“Make money blogging” sounds like a topic well suited for a YouTube ad featuring a rented mansion and Lamborghini.

But clearly it’s possible to monetize a blog. In fact, I monetize my blog! I also run an agency that literally works to help companies drive revenue with blogging. Every company who runs a blog has an explicit or implicit desire to do so (otherwise, why would they blog?!).

Of course, you don’t have to monetize your blog. You can just write for yourself or your friends. That’s totally fine, too.

But if you are interested in making money from your writing, then read on. This is mostly going to cover the perspective of a solo blogger, but you’re also going to learn a lot if you work in-house as a content marketer. This article is fundamentally about content marketing strategy and how to center it around revenue.

This article will cover how to monetize a blog in two parts: first, building a blog worth monetizing, and second, actual tangible monetization tactics to help you drive active or passive income.

Editor’s note: this post comes from my personal experience building a content agency as well as monetizing this blog you’re reading now. I’ve also helped build content marketing channels at three different companies. And I’m not going to sell you a get rich quick course.

How to Monetize a Blog? First, Build a Blog Worth Monetizing

First thing’s first: you need to have a blog worth reading, and not just worth reading, but something that can actually be monetized.

8 Steps to Building a Blog You Can Monetize

If I were to start a blog from scratch, here are the steps I would go through:

1. Pick the right topic
2. Map out potential monetization pathways
3. Choose a content strategy
4. Choose a content distribution channel
5. Write high quality content at scale
6. Promote your content
7. Map out conversion points in your content
8. Measure, optimize frequently

1. Pick the right topic

Picking a topic is probably the most important thing you can do.

Some topics will languish in obscurity, while others will be so competitive that you’ll never be able to stand out from the fray. Then there’s the sweet spot: a topic that is lucrative, yet relatively untapped.

Ideally, you also want to blog about something you actually know and care about. Otherwise people will see through you, your content will suck and competitors will outrank you easily, and you’ll get bored and quit the project when it’s not making progress.

So write about stuff you know and like, not just because it’s ethical, but because it’s effective.

This, by the way, was Tim Soulo’s answer when I asked him what he’d do if he were starting a new blog from scratch today. It’s just too hard and too long term to do anything you’re not actually interested in.

Luckily, your interests will almost certainly map to a topic that is monetizable. You just need to do some soul searching and initial research.

The best topics to monetize:

• Have rising popularity
• Currently have companies or affiliates making money in it
• Have significant search volume
• Have communities that formed around the topic, either analog or digital

You can find topic trends using Google Trends or Exploding Topics. The Hustle’s “Trends” newsletter is another great curated way to do this.

The Trends newsletter is how we found “kava” was a rising trend. We launched cupofkava.com to take advantage of that (though actually got bored since it wasn’t a niche we cared about – see? This advice isn’t just theoretical!)

Even better if the topic you write about is a niche that serves high income audiences. Selling expensive things, more often than not, is going to be a better bang for your buck than selling cheap things. That’s not always the case, but I tend to like B2B and luxury niches more than mass market niches.

Just think, if you want to monetize a blog through affiliate marketing, what’s easier: selling B2B software at a 30% cut or selling javasok sleeves at a 30% cut? The former is going to kick you back 100s of dollars a month per sale in many cases whereas the latter only costs like $5 total, so your cut is going to be minuscule and you have to make up for it with volume.

For example, look at bloggers like Ryan Robinson, who monetizes through affiliate marketing as well as consulting and courses. The affiliate products (as well as consulting) he sells are high ticket items, so even one purchase is worth quite a bit of money:

2. Map out potential monetization pathways

While you don’t need to perfectly plan out your monetization strategy, you should loosely know how you’ll make money before you begin.

“Plans are nothing,” as Eisenhower said. “But planning is everything.”

• Are you starting a blog as an acquisition channel for a SaaS or ecommerce company?
• Can you dropship products or monetize with affiliate links?
• Can you build a course, digital products, or a membership community around the topic?

Again, you don’t need to know this in advance perfectly, and you can always change and adapt this vision over time. But if you have *no* idea how it will make money, it’s going to be much harder.

For example, I knew when I started my personal blog that I could monetize through the freelance writing I was doing at the time. That monetization strategy has changed over time. Now I monetize with affiliate marketing as well as a course and my agency. Each of these serves a different audience and has a different payout (affiliate is super low touch, course is $1k, and my agency costs $10k a month). But this has adapted over time and as my life has changed.

At the start, however, I knew I could pull clients from my content.

If you want to write about kava, then you know, to an extent, you won’t be selling coaching or consulting. More likely, you’ll need to develop an ecommerce site, drop ship, or use affiliate links. Perhaps you could build a community around kava enthusiasts.

Just brainstorming some of this in advance will not only help you determine the feasibility of your topic, but it will help you choose which content strategy and distribution plan to use.

3. Choose a content strategy

The number one cause of death of most blogs is a lack of strategy.

Sure, content quality matters, as does how you distribute and promote your content. But if you don’t have a plan in place, you’ll likely end up wasting a ton of time and money producing content that never produces ROI.

Why?

The reason is simple: there’s a ton of content out there already.

Apparently 7.5 million blog posts are published every day. Many of these will also languish in obscurity, but a nontrivial number of those blog posts will be published by well known brands and websites with a high domain rating. This means that, all things equal, those websites will crowd you out, outrank you, and keep you in oblivion.

Content strategy is hard. It depends so much on what your natural strengths are as a founder, what resources you have available, the strength of your website, and the industry you’re blogging in.

I’m going to link out to my ultimate guide on content strategy, because there’s no way I can do it justice in this small section here. I will, however, summarize two strategies that tend to work quite well for small websites:

• The Wal-Mart Content Strategy
• The Barbell Content Strategy

The Wal-Mart Content Strategy

The Wal-Mart Content Strategy is a high scale approach deliberately aimed at competitive niches.

Instead of looking up the keyword search volume of a topic and writing about the most popular (highest volume) keywords first, you deliberately ignore the high traffic keywords because they’re a) competitive and b) typically not very high intent.

