test for full business cycles, accounting for naturally occurring data cycles

One of the first and common mistakes everyone makes when they start A/B testing is calling a test when it “reaches significance.” This, in part, must be because in our daily lives, the term “significance” means “of importance” so it sounds final and deterministic.

Statistical significance (or the confidence level) is just an output of some simple math that tells you how unlikely a result is given the assumption that both variants are the same.

Huh?

We’ll talk about p-values later, but for now, let’s talk about business cycles and how days of the week can differ.

The days of the week tend to differ quite a bit. Our goal in A/B testing is to get a representative sample of our population, which general involves collecting enough data that we smooth out for any jagged edges, like a super Saturday where conversion rates tank and maybe the website behavior is different.

Website data tends to be non-stationary (as in, they change over time) or sinusoidal – or rather, it looks like this:

While we can’t reduce the noise to zero, we can run our tests for full weeks and business cycles to try to smooth things out as much as possible.

7. Run the test for the full time period you had planned

Back to those pesky p-values. As it turns out, an A/B test can dip below a .05 p-value (the commonly used rule to determine statistical significance) at many points during the test, and at the end of it all, sometimes it can turn out inconclusive. That’s just the nature of the game.

Anyone in the CRO space will tell you that the single most common mistake people make when running A/B tests is ending the test too early. It’s the ‘peaking’ problem. You see that the test has “hit significance,” so you stop the test, celebrate, and launch the next one. Problem? It may not have been a valid test.

The best post written about this topic, aptly titled, is Evan Miller’s “How Not To Run An A/B Test.” He walks through some excellent examples to illustrate the danger with this type of peaking.

Essentially, if you’re running a controlled experiment, you’re generally setting a fixed time horizon at which you view the data and make your decision. When you peak before that time horizon, you’re introducing more points at which you can make an erroneous decision and the risk of a false positive goes wayyy up.

8. Stick to testing only one variant (unless you’re correcting for it…)

Here we’ll introduce an advanced topic: the multiple comparisons problem.

When you test several variants, you run into a problem known as “cumulative alpha error.” Basically, with each variant, sans statistical corrections, you risk a higher and higher probability of seeing a false positive. KonversionsKraft made a sweet visualization to illustrate this:

This looks scary, but here’s the thing: almost every major A/B testing tool has some built in mechanism to correct for multiple comparisons. Even if your testing tool doesn’t, or if you use a home-brew testing solution, you can correct for it yourself very simply using one of many methods:

• F-test
• Bonferroni correction
• False Discovery Rate
• Šidák correction

However, if you’re not a nerd and you just want to test some shit and maybe see some wins, start small. Just one v one.

When you do feel more comfortable with experimentation, you can and should look into expanding into A/B/n tests with multiple variants.

This is a core component of Andrew Anderson’s Discipline Based Testing Methodology, and if I can, I’ll wager to say it’s because it increases the beta of the options, or the differences between each one of the experiences you test. This, at heart, decreases your reliance on hard opinions or preconceived ideas about “what works” and opens you up to trying things you may not of in a simple A/B test.

But start slowly, keep things simple.

9. Be skeptical about numbers that look too good to be true

If there’s one thing CRO has done to my personality, it’s heightened my level of skepticism. If anything looks too good to be true, I assume something went wrong. Actually, most of the time, I’m poking at prodding at things, seeing where they may have been broken or setup incorrectly. It’s an exhausting mentality, but one that is necessary when dealing with so many decisions.

Ever see those case studies that proclaim a call to action button color change on a web page led to a 100%+ increase in conversion rate? Almost certainly bullshit. If you see something like this, even if you just get a small itch where you think, “hmm, that seems…interesting,” go after it. Also second guess data, and triple guess yourself.

As the analytics legend Chris Mercer says, “trust but verify.”

And read about Twyman’s Law here.

10. Don’t shut off a variant mid test or shift traffic allocation mid test

I guess this is sort of related to two previous rules here: run your test for the full length and start by only testing one variant against the control.

If you’re testing multiple variants, don’t shut off a variant because it looks like it’s losing and don’t shift traffic allocation. Otherwise, you may risk Simpson’s Paradox.

Intermediate A/B Testing Issues: A Whole Lot More You Should Maybe Worry About

1. Control for external validity factors and confounding variables
2. Pay attention to confidence intervals as well as p-values
3. Determine whether your test is a Do No Harm or a Go For It test, and set it up appropriately.
4. Consider which type of test you should run for which problem you’re trying to solve or answer you’re trying to find (sequential, one tail vs two tail, bandit, MVT, etc)
5. QA and control for “flicker effect”
6. Realize that the underlying statistics are different for non-binomial metrics (revenue per visitor, average order value, etc.) – use something like the Mann-Whitney U-Test or robust statistics instead.
7. Trigger the test only for those users affected by the proposed change (lower base rates lead to greater noise and underpowered tests)
8. Perform an A/A test to gauge variance and the precision of your testing tool
9. Correct for multiple comparisons
10. Avoid multiple concurrent experiments and make use of experiment “swim lanes”
11. Don’t project precise uplifts onto your future expectations from those you see during an experiment.
12. If you plan on implementing the new variation in the case of an inconclusive test, make sure you’re running a two-tailed hypothesis test to account for the possibility that the variant is actually worse than the original.
13. When attempting to improve a “micro-conversion” such as click through rate, make sure it has a downstream effect and acts as a causal component to the business metric you care about. Otherwise, you’re just shuffling papers.
14. Use a hold-back set to calculate the estimated ROI and performance of your testing program

Intermediate A/B Testing Issues: Explained

1. Control for external validity factors and confounding variables

Well, you know how to calculate statistical significance, and you know exactly why you should run your test for full business cycles in order to capture a representative sample.

This, in most cases, will reduce the chance that your test will be messed up. However, there are plenty more validity factors to worry about, particularly those outside of your control.

Anything that reduces the representativeness or randomness of your experiment sample can be considered a validity factor. In that regard, some common ones are:

• Bot traffic/bugs
• Flicker effect
• PR spikes
• Holidays and external events
• Competitor promotions
• Buggy measurement setup
• Cross device tracking
• The weather

I realize this tip is frustrating, because the list of potential validity threats is expansive, and possibly endless.

However, understand: A/B testing always involves risks. All you need to do is understand that and try to document as many potential threats as possible.

You know how in an academic paper, they have a section on limitations and discussion? Basically, you should do that with your tests as well. It’s impossible to isolate every single external factor that could affect behavior, but you can and should identify clearly impactful things.

For instance, if you raised a round of capital and you’re on the front page of TechCrunch and Hacker News, maybe that traffic isn’t exactly representative? Might be a good time to pause your experiments (or exclude that traffic from your analysis).

2. Pay Attention to Confidence Intervals as Well as P-Values

While it’s common knowledge among experimenters that one should strive to call a test “significant” if the p-value is below .05. This, while technically arbitrary, ensures we have a certain level of risk in our decision making and it never rises above an uncomfortable point. We’re sort of saying, 5% of experiments may show results purely due to chance, but we’re okay with that, in the long run.

Many people, however, fail to understand or use confidence intervals in decision making.

What’s a confidence interval in relation to A/B testing?

Confidence intervals are the amount of error allowed in A/B testing – the measure of the reliability of an estimate. Here’s an example outlined by PRWD:

Basically, if your results, including confidence intervals, overlap at all, then you may be less confident that you have a true winner.

John Quarto-vonTivadar has a great visual explaining this:

Of course, the greater your sample size, the lower the margin of error becomes in an A/B test. As is usually the case with experimentation, high traffic is a luxury and really helps us make clearer decisions.

3. Determine whether your test is a Do No Harm or a Go For It test, and set it up appropriately.

As you run more and more experiments, you’ll find yourself less focused on an individual test and more on the system as a whole. When this shift happens, you begin to think more in terms or risk, resources, and upside, and less in terms of how much you want your new call to action button color to win.

A fantastic framework to consider comes from Matt Gershoff. Basically, you can bucket your test into two categories:

1. Do No Harm
2. Go For It

In a Do No Harm test, you care about the potential downside and you need to mitigate it or avoid it. In a Go For It test, we have no additional cost to making a Type 1 error (false positive), so there is no direct cost invoked when making a given decision.

In the article, Gershoff gives headline optimization as an example:

“Each news article is, by definition, novel, as are the associated headlines.

Assuming that one has already decided to run headline optimization (which is itself a ‘Do No Harm’ question), there is no added cost, or risk to selecting one or the other headlines when there is no real difference in the conversion metric between them. The objective of this type of problem is to maximize the chance of finding the best option, if there is one. If there isn’t one, then there is no cost or risk to just randomly select between them (since they perform equally as well and have the same cost to deploy). As it turns out, Go For It problems are also good candidates for Bandit methods.”

Highly suggested that you read his full article here.

4. Consider which type of test you should run for which problem you’re trying to solve or answer you’re trying to find (sequential, one tail vs two tail, bandit, MVT, etc)

The A/B test is sort of the gold standard when it comes to online optimization. It’s the clearest way to infer a difference between a given element or experience. Though there are other methods to learning about your users.

Two in particular that are worth talking about:

1. Multivariate testing
2. Bandit tests (or other algorithmic optimization)

Multivariate experiments are wonderful for testing multiple micro-components (e.g. a headline change, CTA change, and background color change) and determining their interaction effects. You find which elements work optimally with each other, instead of a grand and macro-level lift without context as to which micro-elements are impactful.

In my anecdotal experience, I’d say good testing programs usually run one or two multivariate tests for every 10 experiments run (the rest being A/B/n).

Bandit tests are a different story, as they are algorithmic. The hope is that the minimize “regret” or the amount of time you’re exposing your audience to a suboptimal experience. So it updates in real time to show the winning variant to more and more people over time.

In this way, it sort of “automates” the a/b testing process. But bandits aren’t always the best option. They sway with new data, so there are contextual problems associated with say, running a bandit test on an email campaign.

However, bandit tests tend to be very useful in a few key circumstances:

• Headlines and Short-Term Campaigns (e.g. during holidays or short term, perishable campaigns)
• Automation for Scale (e.g. when you have tons and tons of tests you’d like to run on thousands of templatized landing pages)
• Targeting (we’ll talk about predictive targeting in “advanced” stuff)
• Blending Optimization with Attribution (i.e. testing, while at the same time, determining which rules and touch points contribute to the overall experience and goals).

5. QA and control for “flicker effect”

Flicker effect is a very special type of A/B test validity threat. It’s basically when your testing tool causes a slight delay on the experiment variation, briefly flashing the original content before serving the variation.

There are tons of ways to reduce flicker effect that I won’t go into here (read this article instead). A broader point is simply that you should “measure twice, cut once,” and QA your test on all major devices and categories before serving it live. Better to be prudent and get it right than to fuck up your test data and waste all the effort.

6. Realize that the underlying statistics are different for non-binomial metrics (revenue per visitor, average order value, etc.) – use something like the Mann-Whitney U-Test instead of a Z test.

When you run an A/B test with the intent to increase revenue per visitor or average order value, you can’t just plug your numbers into the same statistical significance calculator as you would with conversion rate tests.

Essentially, you’re looking at a different underlying distribution of your data. Instead of a binomial distribution (did convert vs. didn’t convert), you’re looking at a variety of order sizes, and that introduces the concept of outliers and variance into your calculations. It’s often the case that you’ll have a distribution affected by a very small amount of bulk purchasers, who skew a distribution to the right:

In these cases, you’ll want to use statistical test that does not make the assumption of a normal distribution, such as Mann-Whitney U-Test.

7. Trigger the test only for those users affected by the proposed change (lower base rates lead to greater noise and underpowered tests)

Only those affected by the test should be bucketed and included for analysis. For example, if you’re running a test on a landing page, where a modal pops up after scrolling 50%, you’d only want to include those who scroll 50% in the test (those who don’t would never have been the audience intended for the new experience anyway).

The mathematical reasoning for this is that filtering out unaffected users can improve the sensitivity (statistical power) of the test, reducing noise and making it easier for you to find effects/uplifts.

Most of the time, this is a fairly simple solution involving triggering an event at the moment where you’re looking to start analysis (at 50% scroll depth in the above example).