Instead, you take a broad approach, writing about every single low difficulty and low volume term you can.

Eventually, this traffic adds up (as well as being more specific and long tail, and thus high intent, traffic). When the traffic adds up, you have an audience. When you have an audience, you can leverage that to compete for some of the higher traffic terms.

This approach flips the typical prioritization model on its head, and I love it. You *do* need to go publish super frequently to make this pay off, however, as each low traffic topic is unlikely to make or break your traffic goals.

The Barbell Content Strategy

The Barbell Content Strategy is a riff on a financial portfolio allocation method popularized by Nassim Taleb.

To both cap your downside as well as participate in unpredictable upside, you have two baskets of assets sitting at the extreme of the volatility distribution (nothing in the middle). You want a large percentage of very safe and predictable assets and a small basket of extremely volatile assets.

In the context of content marketing and blogging, the two baskets might look like this:

• 80% Product Led Content – terms that are likely to drive both predictable search traffic and predictable conversions
• 20% Buzzworthy Content – creative topics that don’t have search volume, but may generate a ton of social traffic or backlinks.

The benefit of this strategy is you pay the bills with your Product Led Content while supporting your domain authority and audience growth with Buzzworthy Content. It’s a way to not only get the best of both worlds, but have each world contribute to the other through synergy.

If you’re interested in learning more about content strategy, my agency has a huge course all about this (mostly centered around the Barbell approach that we use for our clients).

4. Choose a content distribution channel

Your content strategy should inherently include a distribution strategy. For example, both the Wal-Mart Strategy and the Barbell Strategy above rely mostly on search engine optimization to get eyes on your content.

This isn’t the only channel that could work, though. You can distribute content through any social network, email newsletters, etc.

For example, Upworthy’s content strategy is what I call the “hit factory strategy.” it’s similar to Hollywood movies, in that each individual movie’s success is hard to predict and unlikely to be an outstanding success, but 1 out of every 10 movies is a massive blockbuster and pays for the rest.

In essence, it’s a strategy that is optimized for vitality (which is notoriously hard to predict). Virality, by its nature, is best facilitated with social networks.

This doesn’t work for every industry or type of content. But if you’re in health & wellness, for example, perhaps going viral on Twitter is the play. Or it could be creating infographics that are pinned thousands of times on Pinterest.

Whatever the case, you want to think about “where the fish are” and how you can reach them with content promotion. Otherwise it’s going to be difficult to get initial traction.

5. Write high quality content at scale

Got your topic picked, content plan in place, and a promotion strategy? Now it’s time to write!

Writing is hard. It takes time and practice.

I think blogging is most successful when you personally write your own content, at least at the start. Your voice is going to be a big differentiator, and hiring anonymous freelancers and ghost writers is going to be less effective in most niches. Unless you’ve got a strong link building component built in, but I’ll cover that in the “promote your content section.”

So in the beginning at least, write yourself, put your name on it, and write as much as you can.

Set aside a time during the day when you have to write and pick a quota for word count. I do an hour in the morning and write 1000 words a day minimum, still to this day. I also never hire ghost writers to do content under my name on my blog. It’s important you hear my voice when you’re on alexbirkett.com.

I have recently started hiring writers to help me scale content, however.

I’ve been able to do that for three reasons:

• I have a high enough domain rating
• I have very clear monetization paths
• I know exactly how to hire, vet, onboard, and train writers to produce near perfect content with little back and forth.

Unless you can do those things, I recommend writing yourself, at least until you’ve hit the initial traction stage (a few thousand visitors a month, usually).

6. Promote your content

Promoting your content is going to depend on your content strategy and promotion plan.

90% of content strategies and clients I work on rely on link building. Therefore, I’m trying to set a link quota each month, and I have a variety of trusty tactics I use to get those high quality links. A few of those include:

• Guest posting
• Original research + blogger outreach
• Reciprocity and community link building

For our clients, we typically deliver anywhere from 2 to 12 links per month in their industry. For my personal website, I try to get 5 links per month. I try to aim links at the highest value posts, as well.

An easy way to get links, depending on your niche, is to sign up for HARO. You can get quote requests from lazy journalists and throw a backlink in.

Otherwise, I have to say, link building is a slog. It’s not easy, but it’s super valuable. Here’s a full guide on how to do it.

Link building is important because the higher the authority of your website, the easier it is to rank content (and links are the main signifier of website authority). The easier it is to rank content, the more predictable your traffic and revenue channels.

It’s like a flywheel effect. The bigger you are, the easier it is to rank stuff. So get started link building as early as possible.

Other popular forms of content promotion includes social media and virality optimization. A new and effective way to promote content is to do community building and community content promotion. Basically, find a Slack group, LinkedIn Group, Facebook group…whatever…join it and become a genuinely valuable contributing member.

Eventually, you’ll build up the trust to share your content there and the people will love it and amplify it (unless it sucks – so write good content).

7. Map out conversion points in your content

Finally, we’re going to pick where and when to trigger monetization points in your content.

For the vast majority of blogs, your best bet is to get people to sign up for your email list or newsletter. It’s just too hard to drive direct purchases, unless you’re just dropping affiliate links (in which case, just drop as many as you can in relevant places).

“The money is in the list,” they say. Email is powerful because it’s an owned channel and you’ve got permission to send messages. You can build up trust over time, segment your list by behavior and lead quality, and sell different products depending on different buyer’s journey stages (customer lifecycle optimization).

The *how* of implementing these points is tricky, which is why I’ve written an entire guide on how to capture email leads. Some easy low hanging fruit, though:

• Create lead magnets / content upgrades that are related to your topic. Gate them and require an email.
• Use exit intent popups to trigger email capture forms
• Use a sidebar popup form to sign up for your list
• Use in-content forms to unlock a premium section of the content
• Have a “subscribe” page that is easily found on the top navigation bar.

There’s a whole art and science to collecting email leads called conversion rate optimization. You want to use data to inform how you get people to convert and run experiments if you’re able to.

Before you do any of this, though, focus on getting tons of traffic (probably 10s of thousands before you start testing different offers at scale).

8. Measure, optimize frequently

As I mentioned, when you get to a certain scale, you want to be optimizing continuously. The only way to do that is to properly instrument your data and measure the right things as you grow.

I’ve written a whole post on content marketing analytics. Here’s the shortest possible summary:

• Use Google Analytics
• Set up goals
• Ask good business questions and use analytics to help you come up with hypotheses or answers

It’s better than gut feel or guessing!

18 Ways to Monetize a Blog

Alright, now that we’ve covered the fundamentals of how to monetize a blog (starting with how to build the blog part of it), let’s cover the things you can sell.

Realistically, you’re only limited by your own creativity when it comes to using a blog to make money.

However, there are clearly some more popular and effective ways than others.

Here are 18 popular ways to monetize a blog:

1. Start a real business, you slacker
2. Dropshipping
3. Affiliate links
4. Sell courses
5. Sell ebooks and other digital products
6. Sell actual physical products (start an ecommerce store)
7. Offer coaching and consulting sessions
8. Start an agency
9. Partner with other agencies
10. Build a newsletter
11. Build a community
12. Organize events
13. Take sponsored posts
14. Accept donations
15. Create premium content behind a paid gate
16. Start a podcast
17. Create paid directories
18. Sell ad space

1. Start a real business, you slacker

*Scratch the record*

Stop looking for get rich quick schemes and make something people want. Add value to the world, charge for it, and you’ll make money.

Then just create a blog that builds awareness and a funnel for those products.

It’s easier than ever to start a business, and we still need more innovation and entrepreneurs. Instead of trying to “make passive income” or “make money in your pajamas” or whatever, put on Edison’s overalls and do something worth doing.

*rant over*

2. Dropshipping

Dropshipping is when the seller accepts customer orders but does not keep goods sold in stock. In many ways, it’s similar to affiliate marketing in that, you’re basically a top marketing layer for someone actually making the products you’re selling. Your job, as the blogger, is to get attention and sell things. You don’t have to make those things, you just partner with someone who does.

The only real difference between drop shipping and affiliate marketing is that you can’t set the price with affiliate. So you get slightly more control when you dropship products.

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Here’s a huge guide on how to find dropshipping suppliers from Shopify.

3. Affiliate links

Selling affiliate products is almost certainly the easier monetization model to understand. You sell other people’s products to your audience using a unique link to identify and attribute the sale to you.

Most people do this through email marketing or through SEO, but you can also monetize with affiliate using YouTube, Clubhouse, podcasts, or basically any form where you’re speaking to an audience.

It’s basically like paid word-of-mouth. Affiliate marketing, then, tends to be most effective if you’ve built a ton of trust with your audience and people genuinely want to hear your recommendations.

This would make someone like Tim Ferriss or Oprah or Joe Rogan the affiliate marketing king. Anything they mention on their podcast is going to have a crazy spike in sales.

Once you know where to look, you can find affiliate links all over the internet. For example, just search “best [product name]” and click on a few listicles. Here’s an article that ranks for “best cms software” where every link on the page is an affiliate link:

Sometimes bloggers will have specific resource sections on their website where they recommend their favorite products. Nomadic Matt, for instance, has a section where he recommends his favorite credits cards and other travel resources:

Sure enough, each link here is an affiliate link for the given credit card he recommends:

Anyway, affiliate is probably the lowest friction way to get started with blog monetization.

You just sign up for the affiliate program for the product you want to recommend, and then you use their unique link when you mention the product. Amazon Associates is probably the most popular program, though they’ve recently slashed their affiliate payout rates, so it’s harder to make a real amount of money through Amazon now.

I use affiliate links on this site. I’ve also monetized cupofkava.com using affiliate links. Tons of my friends are affiliate bloggers and some have even added on affiliate sites to real products/SaaS companies to increase their revenue with no downside.

One tip: recommend products genuinely. It’s difficult to build up trust, and trust is the most impactful dimension when it comes to conversion.

4. Sell courses

I said I didn’t have a course to sell you, but I do have a course, and I do monetize it (mostly indirectly) through my blog.

It’s about content strategy.

Obviously if you’re coming to read my blog or listen to my podcast, where I talk about content strategy, a course to follow up and dive deeper is a good product.

Online courses get a bad rap due to bullshit info-marketers, but if you have genuine and specific knowledge (and you almost certainly do), you can create a course.

I will warn you, however: it takes a massive amount of time and energy. We poured our hearts into our course and just the content creation portion of it took several months to put together.

Now, however, we have a ton of content we can use in different forms and in different places (for example, we’ve taken small sections of our lessons and repurposed them into lead nurturing flows, mini-email courses, and blog posts).

But don’t launch an online course thinking it will be easy money. It’s hard work, and it’s a highly competitive space.

5. Sell ebooks and other digital products

Ebooks are almost always used as a free lead magnet, something that you can gate and use to collect an email address.

However, in some cases, you can use ebooks, templates, videos, or other premium content as an actual blog monetization method.

For example, Kaleigh Moore is a freelance writer and sells templates to help writers and editors work better together, templates to help you write better, and templates to help you become a better freelancer:

Nomadic Matt also sells digital guidebooks on different travel locations:

6. Sell actual physical products (start an ecommerce store)

Due to the ease of self publishing, you could also just as easily sell physical copies of your book. Nomadic Matt also has a few physical books he wrote for sale in his blog store:

There’s also the option – albeit, a difficult one – to start a tried and true, direct to consumer ecommerce business. Make your own products!

Like Pique Tea. They sell tea:

But they also have a blog.

The thing is, you’re unlikely to solely grow an ecommerce store through a blog. But most ecommerce stores underrate content in the marketing mix. Therefore, if you know how to drive traffic and conversions with content *and* you have a real product that people love, you’ll be in a really good place.

7. Offer coaching and consulting sessions

When I first started my blog, I initially just offered freelance writing services and 1 hour consults. I still do offer limited 1 hour consulting sessions:

This is one of the easiest things you can do, especially if you’re a solo blogger or a subject matter expert.