Read more on triggering here.

8. Perform an A/A test to gauge variance and the precision of your testing tool

While there’s a constant debate as to whether A/A tests are important or not, it sort of depends on your scale and what you hope to learn.

The purpose of an A/A test – testing the original vs the original – is mainly to establish trust in your testing platform. Basically, you’d expect to see statistically significant results – despite the variants being the same – about 5% of the time with a p-value of < .05.

In reality, A/A tests often open up and introduce you to implementation errors like software bugs. If you truly operate at high scale and run many experiments, trust in your platform is pivotal. An A/A test can help provide some clarity here.

This is a big topic. Ronny Kohavi wrote a great paper on it, which you can find here.

9. Correct for multiple comparisons whenever applicable

We’ve talked a bit of about the multiple comparisons problem, and how, when you’re just starting out, it’s best to just run simple A/B test. But you’re eventually going to get curious, and you’ll eventually want to run a test with multiple variants, say an A/B/C/D/E test. This is good, and you can often get more consistent results from your program when you test a greater variety of options. However, you do want to correct for multiple comparisons when doing this.

It’s fairly simple mathematically. Just use Dunnett’s test or the Sidak correction.

You also need to keep this multiple comparisons problem in mind when you do post-test analysis on segments. Basically, if you look at enough segments, you’ll find a statistically significant result. The same principle applies (you’re increasing the risk of a false positive with every new comparison).

When I do post-test segmentation, I often use it more as a tool to find research questions than to find answers and insights to based decisions on. So if I find a “significant” lift in a given segment, say Internet Explorer visitors in Canada, I note that as an insight that may or may not be worth testing. I don’t just implement a personalization rule, as doing that each time would certainly lead to organizational complexity, and would probably result in many false positives.

10. Avoid multiple concurrent experiments and make use of experiment “swim lanes”

Another problem that comes with scale is running multiple concurrent experiments. Basically, if you run two tests, and they’re being run on the same sample, you may have interaction effects that ruin the validity of the experiment.

Best case scenario: you (or your testing tool) creates technical swim lanes where a group can only be exposed to one experiment at a time. It prevents, automatically, this sort of cross-pollination, and reduces sample pollution.

A scrappier solution, one more fit for those running fewer tests, is to run your proposed experiments through a central team who gives the green-light and can see, at a high level, where there may be interaction effects, and avoid them.

11. Don’t project precise uplifts onto your future expectations from those you see during an experiment.

So, you got a 10% lift at 95% statistical significance. That means you get to celebrate that win in your next meeting. You do want to state the business value of an experiment like this, of course – what’s a 10% relative lift mean in isolation – so you also include a projection of what this 10% lift means for the business. “We can expect this to bring us 1,314 extra subscriptions per month,” you say.

While I love the idea of tying things back to the business, you want to tread lightly in matters of pure certainly, particularly when you’re dealing with projections.

An A/B test, despite misconceptions, can only truly tell you the difference between variants during the time we’re running the experiment. We do hope that differences between variants expand past the duration of the test itself, which is why we go through so much trouble in our experiment design to make sure we’re randomizing our sample and testing on a representative sample.

But a 10% lift during the test does not mean you’ll see a 10% lift during the next few months.

If you do absolutely need to project some sort of expected business results, at least do so using confidence intervals or a margin of error.

“We can expect, given the limitations of our test, to see X more subscriptions on the low side, and on the high side, we may see as many as Y more subscriptions, but there’s a level of uncertainty involved in making these projections. Regardless, we’re confidence our result is positive and will result in an uptick in subscriptions.”

Nuance may be boring and disappointing, but expectation setting is cool.

12. If you plan on implementing the new variation in the case of an inconclusive test, make sure you’re running a two-tailed hypothesis test to account for the possibility that the variant is actually worse than the original.

One-tail vs. two-tail a/b testing. This can seem like a somewhat pedantic debate in many cases, but if you’re running an A/B test where you expect to roll out the variant even if the test is inconclusive, you will want to protect your downside with a two-sided hypothesis test.

Read more on the difference between one-tail and two-tail A/B tests here.

13. When attempting to improve a “micro-conversion” such as click through rate, make sure it has a downstream effect and acts as a causal component to the business metric you care about. Otherwise, you’re just shuffling papers.

Normally, you should choose a metric that matters to your business. The conversion rate, revenue per visitors, activation rate, etc.

Sometimes, however, that’s not possible or feasible, so you work on moving a “micro-conversion” like click through rate or improving the number of people who use a search function. Often, these micro-conversions are correlative metrics, meaning they tend to associate with your important business metric, but aren’t necessarily causal.

A good example is if you find a piece of data that says people who use your search bar purchase more often and at higher volumes than those who don’t. So, you run a test that tries to increase the amount of people using that search feature.

This is fine, but make sure, when you’re analyzing the data, that your important business metric moves. So you increased people who use the search feature – does that also increase purchase conversion rate and revenue? If not, you’re shuffling papers.

14. Use a hold-back set to calculate the estimated ROI and performance of your testing program

Want to know the ROI of your program? Some top programs make use of a “holdback set” – keeping a small subset of your audience on the original version of your experience. This is actually crucial when analyzing the merits of personalization/targeting rules and machine learning-based optimization systems, but it’s also valuable for optimization programs overall.

A universal holdback – keeping say 5% of traffic as a constant control group – is just one way to try to parse out your program’s ROI. You can also do:

• Victory Lap – Occasionally, run a split test combining all winning variants over the last 3 months against a control experience to confirm the additive uplift of those individual experiments.
• Re-tests – Re-test individual, winning tests after 6 months to confirm that “control” still underperforms (and the rate at which it does).

If you’re only running a test or two per month, these system-level decisions may be less important. But if you’re running thousands of tests, it’s important to start learning about program effectiveness as well as the potential “perishability” or decay of any given test result.

Here are a bunch of other ways to analyze the ROI of a program (just don’t use a simple time period comparison, please).

Advanced A/B Testing Issues – Mostly Fringe Cases That Some Should Still Consider

1. Look out for sample ratio mismatch.
2. Consider the case for a non-inferiority test when you only want to mitigate potential downsides on a proposed change
3. Use predictive targeting to exploit segments who respond favorably to an experience.
4. Use a futility boundary to mitigate regret during a test
5. When a controlled experiment isn’t possible, estimate significance using a bayesian causal model

Advanced A/B Testing Issues: Explained

1. Look out for sample ratio mismatch.

Sample Ratio Mismatch is a special type of validity threat. In an A/B test with two variants, you’d hope that your traffic would be randomly and evenly allocated among both variants. However, in certain cases, we see that the ratio of traffic allocation is off more than would be natural. This is known as “sample ratio mismatch.”

This, however, is another topic I’m going to politely duck out of explaining, and instead, link to the master, Ronny Kohavi, and his work.

He also has a handy calculator so you can see if your test is experiencing a bug like this.

2. Consider the case for a non-inferiority test when you only want to mitigate potential downsides on a proposed change

Want to run a test solely to mitigate risk and avoid implementing a suboptimal experience? You could try out a “non-inferiority” test (as opposed to the normal “superiority” test) in the case of easy decision tests and tests with side benefits outside of measurement capability (e.g. brand cohesiveness).

This is complicated topic, so I’ll link out to a post here.

3. Use predictive targeting to exploit segments who respond favorably to an experience.

A/B testing is cool, as is personalization. But after a while, your organization may be operating at such as scale that it isn’t feasible to manage, let alone choose, targeting rules for all those segments you’re hoping to reach. This is a great use case for machine learning.

Solutions like Conductrics have powerful predictive targeting engines that can find and target segments who respond better to given experience than the average user. So Conductrics (or another solution) may find that rural visitors using smartphones convert better with Variant C. You can weigh the ROI of setting up that targeting rule and do so, managing it programmatically.

4. Use a futility boundary to mitigate regret during a test

This is basically a testing methodology to improve efficiency and allow you to stop A/B tests earlier. I’m not going to pretend I fully grok this one or have used it, but here’s a guide if you’d like to give it a try. This is something I’m going to look into trying out in the near future.

5. When a controlled experiment isn’t possible, estimate significance using a bayesian causal model

Often, when you’re running experiments, particularly those that are not simple website changes like landing page CTAs, you may not be able to run a fully controlled experiments. I’m thinking of things like SEO changes, campaigns you’re running, etc.

In these cases, I usually try to estimate how impactful my efforts were using a tool like GA Effect.

Conclusion

As I mentioned up front, by its very nature, A/B testing is a statistical process, and statistics deals with the realm of the uncertainty. Therefore, while rules and guidelines can help reduce errors, there is no decision tree that can result in the perfect, error-less testing program.

The best weapon you have is your own mind, inquisitive, critical, and curious. If you come across a fringe issue, discuss it with colleagues or Google it. There are tons of resources and smart people out there.

I’m not done learning about experimentation. I’ve barely cracked the surface. So I may reluctantly come to find out in a few years that this list is naive, or ill-suited for actual business needs. Who knows.

But that’s part of the point: A/B testing is difficult, worthwhile, and there’s always more to learn about it.

Key Sources:

• https://hookedondata.org/Guidelines-for-AB-Testing/
• https://hbr.org/2017/09/the-surprising-power-of-online-experiments
• https://medium.com/airbnb-engineering/4-principles-for-making-experimentation-count-7a5f1a5268a
• https://exp-platform.com/advanced-topics-in-online-experiments/
• https://www.oreilly.com/learning/ab-testing-a-checklist
• https://cxl.com/blog/testing-statistics-mistakes/
• https://conductrics.com/PastStatisticalSignificance

Also, thanks to Erik Johnson, Ryan Farley, Joao Correia, Shanelle Mullin, and David Khim for reading this and adding suggestions before publication.

The post What is A/B Testing? An Advanced Guide + 29 Guidelines appeared first on Alex Birkett.

Lifehacker gets many millions of visitors every month, the supplement industry is like $50 billion a year, and we all listen to Tim Ferriss’ podcast, which in effect covers the morning routines and productivity hacks of those more successful than us.

We all want to squeeze more out of our days.

The pursuit of this is noble; the reality of the pursuit is often frustrating, ineffective, and filled with advice from charlatans (best satirized by this brilliant article).

I’ve tried my fair share of “productivity hacks,” and I still experiment with different tools, tricks, and routines to optimize my life. But in these trials, I’ve learned a few things, mostly unsexy lessons about the value of the fundamentals – eat, sleep, and exercise.

This article is sort of my compendium on what I’ve learned so far about optimizing my own productivity.

I’ll cover the basics, the things that will get you 90% of the way there and how to tackle them. Then I’ll also cover the remaining, more volatile 10% of productivity hacks that most articles cover as the only productivity hacks, like pomodoro timers, supplements, and sleep induction mats. If you don’t want to hear me lecture about the basics, click here to skip to the fun stuff.

If you’ve ever wondered about how to increase your productivity and squeeze more out of life, you’re in the right place.

The Fundamentals > Productivity Hacks

The boring stuff is usually the true stuff.

You shouldn’t eat too much sugar or overload on any food, you should exercise a bit, and you should sleep well. You should work a job you like, instead of a job you hate. You should surround yourself with good people and ideas so your work is directed towards the correct path.

These are the basic, the things that will control ~90% of your life’s “productivity” (silly word, bad to aim for solely productivity – will cover that in a bit). If you don’t have this stuff in order, you’re wasting your time with keyboard shortcuts and alarm clocks that roll around on the floor.

In my estimation, we can narrow the basics down into three categories:

• Define and live by a set of principles (orient yourself)
• Work towards something that matters (don’t work on something you hate)
• Eat, sleep, and exercise well.

A Principled Life: Why That Matters

Principles are where everything begins.

If you don’t define clear principles for yourself, you may be trying to hack your productivity on a mission that doesn’t matter to you, or worse, on something you actually hate. For example, squeezing more out of your day if you’re marketing cigarettes may not be ideal, for anyone.

Imagine being the person from Intuit that lobbies the government to keep taxes complicated so they can keep charging to simplify them. We should hope that person is horribly unproductive.

That’s a good rule to live by: don’t try to be more productive if what you’re doing is bad.