If you run a dog blog, offer consulting sessions on how to train your dog. If you run a content marketing blog, start doing consulting for companies trying to learn about content marketing.

Another famous move is to grow your blog and then simply teach people how to grow a blog. Meta, but effective (example from my friend Ryan Robinson):

8. Start an agency

Next step up from solo consulting and training is to start an agency. An agency is a great revenue stream and is a great way to scale out your own individual subject matter expertise. Of course, it requires a totally different skill set than just the domain expertise.

If you run an agency, you have to learn how to do sales, how to do client management, how to hire and train employees, how to upsell and expand your accounts, etc.

It’s a lot of work, but honestly, it’s super fun (I run a content marketing agency myself).

A good way to determine if this is a viable revenue stream for you is if you’re getting too many consulting requests to handle on your own. Once you hit that breaking point, it’s time to partner up or hire people to help you run your services. When that happens, you’re technically an agency.

My agency, by the way, is now the primary way I monetize my own blog.

9. Partner with other agencies

If you don’t want to start your own agency and go through the hassle of the paperwork and the client relationships, you can just partner with other agencies and refer people out to them.

This is sort of like a hybrid model between building an agency and doing affiliate.

Shocker, I also monetize my blog this way. Here’s how:

While I have a content marketing agency, most people follow me for my articles on A/B testing and analytics. This means I get tons of requests for consulting with conversion rate optimization, experimentation strategy, or data. Instead of just turning them down, I’ve partnered with an agency in each niche, and they give me a 30% kickback if they close the referral I send to them.

Because these deal sizes tend to be quite high ($5k-$15k), the kickback is pretty sweet.

Here’s the real key: I only partner with agencies I absolutely trust 100%. Otherwise I’m playing with fire regarding my own reputation, and that’s something that I just won’t do. If I hear from someone that my referral sucked, I’ll immediately chop them and get a different agency in my roster.

10. Build a newsletter

Newsletters are a popular way to make money online now, but really, paid newsletters have been an effective way to make money for a long, long time (one might even call them a “newspaper” or a “magazine”).

This is a massive topic, mostly because of high profile exits for newsletters like The Hustle to HubSpot, and because of Substack’s success (and controversy).

Suffice to say, newsletters rock. Since you’re producing content already, the “conversion” is obvious: sign up to get more content. Once people are getting more content for free, you create a premium version of your offering and gate that only to paying members. Some small percentage will subscribe to the premium offering.

So the name of the game here is twofold:

• Grow a massive top of funnel with free content
• Build trust and provide truly great content

Those are the only real ways a newsletter can work. If you don’t do the former, the numbers will never work out in your favor (a very small percentage of people will become paid subscribers for content no matter what industry you’re in, so you need a lot of overall people). If you don’t do the latter, no one will pay for your content.

Great examples of paid newsletter businesses:

• Stratechery
• The Hustle / Trends
• The Agora
• Any top Substack creator

11. Build a community

The next step up from a newsletter is a paid membership community. This is the holy grail of blog monetization, and indeed, many blog platforms are baking in this functionality nowadays (e.g. if you have a WordPress blog there are a ton of plugins you can use to create membership sites).

If you can get people to sign up for a community, you’ve done something incredible. A community is a flywheel if you can keep it well moderated. Essentially, your cost of blog content goes down as your community members begin to create their own user generated content.

It’s also a subscription, so you get nice predictable revenue, unlike Amazon affiliate marketing or even ecommerce sales (which tends to exhibit strong seasonality).

Nomadic Matt runs a community for travelers and travel bloggers:

Traffic Think Tank is a community for SEOs and content marketers:

While creating and organizing a community will never be *easy*, it is definitely the best time ever to try. The tools available make it so easy to set up and maintain, at least from a technical standpoint. Hell, I know personally many communities that are just printing money by selling access to private Slack groups.

You just need to find or build a tribe of tightly connected individuals in a given niche. Product Marketing Alliance is a good example of this:

12. Organize events

Online communities organize tribes digitally, but there can also be a lot of money to be made in organizing people physically through conferences and meetups.

This is how The Hustle initially made money, launching Hustle Con conference:

Product Marketing Alliance also monetizes through physical and virtual summits and events:

13. Take sponsored posts

I get a million requested for sponsorships and sponsored content on alexbirkett.com. I’ve never taken one and I never will:

But if you’re ever struck with the realization that, “hey, I don’t give a shit about my readers or putting out good content, and I’d really like to monetize my blog using the least lucrative way to do it,” then you should look into taking sponsored content.

If you go down this route, good luck. Your blog is now on a slow path to obscurity.

I’ve never seen a piece of valuable content that needed payment to get placed. If someone is paying to place their content, you can guarantee it’s total dogshit and doesn’t belong anywhere outside their personal diary.

But if you want to do this, you do you.

14. Accept donations

I rather like the idea of taking donations. I donate to a few Patreon accounts and I consider my Substack payments a sort of form of donation to writers I like.

I also donate from time to time to creators I really like, such as Sam Harris or WaitButWhy (who solicits donations on his website):

It used to be cool to have a button that said something like “buy me a coffee,” and the option to give a quick $5 donation.

This is obviously not going to make you rich unless you have a genuinely huge audience. But if you’re producing amazing content, it’s cool to give people the option to say thanks.

This is basically the whole Wikipedia model, no?

15. Create premium content behind a paid gate

Instead of creating a site to sell online courses or community membership site or even a newsletter, you could simply gate content on an a la carte basis and allow for quick ecommerce style payments.

Imagine you write about Google Analytics. Most of your content is probably 101 level, perhaps you dabble in intermediate content like setting up custom dimensions or using the DataLayer with Google Tag Manager.

But every once in a while, you have a piece of truly valuable content. Perhaps it’s a tutorial on how to do something very specific or an interactive webinar.

In this case, why not through a $10 gate on the content? I’ve not personally experimented with this, but it could be a great way to drive additional revenue. It probably won’t be your full-time income and only way you monetize, but it’s a pretty frictionless way to add additional options to support you.

16. Start a podcast

I’m going to be honest, if you want to make a lot of money and you’re a first time blogger, a podcast is probably not the best way to do it.

I have a podcast. It’s got some listeners, but not many. You know why I do it?

• I get to talk to cool people and learn things
• The people who listen are high value and part of our target audience
• I can use the insights from podcasts to repurpose into blog posts and eventually a book
• I can use podcasts as an account based marketing channel

But I’m literally never going to make money from sponsorships or ad networks. Some, like Tim Ferriss and Sam Harris, are making a massive amount of money from podcasts that once were just startups. But you probably won’t.

Still, don’t let that deter if you really want to start a podcast. There are tons of benefits outside of making money.

17. Create paid directories

A great way to monetize a given blog is to become the de facto source or directory for people seeking resources.

The most obvious way to do this is to start a job board. ProBlogger did it. CXL did it. You can do it! It’s hard to hire. Make it easier for people to find and advertise jobs, and you’ll make money.

You can also do this with agencies, like Credo, who lists the best agencies in each vertical:

Curation is a major value add if you do it with integrity and high standards. Just don’t become a pay-to-play extortion site like Yelp or Capterra.

18. Sell ad space

Finally, the absolute worst option if you want to get rich: sell ad space!

Google Adsense and display ads. This used to be the most popular way to make money blogging. However, in 2021, no one clicks on display ads. So unless you write click bait content and have millions of visitors, you’re probably going to make peanuts.

If it doesn’t hurt your UX too badly, you can add it on as an additional revenue stream. But it’s probably not going to let you quit your day job.

Conclusion

Making money blogging is actually pretty easy. If you write high quality content, tap into your target audience, and have at least one or two ways to monetize your expertise, you can make a good side income or even a stable full-time income.

On the extreme, I know bloggers making millions per year. This is not super common so don’t let them sell you hopes and dreams.

The most likely winning scenario: pick a topic you care about with a sizable community, start small and build up a little audience, and monetize with highly active methods (consulting, courses, etc.).

As you build a broader and bigger audience, then stuff like community, affiliate, ecommerce, and ads can start to pay off.

But honestly, it’s easier to be a small giant when it comes to blogging.

Whatever you choose, good luck! And let me know if you want help, because I’ve got courses, an agency, and some affiliate links I can send you

The post How to Monetize a Blog (8 Steps + 18 Tactical Methods) appeared first on Alex Birkett.

“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.

2018 Was a Good Year (Recap)

2018 was an absolutely wild year of exploration and new experiences.

Travel

I traveled a ton, hitting 5 new countries (Portugal, Peru, Mexico, Czech Republic, and Austria), like 10 foreign countries overall (all the aforementioned plus Canada, Spain, the Netherlands, and Ireland twice), and many new states as well (weirdly enough, I checked off Arkansas from the list and had a lot of fun there).

I spent about half of my time in Austin and the other half in other places. This was both exhausting and exhilarating.

Hobbies and Personal Development

I continued learning Spanish, and I hit my goal of testing at a C1 advanced level. I now feel confident speaking Spanish with just about anyone, and I feel a level of conversational fluency that I’m pretty proud of. I dipped into learning German towards the end of this year, but I haven’t made massive improvements. I’m still not conversational by any means.

I’m still at level one in Krav Maga, but that’s mostly due to me being on the road every time there’s a chance to test up to the next level. The next level test is in February, and I’m pretty confident I can get to level 2 at that point. I’m stoked that I have now regularly (twice per week) practiced Krav for over a year now.

I surfed for the first time (in San Diego) as well as many more times after that (in Portugal). Unsurprisingly, I love surfing and hope to do much more of it. I also feel blessed with my snowboarding opportunities this year – I got to do both Colorado and Vermont.

I also stepped way the fuck outside of my comfort zone and took a 101 level improv class. This was wildly fun and beneficial (and definitely still scary).

Health

One serious new addition to my life is a regular yoga practice. I go to semi-hot yoga (I think it’s at 90 degrees) at Black Swan Yoga in Austin almost every day of the week, and it’s become an almost therapeutic part of my day. Plus it’s the perfect counterbalance to the weightlifting and martial arts I regularly do.

I still meditate every day, write in my daily stoic journal, and do morning Spanish lessons and Duolingo. I try to eat whole natural foods but fail a lot (mostly due to travel), and I don’t beat myself up over it too much.

Relationships

I don’t want to dive too deeply here on a public blog post, but I’ve got my own notes here and the summary is: things are good. I’ll say I sometimes neglect existing relationships in favor of professional development and work, travel, and new connections, but not to the detriment of the relationships. Just something to keep an eye on moving forward.

Career

I got promoted at HubSpot and have learned a ton more about SEO over the past year. The work is still exciting, and there are plenty of fascinating projects in the works now and coming up in the near future – many dealing with technical skills and data science, which are my core professional interests.

In the area of technical skills, I probably slowed down my education more than I would have liked. Urgent priorities can cause development related work to fall by the wayside. But next year, I’ve made it a point to continue learning technical skills, in particular data analysis/data science, even if it’s necessary to do so outside of work hours.

However, despite not learning as much as I’d have liked, I’ve made modest progress into a “Statistics in R” program through Coursera, and I’ve got to pick up some Python skills through some technical SEO + scraping projects. I also get to learn new skills working with CRO & customer acquisition clients on the side from time to time.

I have learned a ton about creating motion and impact in a big organization, though. Before this year, I only worked at startups where teams were small, hustle and scrappiness was the name of the game, and if the data suggested something was worth doing, we usually just launched into it (no hoops to jump through). By nature of the size and complexity, it’s not as straightforward at a big company, so it takes more emotional intelligence to get buy-in for your ideas and to spread them through the company. I’m still working on this, but I’ve gotten much better.

Personal Brand & Professional Development

In the broader marketing world, I got to speak at a few conferences. I did many online events like Conversion World and CommerceNow, but the most exciting event for me was probably Conversion Hotel. It’s an event on an island called Texel that is off the coast of the Netherlands and it’s filled with conversion nerds, my crowd. I got to do a panel with Justin Rondeau, as well as moderate some Q&A and do a very interesting late night (230am) Pecha Kucha session. A wild an awesome experience!