Even something less strident, such as my principle to “Optimize for Interesting,” means that I couldn’t work at something that I didn’t feel was interesting. This is subjective (and it should be). I don’t think I’d be a happy lawyer or auto-mechanic, so being a more productive one wouldn’t help me. Optimizing my life to include a variety of activities, travel, and experiences is going to beat out money given equal consideration.

In my estimation, defining your principles helps you place yourself in a context that you like, with friends you like, and with information sources that you don’t regret consuming.

With these, we can check off a few pieces of common and wise “productivity” advice (which isn’t productivity advice – it’s advice on living a principled life):

• Surround yourself with great people (you’re the average of the 5 people…)
• Read a lot of good books (or drink from your preferred information source)
• Be in a city or location that allows for serendipity in the path that you’re seeking

When you know what your values are and what you dislike, you can choose your friends accordingly.

One of my favorite recent things I’ve read is Jordan Peterson’s 12 Rules for Life, one of which is “make friends with people who want the best for you.”

This is only possible when you know what “best for you” means. You’ll tweak and iterate up on this, but it helps first to define who you even want in your life.

Reading is something I credit a lot of my success and happiness to. Part of it is going down rabbit holes and serendipitously finding new things or recommendations, but most of it is starting at a place of genuine interest. More importantly, setting your principles can let you decide what information sources you don’t want in your life (CNN, gossip sites, or anything by a book or movie critic).

Finally, when you know what you want you know where you want to be. It’s difficult to become a great lawyer (truly great) in a small town. It’s tough to get funding for a SaaS company in Nebraska. Not impossible, the world is becoming smaller and more accessible with technology, but your city, where you spend almost all of your time, is something to consider.

Your principles will change and adapt with time (they should), but you should start defining them today. A variety of techniques can help you do that, some of which you may currently be doing already. Therapy might help. Talking with your friends, openly, definitely. Meditation helps you notice things.

One of the things that helped me the most with this was completing a Self Authoring program.

Reading Principles by Ray Dalio is also suggested.

Work Towards Something That Matters (but Especially, Not Something You Hate)

I touched on this before, but if you hate what you do, you shouldn’t try to get more productive at it (well, unless the only thing you hate about it is that you’re unproductive).

Sam Altman wrote a post on productivity recently (he beat me to the punch by like 2 weeks). In it, he writes on this point as well:

“It doesn’t matter how fast you move if it’s in a worthless direction. Picking the right thing to work on is the most important element of productivity and usually almost ignored. So think about it more! Independent thought is hard but it’s something you can get better at with practice…

…I make sure to leave enough time in my schedule to think about what to work on. The best ways for me to do this are reading books, hanging out with interesting people, and spending time in nature.

I’ve learned that I can’t be very productive working on things I don’t care about or don’t like. So I just try not to put myself in a position where I have to do them (by delegating, avoiding, or something else). Stuff that you don’t like is a painful drag on morale and momentum.

By the way, here is an important lesson about delegation: remember that everyone else is also most productive when they’re doing what they like, and do what you’d want other people to do for you—try to figure out who likes (and is good at) doing what, and delegate that way.

If you find yourself not liking what you’re doing for a long period of time, seriously consider a major job change. Short-term burnout happens, but if it isn’t resolved with some time off, maybe it’s time to do something you’re more interested in.”

What’s meaningful to you?

• Working on big budget, high risk projects?
• Debugging and solving complex problems?
• Communicating and turning complex issues into understandable narratives?

Figuring out what matters to you will make it a hell of a lot easier to put out better work.

When you do have a modicum of freedom and you don’t have to go work to put food on the table, it helps to think about things that really matter to you. I’m sure working on Headspace isn’t too grating for a Tibetan Monk, but it might be unnerving for them to work on corporate law.

Eat, Sleep, and Exercise Well: The Boring Yet Important Stuff

This may not be right for you, but after much trial and error it’s what’s right for me…

Food:

• Don’t eat sugar
• Don’t eat too much food
• Don’t eat too little food
• Eat natural, whole foods (meat, veggies, etc.)
• Listen to your body and discover what it needs

Exercise:

• Walk more
• Get in the sun more
• Do a variety of different exercises
• Try to lift some weights once in a while or do HiiT
• Listen to your body and discover what it needs

Sleep:

• Don’t drink caffeine after 2 (even better, after noon)
• Wake up at the same time every day
• Don’t look at screens before bed
• Make your room as dark as possible
• Create a relaxing nighttime routine

The Last 10%: How to Hack Your Productivity

Here’s the fun stuff.

I’ve experimented a lot with supplements and productivity hacks. Not all of them work equally well.

The thing to note here is that if you don’t have the basics down, none of this matters. But if you have the basics down, these things can help a lot.

The math you need to worry about is compounding effects. If you increase your memory, focus, and creative output by 1% per day, that adds up over time. If you’re trying to do a variety of tasks, like balancing a demanding job with learning Spanish and machine learning, that 1% can mean the world.

The Importance of Trial and Error

Even with the basics, you need to try this stuff out for yourself. It turns out, humans are pretty variable even with core things like eating, sleeping, and exercise. Some of us can get by on 4 hours, some need 8. Some can eat bread, some can’t.

This also goes for the supplemental productivity stuff.

The snapshot of time I currently exist in came to be because of many years of experimenting and iterating. In fact, I’m still cycling through different hacks and habits, some of which will stick, most of which won’t.

The process I use: 30 day challenges. It’s enough time to see the effects of most things, but not too long that it’s a daunting commitment. I started most of my current habits with simple 30 day challenges.

Anyway, without further ado, here are the things I do to boost my productivity…

Supplements

I’ve got a pretty bangin’ supplement cabinet.

I drink a lot of coffee (3-4 cups a day), and have recently switched to Four Sigmatic’s mushroom coffee (it has Lion’s Mane and Chaga). There’s a good amount of research supporting both Lion’s Mane and Chaga, and it tastes almost the same as my other coffee, so why not?

With my coffee, I also take L-Theanine. This blunts the jittery effects of coffee and makes me calmer throughout the day. I do this maybe 4-5 days a week, not every day.

Not sure if this counts as a supplement, but I also sometimes have Bulletproof coffee. I put a tablespoon of grass fed butter plus some MCT oil in my coffee. I used to do this every day, now I just do it maybe twice a week.

I also fast 4 days per week. I stop eating at 8pm and start again at noon the next day (a 16 hour fast). I actually really enjoy my productivity on fasting days.

Another supplement I’ve taken a lot in the past is bacopa monniera, which has positive effects on memory, attention, and anxiety. I’ve recently started buying a stack from Legion Athletics called Ascend, that contains bacopa but also other nootropics (such as Alpha GPC, CDP-Choline, etc.).

Other than that, I take some staples: fish oil, vitamin D, and a multivitamin.

For weight lifting, I take creatine, whey protein (after lifting), and I’ve recently started taking BCAAs during longer workouts.

Sometimes, for sleep I’ll take some reishi mushroom or ashwaganda, though not very regularly. I also use a Spoonk mat to help me get to sleep faster. I include this in the supplements section instead of the basics because, while helpful, it’s definitely a “last 10%” kind of helpful. I’ve also begun looking into social alternatives to alcohol (as that can be a sleep crutch – though don’t get me wrong, I still love wine). This means I’ll sometimes hit up a kava bar during the week, which I’ve found to be super helpful to sleep.

I’ve taken modafinil and adderall in the past for productivity and alertness, though I prefer not to because the downside probably outweigh the upsides. Honestly, I don’t feel the need to have that same productivity rush anymore like those stimulants give you, I’d much rather just enjoy life.

Meditation and Spirituality

I meditate every day, first thing in the morning. Currently, I’m doing a 30 day challenge where I meditate 30 minutes a day, but I usually just meditate for 15 minutes. Since I’ve started doing 30 I’ve noticed a difference in my attention and anxiety levels through the day (a positive difference). I think I’ll keep doing the whole meditation thing.

I don’t really do anything else, here, like pray or whatever. I do yoga a lot, which is sort of like moving meditation. None of this is done with the explicit goal of productivity, though, and I think those who meditate to become more productive are missing the point and are sort of weirdos.

Thinking Differently

Most of what makes my work special is that I break things down to the core problem and see solutions in unique ways (or at least I try to).

To do that, I live a varied life with lots of time spent outdoors and with different types of people. That whole “you’re the average of the 5 people you spend the most time with” is cool and all, but sometimes it sounds boring to me. I like to spend time with people who challenge my opinions, not simply with those I look up to.

The same goes for the content I consume. It’s lots of varies material, from finance to history to politics and more. I like Joe Rogan, Sam Harris, Tim Ferriss, James Altucher, but I also like Planet Money, Radio Lab, Not So Standard Deviations, and Analytics Power Hour.

I almost never read marketing or explicit business books. I barely read marketing or business blogs unless I’m seeking a specific solution or really respect the author (e.g. Simo Ahava or CXL).

You may or may not consider this a “productivity hack,” but I find it vastly reduces the amount of time and stress I have to spend to solve problems.

Learning Hacks

Learning for me is mostly a function of four things:

• Extended period of quiet and intense focus
• Active reiteration of ideas (the Feynman Technique)
• Spaced repetition
• Short periods of free thinking/non-focus (e.g. day dreaming and walks)

A good course to go through is Coursera’s bit on how to learn. The techniques there are all things I’ve habitualized.

Morning Routine

Waking up at the same time every day is the most important. Regardless of when you go to bed, set your alarm for the same time (also, I use an alarm that mimics the sunrise, and I sleep in a pitch black room using blackout curtains).

When I wake up, I make a coffee, do a Spanish lesson on Skype (twice per week, if no Spanish lesson, I read from a Spanish book), meditate for 10-20 minutes (I use Oak now, but I really prefer Sam Harris’s guided meditations), do three lessons of Duolingo, fill out the morning section of my 5 minute journal, then start working at exactly 9am. I do heads down focus work for three hours, and then do lunch followed by other stuff.

This routine is rigorous and, writing it down, it makes me sound a bit weird. But I work remote, and I’ve found it’s incredibly important to have a familiar routine to kick you into gear (especially when you travel 6 months a year and still need to get work done like I do).

Working Faster

I overcommit, put a lot (but not too much) on my plate, and drink a shit load of coffee. I don’t use a pomodoro or anything like that. It’s pure ambition and adrenaline over here.

I do use a few free software products to improve my efficiency.

First, I use HubSpot’s free sales tools to set up meetings, track emails, automate sequences, etc. Second, I use Dayboard Chrome Extension to set my tasks for the day and warn me not to use Reddit. I also have a whiteboard in my room that I manually write my checklist on. It helps me to write my tasks out in the physical world, not only on a computer.

In fact, almost all the work I do outside of Excel is first doodled on in a physical notepad.

Big one: I use a separate work computer that I never use social media or Reddit on.

I don’t have the Facebook app on my phone, I always have my phone on disturb mode, and I’ve muted all notifications except for Snapchats, texts, and Tinder.

On every piece of software I use, I learn the shortcuts. I try not to use the mouse when I’m in Excel. I’ve begun learning R & Python to speed up certain data analysis work.

Habits: The Only Thing That Actually Matters

The reason I like 30 day challenges for this kind of stuff is that it’s a non-daunting way to try something out while setting the building blocks of a habit.

Habits are all the matter.

If you’re only productive every time you pop an adderall, you’re not a productive person. If you meditate once every two weeks, it’s not very useful.

To really get cranking, it helps to get to a point of automaticity. As I mentioned, my morning routing is rigorous at this point. I don’t even think about it. That’s where the real magic of productivity kicks in.

But it starts with an experiment. It starts with a single day. Just keep in mind that sporadic productivity hacks are almost certainly going to distract more than they help.

Via Negative

This list has, so far, has had an overwhelmingly additive focus. Usually I’ve found it’s more effective to reduce your bad habits than it is to add good habits. If you remove sugar, for instance, that’s probably better than adding carrots and spinach (though both are good things to do).

My apologies for burying this at the bottom of the post, but if you have bad habits, it’s probably best to work on removing those first. Via negativa.

Conclusion

Just as there is no such thing as a “growth hack,” there is really no such thing as a “productivity hack.” Embedded in both terms is an assumption that the hack is a silver bullet. Such things don’t exist.

Rather, it’s a process of getting the fundamentals right, tweaking and experimenting, and scaling it out in the form of a habit (what you do repeatedly you become).

Looking at things this way takes the power away from charlatans selling cure-alls and from unhelpful hope at a single thing solving your problems (the pomodoro technique will never save you from a job you hate).

Get the basics right, try shit out (different things work for different people), and find a way to create good habits and remove bad ones.

The post Productivity Hacks appeared first on Alex Birkett.

Content marketing is a creative endeavor – just as other types or marketing are – but data and analytics can inform content marketing just like they can paid, social, or affiliate.

Most current guides on analytics aren’t focused at content marketers. Rather, the examples and explanations are geared towards optimizers, paid acquisition marketers, and analysts.

So, since I’ve done a ton of content marketing as well as a ton of analytics work at both CXL and at HubSpot (as well as in my own nerdy free time), I thought it would be helpful to splice the two.

This article will cover some super tactical things content marketers can do to bring data into their daily work – and ultimately understanding how their content promotion and creation efforts are paying off.

Note: you should have a solid grasp of Google Analytics and Google Tag Manager. Just the basics will do (how data is collected, what basic reports means, etc.). If you don’t have any understanding of those, these two courses are great:

• Google Tag Manager 101
• Google Analytics Master Course

Asking Good Questions: The Core of Content Marketing Analytics

In my opinion, every content marketer should be able to answer the following business questions using analytics:

• How effective are our current content marketing efforts according to analytics?
• What are the content marketing opportunities we’re missing as shown by analytics?
• How can we optimize our content marketing efforts in the near term?
• At what points in the funnel are we dropping users? Can we do anything to plug these holes (or work with a team who can)?
• Do we see trends or insights that tell us which types of content are most effective at attracting high value leads/customers?
• What can analytics show me about new content marketing ideas and campaigns?

Generally, data should be able to guide your decisions as a content marketer just as it should if you’re a paid marketer or SEO.

There’s no reason for content to be distanced from business metrics, and using data does not negate your ability to use creativity.

This guide will cover what I think are the absolutely critical analytical functions a content marketer should be able to execute.

They span the qualitative and the quantitative, and I’ll even dip into specific reports in Google Analytics and specific survey questions to help you implement some of this. Here’s what we’ll cover:

• Quantitative Analytics
  • Does this blog post drive conversions?
  • Which blog posts have high traffic but low conversions (or engagement)?
  • How to find content gaps with user search data
  • How to find SEO opportunities
  • How far are people reading into our blog posts?
  • What is the best time of the day or day of the week to publish?
  • How to find out if something you changed on site mattered to SEO or it was just noise
• Qualitative Analytics
  • How to set up qualitative feedback loops
  • How to get real time visitor insights
  • How to find usability issues
• Proving Business Value
  • What’s ROI anyway?
  • A range of approaches

These aren’t the only questions you’ll want to answer, but the span of these use cases for data should at least get you started and provide inspiration for further learning.

Each section may brush over the particular process fairly quickly, but I’ll link to resources to understand it more fully. Let’s get into it!

Content Marketing Analytics: The Quantitative Stuff

This section is mostly going to cover Google Analytics, but whatever digital analytics tool you use will suffice – Adobe Analytics, Woopra, Piwik, etc.

I have the most experience with Google Analytics, and it’s free and super common, so I’ll write with examples from GA.

Does this blog post actually drive conversions?

If you don’t have goals set up in Google Analytics, do that now.

If you haven’t set up goals, you can’t track whether your efforts are actually resulting in what matters for the business.

When you’ve done that, you can view which blog posts are actually leading to goal conversions. You can do so using advanced segments.

So, what you’ll do is click “+ Add Segment” and then click the red “+ New Segment” button. Find “Sequences” under the advanced menu. Then set up a sequence with the first step as “Page” contains “[your blog post URL,” and use “is followed by” and create a second step that includes sessions with goal conversions.

You could use “transactions” or a specific goal for this, but I just used “Goal completions > 0” here…

A common mistake here is that people will use “Conditions,” but since what you care about is the sequence of events, you need to use “Sequences.”

If you’re doing this at scale (for dozens or hundreds of posts), it might be better to do it in a tool like R or even in a Data Studio report so you don’t need to constantly query GA for the reports you need.

You can also find conversions and conversion rate by landing page with customer reports. This blog post does a really good job explain how.

Which blog posts have high traffic but low conversions (or engagement)?

A good way to find CRO opportunities is to locate pages with high traffic and low conversions or engagement.

There are a few ways to do this, but my favorite is to use the comparison feature on Google Analytics.

Just go to Behavior > Site Content > Landing Pages and use the comparison feature on the right hand side of the screen. Then select Goal Conversion Rate (or Bounce Rate) from the drop down menu:

This shows you all pages, but it’s likely that you’ll want to get more granular and focus solely on your blog.

It’s possible you have a View specifically for this, but if not, you’ll need to search your category indicator (in my example below “drinkware” but in yours perhaps “blog”), and you’ll see only those pages and can nail down which ones need work:

The pages with high traffic and lower than average conversion rates or bounce rates are the biggest potential impact areas.

It’s these pages that you can optimize, or send to your web strategy or conversion optimization team for prioritization.

There’s a lot of room for improvement on these pages, and because they’re higher traffic, the impact is larger than the marginal increases in value you’d see with lower traffic pages.

How to find content gaps with user search data

You should know how to do keyword research.

That’s a given.

But after you’ve burned through the basics and the high volume keywords, it can get difficult to find ideas for what to write about. So, why not let your users tell you? Not directly, of course, but through their site search behavior.

If your GA is set up correctly, all of your site search data will be available in Behavior > Site Search > Search Terms.

This will give you a big list of everything users are searching for on your site, along with corresponding metrics like search exits, which is when someone searches and then leaves your site.

If your site has a small list of search terms, you can just look through all of these and find interesting terms – things you may not have even known people were looking for.

A better way, however, would be to do a time comparison and find trends.

This will give you the most popular terms, but even better than that is a little known feature where you can sort by “absolute change.”

This will let you see the biggest changes over time in your search data:

Anything interesting there? You can create pages for it.

For instance, when I was at CXL we found on our CXL Institute site an increase in search terms for “guarantee,” “about us,” and a variety of content topics that helped us to create internal pages for them.

Seriously good information to have as a marketer!

You should, of course, complement this with off-site and general keyword research using tools like Ahrefs and Keywords Everywhere.

This is just what people are searching for in your site-search bar, so it’s a narrow reflection of people’s intentions. It excludes all the people who don’t know who you are, haven’t landed on your site, or just don’t use site search to find their answers.

But this method does tell you what people are looking for, however small the sample. Can you find a way to answer their queries in the form of content?

How to Find SEO Opportunities

Content marketers need to be able to audit their current SEO efforts and results, and they also need to be able to plan out content campaigns based on search volume and intent.

So, we can basically split this step up between two areas:

• How to plan SEO-driven content marketing.
• How to audit your current approach and optimize and improve it.

To the first point, it’s largely a strategic process that starts with you having a discussion about your top business goals and conversion paths, and how you can work backwards to find appropriate keywords with enough volume and intent to help those goals.

For example, if you wanted to acquire users for a term like “free knowledge base software,” then you know you’d need to create a product page that captures some level of volume and intent there.

That’s your starting point, and then you can work backwards and think, “what kind of related things would people be searching for?”

That’s where your traditional keyword research process takes form, and this post isn’t going to be long enough to cover the complete process. There are great guides out there you can follow:

• How To Do Keyword Research – The Beginners Guide to SEO – Moz
• How to Do Keyword Research for SEO: A Beginner’s Guide – HubSpot
• Keyword Research for SEO: The Definitive Guide – Backlinko

In our knowledge base software example, perhaps the results of this keyword research would tell us that “knowledge base” gets a ton of search. This is a high level, broad term, and can be tackled with a 10X Pillar Page.

But we also need “cluster” blog posts to complement this.

(In other words, we want to rank for the broad theme of “knowledge base,” and to do so we’ll need to write many, many related blog posts targeting long tail keywords).

Long tail keywords here could be things like “how to create a knowledge base,” “knowledge base examples,” and “self-service customer support benefits.”

To find search volume (estimated), you can use tools like Ahrefs, SEMRush, etc. Then use this information to plan and prioritize your content calendar.

With regards to content planning, I think the best marketers operate with a foot in the past as well as one in the future.

By that I mean that some of your strategy should come from historical data like search volume, but some of it should be based on looking forward and setting the trends yourself. You know what an only-SEO blog strategy looks like (in a word, “mediocre”).

Auditing Your Current SEO Results

The second part of your SEO skill set should include measuring your efforts, auditing it from time to time (from a content perspective at least), and improving or optimizing things based on your findings.

Of course, you can and should set up keyword rank tracking on something like Accuranker, but you can go even further and analyze broader trends in search data.

The big thing here is to be able to track drops in traffic as they are occurring.

The majority of my roles in the past have been with companies who heavily relied on organic traffic for acquisition. Therefore, it was always anxiety-inducing to see a drop in traffic and not be able to pinpoint its reason.

While you may have a digital analytics or SEO specialist working specifically on this stuff, it still helps to have the skill set as a content marketer.

Here’s a quick process for doing that (abridged for my and your sanity):

Run a Google Analytics report at the end of the every month to see which of your site’s top URLs have lost traffic.

To do this, go to GA, pick your highest traffic month from the past 6 months (if your traffic is relatively stable and you don’t have much seasonality), or pick a period of 6-12 months that you think represents your data (say Jan 2016 to Jan 2017).

Then go to the Behavior > Site Content > All Pages report. Set your date range (whatever you chose as your representative data set).

If you’re analyzing a property that doesn’t have a given segment, click “advanced” and apply this filter: “Include” “Page” “Containing” “[Property URL]”. Or just filter out pages based on URL structure (like /blog/) if that’s the way your site is set up. Point is: include only blog posts.

If you want all traffic, you can continue on. If you want only organic traffic, set up a filter for that.

To do that, apply a secondary filter of Default Channel Grouping and include only those Channel Groupings that contain “Organic Search,” like the following:

Make sure you include all rows, and then export it to CSV.

Open your spreadsheet and name the first tab whatever month and year it is (Nov 2017) then rename Column B something like “Pageviews Nov 2017” (or Pageviews 2017, depending on what date range you chose) and delete all the other tabs:

Go back to GA and change the date range to the most recent fully completed month (or similar time period to the one you’re comparing it to – if you chose a 12 month period, pick your most recent fully completed 12 month period).

Always compare apples to apples with time period comparisons.

Do the same thing with the filters and the rows and whatnot, and export to CSV. Bring it on over to your other spreadsheet in Tab 2, and name that tab something like Jan 2017. Delete all rows except for Column A and B again.

Now add another column to tab #1 and name it something like Pageviews Jan 2018. Now do a Vlookup, like the following (in column C) where ‘tab 2’ is the title of your tab:

=VLOOKUP(A2, ‘[tab 2]!A:B, 2, FALSE)

Should look like this:

Now we’re going to see if there has been a significant drop. You can do whatever percentage you think is significant, but this example we’ll flag anything that has dropped by 20%.

Add column D and title it “2%+ decline?” then insert this formula in D7:

=IF(C2<(B2-(B2*0.2)),TRUE,FALSE)

That’s essentially asking if the number in Column C is 20% or greater less than the number in Column B. Then you can do conditional formatting to highlight those where that is the case:

Note: My example data here probably doesn’t give the best example because my comparison month was a holiday period (lots of traffic!) and I compared to January (low traffic!) so of course there is a large drop (it’s ecommerce). But you can tweak the time periods and parameters, I’m just trying to show you how you can easily get some good trend data to explore.

From there you can explore why you’re losing traffic (is search volume declining in general for your terms? Are competitors stealing your rankings?)

One more way to do this is simply to create a custom report that only includes blog pages and organic traffic, and simply track trends. Are you down month-to-month, year-to-year? This report will show you the broad answer and then you can drill down and find out why.

Finally, the easiest but roughest way to notice trends in your organic data is to set up a simple custom alert.

You can do it either way, tracking spikes or falls in your data.