I wrote down a goal of 10k monthly visits to my blog. It’s really around 2k, but I’m alright with that. It’s difficult to set aside time to write the caliber of articles I’m trying to write, but I’m proud of what I’ve put out this year, and I’ll do more next year. I’ve already got a few articles that are almost finished that I’m super stoked to launch.

Conclusion

Every year is better than the last.

2019 Will Be Even Better (Goals)

2018 was largely a year of new experience – travel, surfing, trying out new skills, meeting new people, etc. While that will likely never change due to my personality (very high on trait Openness as well as Extraversion), I’d like to have a “quieter” 2019. Doing less, but doing it better, and focusing my time and energy on things I already know I really like. Essentially, instead of pointing my energy outside, I want to spend more of it focusing inward.

Career

I want to deeply focus on two areas:

1. Technical skills, largely focused on data science areas (python, statistics, R, etc)
2. Communication skills (continued writing focus, but next year a deeper focus on speaking/presenting)

Personal Branding

I planned to speak at ~4 conferences in 2018, and I suppose I hit that (depending if you count online events).

I actually don’t care how many I speak at next year, but I want to continue speaking and sharing my experience and knowledge. I’ve got two exciting ones lined up already for the new year – a startup event in Tartu, Estonia and a growth marketing event in Kiev, Ukraine. I also want to continue attending as many data, growth, and CRO events as I can. So I’m pretty much saying Yes to all of those. I’ll probably go through Toastmasters or something to hone up my skills a bit, as I’m pretty much a rambler when I speak.

Another piece is I actually do want to focus more on my personal blog next year, mostly because I have a backlog of ideas and info that I really want to publish. It’s just up to me to put aside some time to do so. I’d like to hit 10-20k traffic per month, but more than that, I just want to publish good articles that people bookmark for later.

In general, I want to publish 50+ articles in 2019. These could be guest posts, personal site articles, or HubSpot posts. But it’s important that I keep writing and putting together my thoughts in that format.

Personal Development & Hobbies

This is a mixed bag of things I like to do and want to do more of and get better at…

Spanish: continue taking group lessons twice per week and 2+ official classes per month. I also have a weekly Spanish call with Svitlana Graves and I hope to travel again to South America (hopefully Colombia) this year and immerse myself again. If you’re interested in doing Spanish calls with me, hit me up

German: it’s going to be a challenge juggling two languages, but I’ve already cracked into German, and I’d like to get to a B2 level by the end of 2019. This is going to be pretty difficult, but I think possible, following the same process I used to learn Spanish.

Martial Arts: level 2 Feb 23, 2019, and continue classes after that. In 2019, I’m going to start testing the waters with BJJ/ground fighting.

Reading: It’s hard to attribute causality to any one variable, especially in the messy real world, and particularly in absence of the ability or desire to run a controlled experiment. That said, reading has probably been the biggest positive lever in my life, in making me successful and happy.

I usually do 50 (or at least 30) new books per year, and I’ve been doing that for 5+ years now. Next year, I’m going to try something new: I’m only aiming for 10+ books and am focusing on re-reading my top all time favorites. This is to double down and relearn from things I’ve already taken value from, such as NN Taleb’s books, F Scott Fitzgerald’s masterpieces, Meditations, Radical Acceptance, and more.

Basically, I’m only going to read very technical books or fictional/spiritually rewarding books, no middle ground of feel good + feel productive pop business lit. In the spare time I’ll carve out here, I’m going to dive deeply into technical training in Python, statistics, and R, and work on the skills I like learning (languages, martial arts, and the new ones below, basically).

New skills: I still like learning new things, but in 2019 I’m going to bring it back and pick up old skills that have faded a bit:

• Poker – my grandpa taught me how to play when I was really young but I haven’t played in years. I loved poker, and it goes together really well my love of decision theory, probabilities, and uncertainty. I’ll start slowly, playing with friends and shaking off the cobwebs, but I hope to join more serious clubs before the year ends
• Salsa dance – I took a salsa dance class on a whim in college. I sucked at it but it was really fun, and eventually I was okay at it. I’m going to look for a class here in Austin to join, hopefully meeting weekly.
• Music – Music is pretty core to my identity but it’s fallen to a footnote in my life, I think largely because there’s no “end” to the means of playing guitar. It’s not helping me in any pragmatic way, it just makes me happy (that’s all!). That’s the biggest reason I’m picking up the guitar again in 2019 and setting the goal to play at one open mic. I figure once I do one open mic, I’ll want to do more of them, so I’m making my goal an easy one.

As I said last year, for leisure I again want to place a premium on outdoors activities, particularly kayaking, surfing, snowboarding, and hunting/fishing. No goals here, just something I always want to do more of.

Travel

I want to travel less often overall, but I still want to travel a lot (if that makes sense). I basically want to travel for two purposes:
Business (conferences, retreats, masterminds)
To assist other goals and focuses here (yoga retreats, well chosen historical interests, language learning etc)

Basically, I want to do less hedonistic Euro-city hopping – which is pretty much just drinking local beer and wine in foreign places & seeing museums – and more meaningful travel.

I also love spending time in Austin and want to do more of that, particularly because I have activities like Black Swan yoga and martial arts that I want to do more often.

Relationships

Spend more (high quality) time with fewer people. Less networking and bar hopping and Bumble, and more time building on the foundations I’ve got.

Health

It’s all about the yin and yang, in terms of exercise and activity:

• Yoga + Weightlifting
• Salsa Dance + Martial Arts

And all I want to do outside of that is follow a reasonable diet that lets me feel energized all the time. Per usually, this is a paleo-esque diet with mostly veggies, meats, and water, with lots of supplements as well.

Conclusion

I’m excited for 2019. Every year has been better the last so far in life, and I expect as much moving forward.

Ironically enough in a post about the future, I’d like to spend more time in the present moment in 2019. To stop worrying so much about the past and future and just enjoy and focus on what I’m doing in the moment. This goes for everything, from fun hobbies to personal relationships to work projects. I know where I wanna go, now if I could only put my head down and enjoy more of the journey

The post 2018 Recap (and 2019 Goals) 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.