You’ll want to get a baseline level of your data, ideally at a yearly level since so much can effect your week-to-week and even month-to-month traffic (seasonality is real). So what would be alarming to you regarding yearly trends in organic search volume?

Set that up as a custom alert so you know right away. It’s super easy to do this in Google Analytics:

Then you can go dive deeper and find specifically why your traffic is in decline (which specific pages, etc.).

How far are people reading into our blog posts?

Google is making it easier and easier to implement robust user engagement tracking via Google Tag Manager. One cool way you can do that is with Scroll Depth Tracking.

Many marketers user bounce rate as a metric to gauge user engagement, but that’s actually not a great metric to track (for many reasons).

I won’t go too in-depth on setting this up (otherwise we’d have to start at square one and talk about setting up Google Tag Manager), so I encourage you to read this guide if you’re interested in implementing something similar.

Once you’ve set up scroll depth tracking, you can use that event to see how far people read your blog posts. You could also combine with with time on page, bounce rate, etc., metrics that are usually used to define engagement, and you can see what the relationships are between the variables.

What is the best time of the day or day of the week to publish?

The time of day and day of the week you publish and promote content matter. And it doesn’t have to be a guessing game. Google Analytics can help answer this (and give you a sweet heatmap to show your team).

The best way to do this is with custom reports in GA.

Note: Google Analytics’ dashboard gives you a heatmap now, but it still helps to do this on your own so you can customize the variables.

Go into customer reports, and choose the “flat table” option. Add dimensions “Day of Week Name” and “Hour,” and then add relevant metrics. For content, you might care about sessions. For an ecommerce site, you could care about conversion rate by hour of day and time of week.

You can also add things like Source / Medium if you want to analyze, say, only organic sessions.

Then export your data to Excel. Make sure that you show all rows in the “shows rows” in the bottom right-hand corner of your screen.

Once you’re in Excel, you can whip up a quick pivot table based on the metrics you’d like to analyze by time of day and day of week.

To do a heat map, it’s as simple as using conditional formatting based on cell value:

You can also visualize this data in other ways, but I think this is the easiest way. I actually learned how to do this type of heat map in R first, and then later went back and figured it out in GA/Excel. The GA/Excel way is easier.

How to find out if something you changed on site mattered to SEO or it was just noise

The gold standard of online optimization is the controlled experiment: the A/B test.

However, with content and SEO, we’re often fighting to prove causality because it’s hard to control all variables (especially with Google’s constantly changing algorithms).

However, you can estimate the significance of the impact without a team of data scientists using Mark Edmondson’s GA Effect dashboard.

You just plug in your variables and the time horizon that you want to analyze (as well as when the change took place) and it calculates the probability of the change happening by chance.

You can read up more on the stats behind the tool here.

Qualitative Analytics for Content Marketing

There’s a whole qualitative side to this game, too.

Qualitative data can help you come up with topic ideas, gauge visitor and customer sentiment, and chase down usability errors.

In addition, it can help you feed critical business insights to other parts of the organization, too.

How to set up qualitative feedback loops

You can and should use any qualitative surveying or feedback tool you can to collect this data.

However, I find communities are even better places to source insights for new content, as well as feedback on your current content (as long as the community doesn’t suck).

At CXL, one of the highest leverage moves we made was to create a Facebook group to facilitate conversations on CRO, analytics, and other data-driven topics.

Granted, it may have been easier for us to do because we already had a large email list and many previous course students. But you don’t actually need to create a community to get insights; you can become a member of a relevant community and get the same value.

We’d start a lot of conversations ourselves, but we also invited tons of people we knew would be high quality contributors. The conversations were (and still are) super high quality. It’s pretty self-sufficient at this point, and I check back all the time for new updates.

When I was at CXL, I would use our group 1) to eavesdrop on conversations and 2) to help form and iterate on content.

Here’s an example of me straight up asking for feedback on a new style of content we were testing:

And here’s an example of me fishing for insights for the second point:

Those posts both got published:

• The Most Effective Ways to Analyze Session Replay Videos
• What Does the Future Hold for Conversion Optimization?

How to get real time visitor insights

Here we want to gauge the intent of individual and anonymous visitors on specific pages. To do this, we’ll strap an on-site polling tool (like Qualaroo) on our site and come up with some questions.

When setting up an on-site poll, you should think strategically and carefully about the question you’re hoping to answer.

Do you need to know what type of an audience is visiting your page? This one came from a VWO blog post:

Do you want to source content suggestions and feedback?

Want to use your survey as a tool to get leads and hand raisers?

You can ask any number of questions here, just make sure to approach it with clear intentions in mind. After all, a poll is a UX hurdle for your users, so it better have a pragmatic tradeoff in terms of the value of the insights you’re getting.

Of course, you can also gauge the intent and goals of visitors to landing pages, too. This helps you align your conversion paths as well as helps with landing page optimization.

How to find usability issues

While I don’t think it’s necessary to become a usability expert (unless you’re really early stage and wearing tons of hats), it’s really helpful to occasionally gauge the user experience of your website and audit your blog for usability issues.

You can send these to a front end developer for prioritization, or maybe you can solve them yourself, depending on the complexity.

There are two general ways I like to find usability issues as a content marketer (there are a few others if CRO or UX is your job role):

• General feedback forms
• User testing

General feedback forms, like that of Usabilla or HotJar, help you crowdsource frustrations from your users at scale. If you have 10,000 visitors, maybe 20 will leave feedback for you and maybe 5 of those responses will be useful.

But again, it’s at scale, so you can usually find some glaring patterns and solve those issues.

The second method, user testing, is a whole issue of its own.

If you can get help conducting user testing from someone who has done it before – a CRO person or user experience research – that will be much better, as there is some nuance and there are common mistakes people make.

But I do think user testing can be beneficial for those outside of traditional user experience roles, and I think content marketing is one of those roles it can help.

Essentially, the way to run a user test is to:

• Recruit target users who have never used your site (5-7 users)
• Create tasks for them to accomplish (usually a few specific and a few general)
• Watch them interact with your site
• Conduct post user test surveys to get attitudinal insights (optional)

There’s more to it than that rudimentary summary, so don’t just jump into it if you don’t know what you’re doing. Rather, read real resources like this one.

You can also just talk to your customers and readers. It’s more manual work, but can be a massive source of insight. I got so much value from being at conferences and interacting with CXL readers and fans. You really can’t overestimate that value.

Proving Business Value

In a larger organization, one of the most impactful things you can do is measure, improve, and evangelize the business impact you’re responsible for.

It can help you improve your own results, and it can also help executives in allocating resources and giving you the props due to you.

What’s ROI anyway?

Content marketing ROI is tricky because there are a lot of long-term and untrackable benefits to doing it. For example, Tim Urban can measure the number of subscribers he gets via his blog (and if his tracking is more advanced, how many per blog post).

But no Google Analytics attribution model will attribute his Ted Talk and numerous podcast appearances and whatever other opportunities he’s had to speak, consult, etc. to his blog – even though it’s quite obvious that was the reason and the catalyst for these opportunities.

That’s an extreme example, but even running a B2B blog, you’ll run into the same issue.

You can track leads and subscribers by blog, category, and post, but you can’t track how your authority built through content has helped close deals, build partnerships, or even raise capital. Those data points are more anecdotal if you ever hear them at all.

So, when you seek to prove out your ROI, you separate that which you can track from that which you can’t, and realize that your measurement strategy for content marketing is always going to be conservative by nature.

Still, though, it’s beneficial both from an optimization perspective and a resource allocation perspective to track what you can. And here we have a few models…

A range of approaches

Calculating the ROI of content, then, isn’t simple. It depends on what your goals are. Are you collecting email addresses? Building site authority to rank ecommerce product pages? Creating thought leadership because your category barely exists in the public knowledge? Building funnels to collect freemium user signups?

All of these goals require a different framework and methodology for measurement.

Therefore, I’m going to cop out here and simply point to resources that can help you structure your ROI measurement:

• The Formula to Calculate Content Marketing ROI (Convince & Convert) – this one is the highest level and the most fundamental. It can help you work out ROI calculations no matter what type of business you operate.
• How to measure the ROI of content marketing (Optimize Smart) – this is more in the weeds and tactical, looking at specific ways to get a dollar value of a piece of content using Google Analytics.
• How to Measure Content Marketing ROI: A Simple 4 Step Process – this, too, is a tactical approaching using Google Analytics, but it implies a specific goal and website architecture so it’s limited in its application to specific scenarios.

Conclusion

There’s only so much you can cover in a blog post, and this one is already long. But you get the point: content marketing and analytics don’t need to be antonyms. Rather, you can become a data-driven content marketers, and it can actually help complement the right side of your brain.

Knowing this stuff not only helps you do your job, but it also helps you communicate your value and evangelize your efforts. I think any business function that is serious about garnering resources should learn to speak in terms of business value, and like it or not, that necessitates a conversation centered around data.

Learn the lingua franca and reap the rewards.

Feature image source: Instagram.com/trevoratx

The post Content Marketing Analytics: 11 Ways Data Can Inform Your Content Strategy appeared first on Alex Birkett.

2017 Was a Good Year

In 2017, I hit lots of personal and professional goals. I started training Krav Maga and taking Spanish lessons (studied in college but never felt comfortable speaking). I moved up a level in Spanish (B1 –> B2) and feel wayyy more confident in conversation. I went boar hunting, hiked Big Bend, and generally tried to get outdoors much more often.

I took a growth marketing role at HubSpot, picked up a great client, and wrote a massive amount of articles on data and analytics. I’m also quite comfortable in R, and am just now finishing up another course that teaches more exploratory data analysis as well as visualization.

I spoke on a few podcasts, but I plan on doing more of that (as well as meetups and events) in 2018.

I continued my daily habit of meditation, but added to the morning routine with a gratitude journal, a Coffee Break Spanish podcast, and a few days per week, a Spanish lesson. I plan to continue tweaking the morning routine in 2018.

I traveled to lots of new countries, including Poland, Romania, Hungary, Italy, and Scotland, as well as some repeats like Ireland, England, Spain, and Estonia. I’ve got lots more travel planned for 2018.

Every year is better than the last.

2018 Will Be Even Better

I mentioned in last year’s post that I focus on broad themes or macro-targets, and then I zoom in with specific experiments and sprints. The Zoom In/Zoom Out model is popular in management, and it helps me be flexible but keep the big focus on mind. Therefore, I’ve got some broad goals here, but also some specific dates to reach some of them.

Career

I’ve got some macro and micro career goals.

At HubSpot, we track skill based goals on a worksheet and zoom in on particular focuses each quarter. The list of things I want to work on is pretty specific and typical to a growth marketers – SEO (current focus), data and analytics, experimentation, etc.

As long as I move the needle on a skill each quarter and continue to master data analysis (mainly R and SQL & predictive analytics for me) and experimentation, I’m happy.

I’m planning on taking Reforge as well.

Personal Branding

It was easy enough to keep visibility working at CXL; writing blog posts was part of my job. Now it takes extra effort on nights and weekends to make that happen. But I know it’s important, so I plan on writing at least 1 blog post per week. Doesn’t have to be a 5k word guide on Google Analytics. Just 1 per week to keep the cadence.

I also plan on speaking at ~4 conferences. They don’t have to be huge, could just be workshops, but I want to get more consistent with speaking.

Personal Development

Spanish: level C1 before March 1st. After that I may set a goal to reach a C2, or I may start off on another language like German or French.

Krav Maga: level 2 before June 1st. In 2018, I also want to add ground combat skills so I’ll begin taking BJJ classes at the same gym.

I’m also going to sign up for an Improv class starting in March, as well as taking archery classes around that same time.

I’ll continue my habit of reading 50 books per year (now lowered to 30, but same point).

One big thing I want to do in 2018 is spend less time in the city and more time in nature. Specifically, I’d like to go hunting a few times (and start taking archery classes again), fishing many times, and do at least one outdoors activity every time I travel.

Travel

I’m writing this in Colorado before heading to Milwaukee before heading to Boston and Vermont all in the month of January. Then in February I’ve got San Diego followed by Peru and Mexico. So, there are already a lot of plans in place.

I’d like to get back over to Europe again for a bit in the summer, primarily to 1) visit Spain again and really crush it with my master Spanish skills and 2) visit some of the Balkans. 10 new countries is ideal, but quantity is obviously the least important variable when it comes to travel.

Health

Lots of my “30 day challenges,” have to do with health, so I’ll continue doing those (Sober October, Discipline December, etc.). But one thing I want to focus on in 2018, outside of martial arts skills, is mobility and stability.

With that in mind, I’m going to do yoga at least once a week, but may even try to incorporate short 20 minute sessions into my morning and/or nightly routine.

Conclusion

My goals are largely continuations of things I’m already doing. Most of them aren’t super rigid, either, just broad themes that bring me where I wanna go. I feel happy with the course I’ve charted.

I’m excited for 2018. Lots of cool stuff from the personal development to the career to the experiential to explore.

The post 2018 Goals appeared first on Alex Birkett.

I’ve got a lot of experience promoting content, from running ego bait blog posts at LawnStarter to pick up thousands of social shares and dozens of backlinks, to creating the content promotion process at CXL that helped double traffic, to building links and promoting pillar pages at HubSpot to rank competitive product pages for products that were yet to exist.

Here’s what I’ve learned: some content promotion tactics work better than others, and some work in certain circumstances and not in others.

Regardless, if you’re tired of blog posts that just tell you to “email people mentioned in the article and share to LinkedIn,” then you’ll like this article. I’ll put some lesser known tips in here and walk through tactically how to do them.

Not only does this come from my own experience, but from dozens of coffee shop and Skype conversations with friends who run big content programs like Shopify, BigCommerce, Klient Boost, etc., as well as SEO geniuses like Ryan Farley, Benjamin Beck, and Luiz Centenaro. This is network knowledge at this point and I’ve just taken advantage of having a lot of smart friends.

Content Promotion Tactics: A Giant List of Ways You Can Get Eyes on Your Content

Long article (5k words or so) so I’ll break this up into rough broad sections, because there are different goals of different tactics, ranging from social shares to link building. The sections will be:

• Pre-promotion
• Social and Community
• Link Building and SEO
• General Traffic Generation/Other

Note: by including tactics here I’m not advocating for them. Unless I note otherwise, I’ve tried them and will try to gauge their effectiveness. If I haven’t used them, I’ll note that.

Pre-Promotion: Baking the Marketing Right Into the Post

1. Pre-Promotion: Include Influencers in Your Article

One way to guarantee distribution is to bake in content promotion to the actual article itself. How? Include influencers in the content creation process.

We see roundup posts all the time, some absurd in their list size…

Clearly this is overkill, but you can take the same thought process and include quotes and links from influencers in your content. This 1) helps you create the actual content and make it valuable and 2) ensures distribution channels upon publishing.

In fact, if you’re not a subject matter expert, you shouldn’t be writing content that doesn’t include quotes and insights from practitioners. In this case, treat your job like a journalist and include the opinions of those who know this stuff best.

It doesn’t have to be a pure “33 experts say” style roundup post. You can sprinkle in quotes where they matter and help the general article flow…

How to Find Influencers

First point: if you’ve been in your industry and role long enough, you should know the landscape like the back of your hand.

Second point: there are tons of tools to find out who the influencers are if you don’t know the industry well. These include:

• Buzzsumo
• Onalytica
• A simple Google search for “Top [X] Influencers”

Keep a list of people you meet and who you see speak at conferences, bloggers you like, etc. Your list of influencers should constantly be growing and updating.

How to Manage Influencers and Contributors at Scale

Two options here:

• Reach out to influencers on an ad hoc basis one-to-one (not a bad strategy)
• Processize things to reduce time and increase efficiency (a better strategy).

Here’s how you do it the second way…

Make sure you have your list of influencers, hopefully tagged by what their specialty is. Let’s say you want to write a piece on customer satisfaction and therefore you want customer experience experts. You then send all influencers tagged “customer experience” an email like this.

Hey {{name}},

I’m working on a big piece of content on customer satisfaction. I know this is an area where you have a lot of insight so I wanted to reach out to see if you can lend some expertise for the piece.

Here’s what I want to know…

{Question}

If you don’t have time to contribute, no worries, but I’d love to get your thoughts!

Thanks,
{Your Name}

Even better, instead of asking the question within the email itself (messy tracking there), you can create a Google form with one or multiple questions.

Then you can set up a Zap to transport the responses from Google Forms to your Google Sheet. This makes it easier when you have to follow up post-publish to thank influencers and ask them to share.

Instructions on how to set up Forms -> Sheets Zap here.

After you publish your content, use Mail Merge with Attachments to send an email to everyone who contributed. Doesn’t have to be super detailed…

Hey {{name}},

Thanks for contributing to our customer satisfaction post. We just pushed it live: linktopost.com.

Can you share it?

Cheers,
{{your name}}

2. Pre-promotion: Craft Content That is Controversial or Hits Emotional Points of Pride

Even if you’re a shrewd consumer of content, you’re pretty likely to share content that has to do with where you live, where you’re from, where you went to school, what your job is, etc.

Including quotes from influencers is a form of ego-baiting, but so is including a reference to the top 10 Midwest college lawns. It’s silly how many shares you can rack up if you create content like that.

For a while at LawnStarter, we were ranking first page for “Midwest Colleges.”

I’m going to be honest: I’ve definitely shared blog posts that ranked UW-Madison highly. I bet you’ve shared similar content with your respective school, town, etc. Very few of us are immune to this kind of “Granfallooning”

This is, by the way, the entire strategy of content sites like Thrillist. It’s almost obnoxious when you know how the sausage is made – and you know the marketing psychology and pandering behind it. But it works because people feel pride in their school, town, sports team, whatever…

This may not work for every site and niche, but I’ve seen it work for a wide variety of sites already (including eco-friendly wedding rings):

Similarly, ranking and listing top software products is a common tactic in the B2B space. How many posts have you seen like:

• “Top Marketing Influencers You Need to Follow on Twitter”
• “Top 54 SEO Tools in 2017”
• “Top 18 Customer Success Blogs”

It’s the same mechanism. If you’re on that list, you’re going to share it.

3. Run a Survey

Keeping with the theme of “include people in content creation,” you can create a survey (which, depending on the interestingness of the results, can also act as a nice backlink hook).

Here’s a good example from Orbit Media:

They probably had some noble intentions regarding research and learning about the blogging space. But it doesn’t hurt that they can turn around and use those 1000+ bloggers they surveyed as a distribution network (and to get some backlinks – they’re all bloggers after all!)

Social and Community

4. Tweet or Email Influencers Mentioned

Super simple tip: for people you mention in the article, tweet or email them and let them know.

Short and sweet:

Hey {{Name}},

Mentioned you in our latest article, {{article}}, and wanted to give you a heads up.

Hope you enjoy it!

{{Your Name}}

Don’t treat this is transactional, though, treat it as a long term relationship building mechanism.

A Tweet literally means nothing unless it comes from, like, Miley Cyrus.

However, being connected with and respected by experts in your industry has long lasting effects for not only content distribution, but for introductions, partnerships, and other long plays in the future.

Don’t be a goof and treat internet connects differently than you would in person connect. Here’s a bad cold email with too little context and too much of an ask with no warm up:

5. Spend All Your Free Time in Communities Related to Your Business

There’s a nice framework for marketing that Scott Tousley taught me by way of Ramit Sethi: you go where the fish are.

You define what type of fish you want to catch, figure out where those fish are swimming, and then cast your net.

There are Facebook communities and Slack channels for the marketing space, local homeowners, customer success professionals, those planning on getting married soon, candle aficionados, etc.

Every company I’ve worked for or worked with has been able to leverage communities for their benefit (both through knowledge and customer research as well as reach and distribution.

There’s not a lot I can say that hasn’t been said already on the topic of communities and marketing, except to reiterate this point: don’t be a dick.

If you just join groups and spam your content, you ruin it for every other marketer, and you’re also ineffective. There’s nothing beneficial about your lazy strategy to anyone, including you.

Especially avoid shady and lazy marketing on communities like Reddit and Hacker News. The reason these places are valuable is because they largely lack the self-promotional hucksters that make it to the top of other communities effortlessly. If you’re going to promote in these places, do it the right way (good case study on how to do that here).

Best bet: put the time in, be a valuable contributor to the community, and only share your stuff if it’s relevant and valuable.

6. Email or Tweet People and Ask Them to Share

This tactic sucks.

I guess sometimes the end justifies the means, though, and maybe you can squeeze some more juice out of a launch with this tactic.

Basically, you should get a list of influencers, cold email them, and ask them to share your content or upvote it on whatever social network.

How do you find them? Again:

• Buzzsumo
• Onalytica
• Scraping relevant communities (ugh.)
• Your own knowledge of the industry

It will be an evolving and growing list, not a static one. The important thing is to tag influencers according to their category of interest. Something like this…

Important: make sure you don’t double email people. So if you’ve work with an influencer to put together the article (previous section), don’t send another email to them if they’re on this influencer list.

How to know there are duplicates? Lots of VLookup, or use a centralized system like HubSpot CRM or an automated email system like Mailshake.

For this idea, probably don’t use it every time. Only for special and epic content pieces.

For the record, I think this one is super, super annoying when it’s used on me. Lots of people are annoyed by it, usually because marketers copy and templatize other marketers, and think only in the short term. And they send stupid pitches with no value offer.

Depending on the person or brand emailing me, I may tweet their content, but I’m not happy about it. It’s super short term thinking. The following is one of the worse examples I’ve seen (I was scraped from a list of GrowthHackers users I think)

7. Share on Social Channels

You know how to share stuff on social, so I don’t need to go into detail on this.

I’ve never worked for a company that this brought in a large amount of traffic, but if you’re targeted about your social sharing it can give a solid boost to your content promotion efforts, especially upon launch. If you’ve built up a big social following, absolutely use this as a channel. If you write viral, vapid content like Buzzfeed or whatever, you probably rack up 90% of your traffic from social.

But it can work for any brand and should be utilized to a certain extent in most cases.

If you have a famous or important figure to share your content, that can bring some traction.

Whatever social channels you have work: Facebook, Twitter, LinkedIn, etc.

There are different rules of engagement and best practices for each channel. Usually, they vary by network, industry, company, and seasonality or even randomness.

Be careful when reading articles that tell you how many times you should tweet or the best time of the day to do so. There’s also likely not a best way to use images, video, or the actual structure of the post. It requires some good old marketing ingenuity so don’t copy and don’t be lazy; Instead, experiment.

8. Repurpose Content for Social Networks

This takes a bit of effort but can pay off well. You’ve probably noticed this (in my opinion, annoying) trend of these LinkedIn posts:

That’s one method. You can also publish on LinkedIn, Facebook, Inbound.org (they do originals), Medium, Slideshare, etc.

In my experience, republishing on social has been a lot of work and little return, but I know a lot of people who have made it work. Worth a try if you have the type of content that is opinionated and suitable for virality on social channels.

Channels come and go. Tactics within channels change. If I wrote a series of tips on how to repurpose content on LinkedIn here, I guarantee it would change in a year.

So, as I said with social, and as I’ll say with most of these avenues, you need to do your own experimentation and innovation. Looking for tactical cookie cutter formulas is a great way to operate several steps behind the competition.

9. Automate Your Social Sharing

Also, if you can automate your social sharing, you can bring some incremental value with zero effort (beyond setup).

We set up an automated Twitter sharing tool using Zapier at CXL and it brings in a good amount of traffic with zero effort (email me if you want more info on how to set this up). Twitter is such an echo chamber that no one cares (or notices) if a brand auto tweets their articles 15 times a day. I probably wouldn’t use this method on other channels.

If you use WordPress, you can also set up Revive Old Post, which sets your old blog posts on an auto-rotating posting schedule on Twitter.

You can also pack a bunch of tweets into Buffer or whatever social tool you use. Similarly, you can engage with automated content promotion networks like Quuu or Viral Content Bee.

I’ve found very little impact with these, but it’s also low effort, so take that as you will.

Anything you can automate without seeming spammy is probably worth doing if it’s low effort, especially if operating at a scale where those incremental increases can add up.

You might think it’s a good idea to automate your Twitter DMs, but you’re probably wrong.