Anyway, you know it’s important or you wouldn’t have found your way here.

The way most people go email capture it is pretty rudimentary: throw up a popup with some seemingly tempting offer, and let the chips fall where they may.

Upon first glance, email capture seems straightforward, with little wiggle room. However, there are really endless possibilities for experimentation and creativity. Actually, I believe there are so many different ways to go about email capture, that it’s a bit overwhelming.

So, to help myself set up some parameters when auditing or optimizing an email capture program, I walk through these questions:

• Who?
• What?
• When?
• Where?
• Why?
• How?

This is usually referred to as the Five Ws (or the Five Ws and How, 5W1H, or Six Ws). It’s commonly applied in journalism, though also in other inquisitive endeavors such as research and police investigations. I believe it can help you to set up an email collection program, but it can also help you audit an existing one and improve it. Without a guiding framework, it’s easy to get lost in millions of tactics, or worse, never know where to get started at all.

All that follows can be applied across industries – SaaS, ecommerce, personal blogs, etc. The specifics may be slightly different, but the game is the same. Emails are valuable for everyone, after all.

Who: Defining Your Target Personas and How to Reach Them

Sales people talk to customers. Customer Success talks to customers. But marketers don’t usually talk to customers. No bueno.

This is a shortcoming for many reasons, but for a concise argument, it’s because “who” you want to target helps you answer the rest of these questions. It all starts with the customer.

This “who?” question branches off in two directions:

• What is our target audience like (how can we model our target customer)?
• To whom will we actually show an email capture form?

The first question is a broader one; it affects every part of your marketing.

I know there’s a lot of bashing around personas, but it’s mostly because marketers have ruined them. The modern “persona” is almost a parody of itself. They’re created with no data, they include irrelevant or useless information, and they’re given silly names like “Meticulous Melvin.”

They are to marketing what the cheesy stock photo is to web design: a lazy placeholder for something that should actually have value.

All that aside, personas hold lots of value if you do them right. They’re a representative model – not 100% accurate, but an actionable approximation – of your target customer that you can use for various product and marketing decisions.

This is no place to dive into what I consider to be a good user persona creation process (summarized: use real data instead of made up stuff). But you should read this CXL article on the topic.

In general, before you create email capture offers, do some research on your audience and find out what they may actually respond to. It will save you tons of time and frustrations.

The second branch here is more local: to whom will you target your email capture form? You can choose to target offers based on:

• Traffic source
• Referral source
• URL/page targeting
• Number of pages views
• New vs. return visitors
• Mobile vs. desktop.

If you’re a Google Analytics user, this information could be found in both the “Audience” and “Acquisition” sections of your dashboard.

Now, the most basic implementation of this specific audience targeting is “everyone.” This is probably unsexy to personalization advocates, but oh well – you save on a lot of complexity by just throwing a static form on your blog asking people to subscribe. Most sites have some sort of static subscription mechanism like that:

When you do start running some A/B tests on your email capture forms – or at least looking into your historical content marketing analytics data – you may find that some audience segments are responding better or worse to different offers. This is when you might want to look into audience targeting.

Most popup tools you’ll use offer this sort of thing out of the box, at least with basic rules like device targeting (mobile vs. desktop) and URL inclusions or exclusions.

You can also build these rules out in a tag management platform like Google Tag Manager, if that’s what you’re using to fire your lead capture tools.

You can get pretty complicated with this stuff, but I always try to keep it simple, as complexity carries a management cost. On my own site, I basically just target all desktop users on their first visit (and their next visit afterwards, after a period of 2 weeks), after scrolling 50%.

I also have a few static forms on my site that everyone sees. There’s no special targeting.

It doesn’t need to be this simple though. For instance, when I was at CXL, we aligned several offers with different content categories, depending on the problem it solved (enterprise CRO program building, A/B testing ebook, CRO mastery guide, etc.).

HubSpot has a million content offers depending on the content topic, the blog where it lives, the desired conversion pathway, etc.

While I said your “who” is your starting point, in reality, it’s something that you’ll definitely learn more about after you create email capture forms and get data rolling in. No matter the pretty picture we paint with our personas, reality usually tells us the situation is different. As Mike Tyson once said, “everyone has a plan until they get punched in the mouth.”

In other words, analyze the data once you have it; it can help you learn which offers convert better or worse on which pages and with which audiences.

This stuff is quite easy to model out at a basic level, and you can get an excellent look at user intent and how well your offer is aligned. Just line up all the associated impressions and conversion rates, and see which ones are lagging:

As I showed in my article on content optimization, I like to model out projects based on the assumption that we could possibly bring every one of these up to the average conversion rate.

To do that, just calculate the average conversion rate (=AVERAGE(E:E)) and put that in a new column.

Multiply the impression count in column C by the average conversion rate, and you have a feasible goal that is hypothetically attainable. You can then put some conditional formatting on them to isolate only the potential uplifts greater than zero (i.e. posts that have a below average conversion rate and could therefore improve if you brought them up to the average).

Then you can project out which email capture locations would bring the most value if you focused on optimizing it.

Note: when you do a report like this, it doesn’t necessarily mean that an offer or targeting is under-optimized for a page; it may just mean the page and the traffic it brings has low or now intent to sign up. I find this is a worthy heuristic, however, to explore optimization opportunities.

Sometimes, I lament, you can tweak and optimize a page forever for marginal or zero gains, and you’re better off simply moving on to “warmer” traffic.

You can also spin through a few custom reports in Google Analytics to weigh out which segments seems to be responding better or worse. A super common and easy one to start with is targeting by device. It’s probably the case that you should be targeting mobile and desktop users differently, especially with email optins:

Intuitively, ask yourself, what audience or acquisition segments would make a difference or matter in terms of what offer they see or when they see it? Ask those business questions, and then dig into your digital analytics data to see if there truly are any meaningful discrepancies between segments. Then use that to form a hypothesis driven experiment, where you can maybe eke out some additional email captures.