If you bring me data telling me it works, I’ll change my mind, but doing this stands against my principles of authenticity. It’s quite clear that the CXL posts are automated, but when you’re automating “personal” DMs, it feels scummy. Again, feel free to prove me wrong and show me some results.

Link Building

We’re aiming not just for a flash in the pan viral article, but for long term organic traffic. As such, doing some link building, for most sites anyway, is a necessity, especially for more competitive keywords.

Here are some of the link building tactics I’ve tried.

10. Link Trading

This is straightforward but is limited in scale. Basically, do what Google doesn’t want you to: find some people to trade links with.

The people you trade with should have access to high DA and relevant sites (e.g. if you’re a digital marketing agency, trading links with Unbounce or Shopify would probably be great). Only work with a limited amount of people, and only trade links with your best content. This tactic, at scale, can trigger red flags for Google and result in penalties.

This strategy is by nature limited (it can look spammy if you do it at scale), but it can help get the ball rolling and get you some solid exact match anchor text links.

Use Slack groups, Facebook groups, or just strong personal connections for this.

11. Traditional Outreach-based Link Building

Email outreach is the style of link building that most people are familiar with.

You need to 1) find relevant target blogs that could link to your content 2) reach out to them. These target blogs could have related broken links, link to competitors, or simply be a relevant site that would benefit from your new amazing content.

If you’re doing broken link building, it’s a lot easier to get the person to update the link. If you’re simply asking them to replace a link from a competitors with yours, it’s a bit harder of an ask. In that case, you need to add more value (can they guest post for you? Can you offer some sort of comarketing? In any case, the value or relationship needs to be stronger.

In any case, here are some ways I’ve found link outreach targets

A) Broad Target Sites for Links

To start, simply use search engines and search phrases like:

• “Keyword”
• “Keyword” blog
• Random word “Keyword”
• “Keyword” guest post

B) Top Shared Content

Use a tool like Buzzsumo to see who is crushing it in terms of your niche or topic. Use those as link targets.

C) Competitor/Skyscraper Link Building

Search the term you’re trying to rank in Google:

Take a URL of someone ranking and put it in Ahrefs. Look at the backlink profile (who is linking to them?):

Reach out to all these sites and ask if they can add your link instead.

This is hard work. It’s not as easy as the case studies make it out to be, but at scale you can pick up a few links (especially if you have a strong brand or a strong value add in return).

D) Web Scraping for Link Opportunities

Summary: You can scrape software review sites to find lesser known but high domain authority software company blogs. I’ve used Capterra. It’s quite effective in finding sites you may not have known about (and there are so many software companies out there, and most are blogging!).

For obvious reasons, I’m not going to walk step-by-step through this (if the reasons aren’t obvious, scraping is usually frowned upon, and anyway, it’s quite technical and in the weeds. Send me an email if you want to know more).

E) Growth Bot for Link Opportunities

This one is similar to the web scraping. You’re basically trying to find lesser known sites and link opportunities, but for this one we’ll use GrowthBot (and also, we’ll save a ton of time).

Run several queries with companies in your niche:

Don’t be afraid to run down the rabbit hole. Run maybe 10-12 queries and copy and paste them into a spreadsheet.

Now let’s clean things up. In cell B1, write =LEFT(A1,FIND(” (“,A1)-1). In cell C1, write =RIGHT(A1,LEN(A1)-FIND(” “,A1))

Your first row should look like this:

If all looks okay, copy the formula down all cells (hover on the bottom right corner and double click when you get the black cross) for both Column B and Column C, as such:

Copy the values from Column C and throw them into a domain authority checker (whichever you prefer, Moz, Majestic, Ahrefs, whatever). Export the file one it has processed:

Add the domain ratings to the list, use conditional formatting to target those within your ideal range, and find contact information for those link opportunities. Next step: email outreach.

F) Twitter + Zapier Hack

This one involves setting up a Zap to see who shares your content, and using this as a preliminary outreach list.

The idea: if they’re already sharing your content, or similar content, they’re going to be warm targets for link building.

Setting up the Zap is super easy. Use the Twitter -> Google Sheets Zap. Just make sure you’re collecting all the fields you need. In our case, they were: Username, Name, Tweet, URL, Associated (Bio) URL. The Bio URL is of particular importance, because that’s how you’ll find out whether they have a website that can link to your content.

There’s no solid way to automate domain authority checking in Google Sheets (that I know of), so you need to port your list of URLs over to a tool like ahrefs to get their domain ratings.

Add them all to your Google Sheet and look only to those domain ratings you think are worth trying to get links from. Gather contact info and do your outreach.

This strategy has been mildly effective for me. I’ve found that it gets links, but they’re generally lower domain authority simply due to more agencies and personal bloggers sharing content on Twitter. It could differ with your audience though.

The benefit, though, is that if you set up your Zapier right, you just automatically collect link opportunities, so this can certainly work at scale (and I’m sure there are many uses for a Zap like this outside of SEO, such as for influencer marketing and affiliate targeting).

Again, email me if you want more details on setting this up, it’s somewhat technical.

Now, Send Outreach Emails

Outreach emails should be straightforward but polite.

They should clearly state what you want from them (share, upvote, backlink, coffee date, whatever), but they should also provide value for the recipient (otherwise this is just a short term burn the bridges strategy).

When possible, I like to kill two birds with one stone. If I’m doing content promotion for HubSpot or CXL, I have a powerful asset in the form of my blog, so I ask if the person would like to contribute a blog post or just a quote to an article. Why not check both off in one email?

Another thing is that most of the time, people don’t take action on the first email. It may help to automate a 2 or 3 email sequence, though be careful not to annoy the shit out of influencers just for the sake of a backlink or tweet (don’t miss the forest for the trees).

No one is completely sure how to do proper influencer marketing, except for the few best practice variables of “be relevant” and “give value.”

I’m firmly in agreement with how Ryan Holiday put it in an AMA. Treating influencer marketing as transactional and quantitative, and treating friendships like a cumulative series of touchpoints is both sad and ineffective:

Another note: I usually send remarkably similar emails, though I hesitate to use the word “template,” as they’re largely personalized and the contacts are well researched.

If you’re wishing I’d share a template, don’t, because a large reason this type of outreach is ineffective is because of the armies of copycat marketers using the exact same words. I got probably a hundred emails using Brian Dean’s exact template. No quicker way to trigger a “delete.”

12. Internal Link Building

This is easy. Search site:yoursite.com “keyword” and add links anywhere applicable.

Track on a content promo spreadsheet so you know what you’ve accomplished and where you still need to add links.

13. Seed Content to Freelance Writers

This idea has a little bit more personal touch involved. Here’s the premise:

• There are a lot of freelance writers
• These freelance writers have access to some pretty top tier sites.
• They link to lots of resources and data.
• You should be one of the resources they link to.

Usually, a freelance writer will link to 1) those they know and 2) those they find with a quick Google search. If you can be someone the writer has a personal connection with, you can rack up exact match anchor text links in a variety of publications.

The trouble? This isn’t a super scalable strategy.

You have to build relationships and some sort of value exchange. Can you offer guest post opportunities or links on your site? Can you get coffee with freelance writers a few times per week? How you make this work is variable; the point is that you should have a network of freelancers and guest writers that can place links on external publications.

One of the best ways is simply to build relationships with writers and influencers and have some good research to supply them. Everyone wants new research and data, and it’s really not that difficult to conduct some research and be the supplier.

Related: go to conferences to hang out with influencers. It has long term payoffs that are hard to quantify in the short term.

Obviously this is an expensive strategy, so I think it should just be a complementary activity everyone does at conferences, meetups, and organized events.

It doesn’t have to only be at large conferences, though. This could be as simple as meeting people at Meetup.com groups or Slack channels. The point is the same: build relationships.

14. Cut a Deal with Freelance Writers to Drop in Links to Your Articles

If you don’t want to put in the time and effort to build relationships, you can probably pay for them.

• Step 1: create an ad on Problogger.
• Step 2: hire a few good writers.
• Step 3: after working with them for a few articles, bring up that you’d be willing to pay them [X} amount of money to drop links to your content in the other sites they write for.
• Step 4: Acquire links.

Never done this, but it sounds like a good setup, yeah? Try it and lemme know if it works for you.

15. Work with Partners

If you’re a B2B company (or sometimes if you’re a B2C company), you likely have partner companies. At HubSpot, there’s whole network of partner agencies (same goes for companies like Unbounce, Amplitude, etc). Think, how can you team up with them for comarketing and content promotion?

In my mind, you have to give value to get value. So you can approach getting your link in two ways:

• Simply ask them for a link.
• Ask to write a post for their blog.

Most people struggle to find and create good content. You can easily bite a piece off of your 10X content and repurpose it for another blog post for an agency or technology partner.

The benefit here is that you and your technology/agency/comarketing partner have a previous relationship. There’s no built in skepticism at the start of the outreach.

Also, there’s obviously a whole slew of things you can do outside of link building with your partner network. But this is a content promo article, and darn it, I’m going to keep the focus.

16. Buy Links

Buying links still works.

You’d be surprised if you knew the level of link buying and selling that is still going on among top internet marketing influencers. I won’t sell anyone out, but I can vouch that people are still doing it and getting results.

Risky, lazy? Sure. Effective? Probably.

General Traffic/Other

17. Focus on List Building and Email Marketing

Generally speaking, the biggest leverage point you can build is a solid email list.

It’s a property you own, regardless of Google’s algorithm changes or the decreasing organic reach of a social network. It’s an asset where people have opted in to receiving your communications in their inbox, a special privilege indeed.

That’s why the internet has been taken over by popups, overlays, exit intent splashes, whatever euphemism you use for them. It should be easy and seamless if someone wants to sign up for your list.

Oh, and push notifications. I consider those popups too. Same deal, they get permission to send you information in the same way an email popup does.

I won’t pass a judgement call on how you collect emails, just to say that email list building is huge and if you can leverage it you have a strong content distribution channel.

18. Comment Content Promotion

Leave a bunch of relevant and valuable blog comments. This strategy is boring and tedious to me, but if you have the time and can prove out the ROI, be my guest.

19. Sponsor Other People’s Email Lists

Whether you do email list trades, affiliate deals, or simply sponsor a newsletter, other people’s email lists can be awesome ponds in which you can catch fish. At CXL, we used to do quite a few email list trades with other similar software companies like Amplitude and Formisimo.

There are also businesses that exist solely to sell you advertising space in email newsletters, which can be much more effective (if you target it well) than buying display space or more traditional forms of online advertising. This is particularly effective if what you’re advertising is content related, like email courses, ebooks, and otherwise.

20. Paid Acquisition

If you have a particularly effective and epic piece of content, and you have some money, you always have the option of giving it a paid boost. Lots of companies do this.

21, 22, 23, and Beyond.

There are a bunch of smaller tactics, too, that I’m not going to mention.

It’s not because I’m lazy (well…), but rather because almost every other tactic I could include is basically a subset of the other tips or marginalia. I could split “communities” into a dozen different tips, as well as “repurpose content” into every single channel you could use. But that would be boring and unhelpful (as well as ephemeral).

In addition, the tactics that make up most of these content promotion tactics lists are so obvious and micro that they’re unhelpful. Things like pinning important Tweets to your profile and scheduling 12 tweets in advance and tweeting at certain times of the day. Marginalia.

I’m not going to tell you to email your mom about your new blog post, because while it may be more than 0 new sessions, it’s not helpful for your actual content promotion efforts.

In an ironic twist, I’m not baking content promo into this blog post so I don’t need to have a list of 100 items just to make it bigger than the other ones ranking (the Skyscraper technique, while inherently a great idea, has, through misunderstanding of its application, ruined content in a lot of ways, yeah?).

Worry about the big stuff, test meaningful tactics, learn, and systematize it.

Conclusion

Getting content promotion right is hard.

Well, it’s easy to go through the motions, or even get wins on one or two content launches.

It’s really hard to do it over and over again, setting up a content promotion process.

The way I’d do it is to try a few of these, prioritize them by your confidence in them and the ease of implementation, and review your results. Tweak and optimize the process, and continue to improve it with time.

In addition, look for the big wins and where you have a competitive advantage. Unless it’s of massive upside to you, don’t spend too much time tweaking the minutia of a tweet when you could be building a long term SEO and link building strategy (or whatever your specific high leverage area is).

The post Content Promotion: Every Single Tactic You Can Use to Boost Traffic appeared first on Alex Birkett.

(Edit March 2018: just took a test and reached level C1. Now on to level C2!)

I didn’t plan on writing a post about it because I’m not moving faster than anyone else, nor do I have a hack that helps me learn faster or better. I’m a normal dude with a job who is learning Spanish on the side, which is why I decided to write the post (and also because Luiz Centenaro told me to write it).

Lots of others are written by “language hackers” who have systems they want to teach you (if you pay them).

How to Learn Spanish: Prerequisites and Preparation

I think of learning in two parts: the planning and the execution.

If you spend a bit of time (not much) planning on how you’ll learn Spanish, you’ll waste less time actually doing so. You can also better gauge the effectiveness of your program if you outline goals ahead of time.

So there are three points here:

1. You need to have a strong reason to learn Spanish.
2. You need to set specific and measurable goals.
3. You need to build a habit of daily practice.

1. You need to have a reason to learn Spanish.

The allure of a superficial reason will fade fast, so you need to find a strong why.

Trust me, you’re going to hit plateaus, where it feels like you’re not getting any better day-to-day. To combat that, you need to do as George Leonard says, learn to love the plateau. You can only love the plateau if you have a good reason for going through it in the first place.

For me, I fucking love traveling and have ambitions to travel South America (have a trip coming up to Peru and Mexico in February). Also, I love the culture in Spain, have been twice, and hope to spend a ton more time there in the future (most likely a another trip coming up this summer). I love the way the language sounds so there’s an inherent desire to learn it.

I’m also somewhat strange in that I like learning for learning’s sake, and I’m not super affected by plateau disappointment.

Whatever the case, know your reason and make sure it’s strong enough to withstand future distraction and disappointment.

2. Set reasonable but ambitious SMART goals.

Most people know that, when seeking to lose weight, they need to be specific. 10 pounds by Christmas is better than “lose some weight.”

Those same people that understand that tend to set a goal to “learn Spanish,” as if there is some magical end point where you kick back and say, “ahh I’m done learning Spanish!”

I’m not done learning English yet (I like to think I’m getting better all the time), so it’s important that I set discrete goals for Spanish, even though the process itself is continuous. In my case I used CERF levels (B1, B2, C1, C2, etc.) and a specific date to attain each. My exact goals:

• B2 by December 1st (succeeded)
• C1 by March 1st (pending)

Yours could be different, such as “be able to carry a 3 minute conversation in Spanish with a native by X date.” It just needs to be specific, measurable, attainable, results-focused, and time-bound (SMART).

3. Build a habit of daily practice.

Spaced repetition is better than binging (though don’t stop yourself from binging if you desire). Do something every day, the more the better, and the more varied the better.

How to Learn Spanish: My Daily Routine

Your routine can obviously differ, but here’s exactly what I did (and do) every day:

• Read a book in Spanish in the morning with my coffee (15-20 minutes)
• 1 Spanish podcast per day (usually Coffee Break Spanish, but sometimes Radio Ambulante) (20-30 min)
• 4 lessons of Duolingo (5-10 minutes)
• Flashcards before bed (5-10 minutes)
• Skype lessons with an instructor twice per week (Monday and Thursday – 1 hr each)
• Informal Spanish conversation with my friend Svitlana on Friday afternoons (20-30 min)
• Saturday Spanish meetups at the local library (I started this after attaining B2 level, but don’t go all the time – 1 hr)
• 1 Spanish movie each week (1.5-2 hours)

This adds up to about 12.5 hours per week, or a little over 1.5 hours per day. Highly do-able even if you’re not a full time language hacker or a language student.

In addition to this, I’d listen to Spanish music (Amaral is solid) when I could. I’d also squeeze Spanish into other activities, like watching Spanish dubbed movies on flights). I’d take every chance for a conversation with someone who knew Spanish as well. All the practice I can get.

And that’s pretty much it. That was and is my practice.

It’s really about 1) motivation 2) specific goals to keep your focus and 3) repetition and getting in the reps each day. There’s nothing hacky or sexy about it, but I’m moving forward every day and will be at a C1 level by March 1st.

Assorted Notes and Tips to Help You Learn Spanish

Once you have your reasons, goals, and daily habits down, the rest if pretty much just putting in the work. However, I can give a few tips for learning more efficiently and optimally.

Most important: Listen & Speak as much as possible.

I studied Spanish in college for a few years, but when I went to Spain I found out I couldn’t really speak it. Huge bummer for me.

I was afraid of making mistakes, and while I could read it on paper (to an extent), I couldn’t speak at all. This is, of course, a problem when your main goal is traveling and conversation (not reading the Mexican newspaper). Start speaking as soon as possible. Read Fluent in 3 Months for a good primer on this “speak first” approach.

Also, don’t be afraid to sounds stupid. That was by far my biggest barrier to learning, but getting over that made everything else possible. A good way to get over this is to get a professional instructor. Which leads me to…

Get professional lessons and pick the right teacher

Do your Skype lessons in the morning, or at least at the same time each day/week. Mine were (are) always Monday and Thursday at 730am and this helped get me in the habit of doing them every week. Also, my teacher gives me homework, so having the same lesson days each week helped me plan out when I would get my homework done.

Also, have an awesome teacher. I have an awesome teacher. How to get an awesome teacher: try out a few different teachers to start with and keep the one (or two) you like best. If you just go with one then you may think you go a great one but you won’t know until you compare your teacher to other potential teachers out there.

Use Italki to source instructors. You can also use Italki to find language exchange partners for free. Use this link to sign up and we both get $10.

Read in Spanish

Get books you’d be interested in even if it was your own language. I’m rereading 48 Laws of Power in Spanish because I’d like the book in English anyway. In school we always had to read these ridiculously boring and poorly written short stories, and it made it such a chore. Kill two birds with one stone and read something you’re actually interested in.

On the other hand, try to read materials that were originally written in Spanish. Source recommendations from a teacher or friend.

Also, note that you can translate most New York Times articles to Spanish.

Let your interests lead you

You’re going to find that certain methods of learning are more fruitful than others. I’m weak at listening and speaking, so classes and intercambios are the most important for me. But if you’re a big movie buff, you may find that replacing a movie or two per week with a Spanish one drastically improves your understanding of the language. So go with it. Be fluid. Learn how you want to learn. It’s about practice, exposure, repetition, so get your time in how you can.

Travel if you can

Setting travel plans months ahead of time makes me really excited to learn Spanish. I’ve got a Peru/Mexico trip coming up, and that excitement lends itself to learning; I approach learning sessions with that much more vigor. If you can’t travel, at least try to set time and goal based rewards for yourself. It helps to have a carrot as well as a stick when learning.

How to use flashcards the right way

Flashcards are a core part of memorization for most Spanish language students. Some people use apps, though most I think still just use traditional paper flash cards. I know there are a few software solutions out there, like Memrise, but honestly, I haven’t found any of them satisfying. There’s a certain lack of control with flashcard applications. Though what I do like about them is their automated ability to use spaced repetition to help you really learn a few words well.

So here’s what I do with physical flashcards:

• I make flashcards using words that I find when reading books in Spanish. Words that come up frequently that I don’t know. This way I know they’ll be useful for me to understand in the near term.
• At this point, I’ve created a few hundred cards using this method.
• To start chopping them down and learning/memorizing the words, I grab a stack of about 7-10 cards per day.
• So, for example, on Monday, I grab a stack of 8 pre-made cards, put it in my back pocket, and those are my words to learn for the day.
• Then, several times throughout the day (work breaks, waiting at a cross walk, etc.), I simply review those cards.
• The next day, I move on to the next stack.
• I keep 7 stacks of 7-10 cards on my desk, and grab one stack every day (shuffling them so it’s somewhat random), and I use them for about two weeks. This ensures I really nail down this set of words.
• Then, after I feel confident with that set of cards, I move onto another set of 7 stacks of 7-10 flashcards for the next few weeks.

I find this allows me to really focus on a few words at a time, use them in conversation, and incorporate them into my arsenal of usable Spanish (and not just be retained as “recognition” words that I’d know if I saw them in a newspaper). They become actionable vocabulary. This is the best way to learn Spanish via flashcards I’ve found yes.

The post How to Learn Spanish (My Process) appeared first on Alex Birkett.

But you have work to do. Or at least I do. So I don’t want to spend all my time on Facebook. And if I am spending time on Facebook, I want it to be valuable.

So I did three things that made sure every second I spent on Facebook would be a net positive effect on my life.

No One Productivity Hack Will Save You

First off, even though this article is about ‘productivity hacks’ – quick things you can implement to see change – no productivity hack can save you from yourself.

You’ve probably noticed there are a lot of productivity blogs – or at least productivity tips interspersed throughout other blogs. It’s not because people want to help you be more productive. It’s because they want organic and social traffic. Trust me, I’ve written posts like that (for that reason) before.

And I’ve tried a ton of productivity tactics. I do short two week experiments and attempt to quantify any meaningful correlation in performance. Most productivity hacks, alone, don’t move the needle much.

Some of the ones I’ve tried that everyone else seems to revere are:

• Pomodoro
• Lemon water in the morning
• Exercise in the morning
• StayFocusd chrome extension
• Waking up really early

Some of these allowed for marginal increases in productivity, but nothing revolutionary. Certainly nothing on the level of “this ONE trick” articles. And of course, everyone is different. What works for one person may not work for another.

This is all to say that just because you aren’t scrolling through your newsfeed anymore doesn’t mean you’ll be a more effective person. You can block a website, but your clever mind will find a way around it (or at least find another way to waste time).

In the end, you need to be an effective person. That, or chug a crazy amount of coffee.

Now, the Facebook stuff.

Three Steps To a More Productive Facebook

I was trying to solve two problems:

• I wanted to spend less time on Facebook
• I wanted the time I spent on Facebook to be inherently valuable

It’s hard to define ‘valuable’ because of the subjectivity involved. But since Facebook began for me as a social connection tool, I wanted all my time spent there to be talking to friends, participating in groups, or otherwise engagement in dialogue. Everything except the newsfeed basically.

People that scroll through their Facebook newsfeed a lot tend to experience more:

• Loneliness
• Depression
• Anxiety
• Body image issues
• FOMO (Fear of missing out)

Shit is also addicting. It works by the rule of triggers and variable rewards (i.e. you can’t predict when you’ll find that dopamine producing content, but you will find it, and therefore seek it in your newsfeed):

I was also very aware that a lot of the time I spent on Facebook was on mobile. When in line or whatever idle time I had, it was so easy to pop open that app, especially when I had notifications turned on (terrible idea).

So with those points in mind, I recommend three actions:

1. Downloaded News Feed Eradicator.
2. Delete your mobile Facebook app.
3. Change Facebook’s default language to one you’re trying to learn.

That’s it. Super easy.

News Feed Eradicator is a Chrome extension that replaces your news feed with an inspirational quote. No more mindless browsing. Now you can consciously check out difference Facebook groups or chat with friends.

Like this:

So far so good…until you check your phone (the extension doesn’t work on the app). Which brings me to my second action: Delete the Facebook app from your phone.

Oh, and make your Safari settings Incognito by default. That way your browser won’t remember your login info, so you’ll have to enter it manually every time.

We’re basically doing reverse conversion optimization here – we’re adding friction everywhere so it makes us less likely to spend time on FB.

Finally, change your language to Spanish – or whatever language you think would improve your life if you knew it.

There are multiple benefits. First, of course, you learn the language better. Second, and maybe more importantly, it makes Facebook more annoying to use. If you have to think about every sentence and every word, it adds a whole lot of friction.

Conclusion

Three things:

• Download News Feed Eradicator
• Delete your Facebook App (and make Incognito browsing your default so your browser doesn’t remember your login)
• Change Facebook’s default language to one you’re trying to learn.

Easy. Now go do work (or browse Reddit until you’re forced to clamp down on that habit with a productivity hack as well).

The post Three Instant Ways (<2 min) to Make Facebook a Productive Place appeared first on Alex Birkett.