No matter what route you choose as to whom you target, just make sure that’s it’s something you truly consider before throwing up some whack, generic popups. This often goes overlooked, but user intent and who gets your offer is just as important as what your offer is and when you deliver it. In fact, it’s difficult to craft a good offer if you don’t understand who you’re targeting.

What: Aligning the Offer with your Audience

I’m wading into murky waters with this one, because it’s still a problem I’m working on, struggling with, and chipping away at bit by bit.

You know your ideal audience. You have defined parameters for your audience targeting. You have some idea of what you do with email subscribers and/or leads as soon as they opt-in.

Now what the hell do you offer them in the first place?

Let’s back up a bit first, and define the basic stuff. What I’m really talking about here is sometimes called a “lead magnet.”

A lead magnet is an exchange of value for information. It’s the promise of an ebook, an email course, a quiz result, a discount, or just regular content updates, in exchange for an email address and potentially other personal information.

In this step, then, we’re talking about maybe the meatiest part of lead generation: your side the of the bargain. What are you offering this anonymous stranger in exchange for their kind offering of their email address?

As it turns out, this is a really hard problem with multiple dimensions:

• What format should your offer be (PDF, video, web content, other)?
• Do some formats convert better than others? Do some contribute to greater down funnel conversion rates (product signup, purchases, upgrades, etc)?
• How do you determine which audiences get which offers (if you’re doing different offers at all)?
• What formats produce the best qualified leads?

There are a million questions here, and seemingly no universal answers.

The best thing I can do here is give two insights that I’ve learned along the way:

• Learn, to the best of your abilities, about the user’s intent and match your offer the best you can.
• Continually update your beliefs and offer alignment based on what the data tells you.

I recognize that can sound vague taken solely as palabras, but I’ll try to get you an example or two to illustrate.

Learning about user intent

How are users coming to your page? If you don’t know that, head over to your Google Analytics account and go to Behavior > Site Content > Landing Pages, and then set up a secondary dimension of “Source / Medium.” This, at a high level, will show you how people are arriving at your site.

Let’s pretend you’re setting up a content offer / content upgrade for a blog post of yours that gets a lot of traffic. Most of the traffic comes from organic search. What to do? Look at the keywords that it’s ranking for (that are presumably bringing visitors in).

In our hypothetical case, we’ve got a page addressing the safety concerns of CBD oil. Here are the keywords it’s ranking for:

Now, candidly, we may not have needed to go through this process to get to the user intent, but it’s such a fast process that I figure, “why not?” And you might learn something new, like finding out a ton of traffic may be coming from a term you didn’t even know you ranked for.

In any case, knowing that people come to the site searching “is cbd safe,” and “is cbd oil safe,” we can cater our offer with this knowledge in mind:

• Maybe we offer a beginner’s guide to CBD oil dosing safely
• Maybe we offer a 10% discount off their first CBD order (if they order today!)
• Maybe we offer them a fact sheet on the health benefits of CBD
• Maybe offer them a quiz or survey that rates their CBD knowledge

There’s no right answer here; it’s something you have to consider in each individual case, stake out a rational strategy to get started, and then test and optimize with time.

Something of interest with all of this talk about “aligning for user intent,” is that there may be a good programmatic way to do this when you’re doing keyword research. IPullRank wrote an excellent post covering it (it’s quite technical). I’ve fought my way through about half of the process, so I can’t speak completely to its efficacy yet, but it seems quite cool.

If you don’t want to learn R and Python, though, you can do what most people do when aligning content and keywords to user intent: just eyeball it and make a gut decision. It’s usually going to be pretty close to accurate.

Or, let your creative juices flow. This is actually the part of the process where you get to have some fun, and most marketers don’t take advantage of it.

The world probably doesn’t crave another ultimate guide ebook; do something weird and attention grabbing. Offer a free vape pen with their first CBD oil if they order in the next 25 minutes (and if they tell you their favorite 90s music video). I don’t know, I’m riffing, but I think it’s fair to say that you’re not going to break down any barriers by swimming in the red ocean of the millions of ebooks and webinars out there.

Look at the data and adapt based on what you learn

Here’s the important part: just because you’ve looked at user intent and decided on an offer doesn’t mean it needs to say like that forever. Look at the data and adapt.

One thing I’ve worked on at HubSpot is “historical blog optimization.” We take a bunch of high organic traffic blog posts, reconsider their conversion paths, and try out new CTAs to see if we can get any wins. The interesting thing? The conversion rates are usually super variable, even though all the posts, in my mind, seem to be similar intent.

I wish I could show you actual data, but I’ll just make up data that looks really similar to show you what I mean:

This may look trivial – conversion rates vary, obviously – but it’s more surprising when you consider that, at least in my mind, all of these posts were super similar intent. They had similar keywords, were written about similar topics, and were published on the same company blog. I put the same CTA that lead to the same landing page, but got such different results.

The average conversion rate that your tool will likely spit out on reports, in this case, doesn’t even matter that much. One post brought in a .06% conversion rate, while two were in the 2.8% range. That’s so different!

Your results may look different, but I highly encourage you to pull these numbers, if for no other reason than to learn that the same offer and same conversion path can have much different results depending on the page. From here, you can move on and attempt to optimize individual pages and offers (again, my post on content optimization).

A quick example of an action I would take on this information is the following: let’s say I put a bunch of product CTAs on a bunch of blog posts. They lead you right to a product page, where you can sign up free. It’s higher intent than a related ebook, but lower intent than requesting a sales demo.

If I then go back and see that some posts are converting very well, I leave those alone for the time being.

But if i see that some posts are converting super low, say two standard deviations lower than the mean, I’ll consider swapping the CTA out for something lower effort – for example, an ebook on “email productivity.” Perhaps I’ll try to go for a simple email subscription instead of an actual product sign up or even an ebook signup.

I’ll usually play with offers on only the highest traffic posts, since that’s where you’ll see impact.

Sometimes, you’ll find out, the user intent on the page is just too damn low or irrelevant to craft a compelling offer. For example, if you wrote a post on “59 ways to increase your Twitter followers,” but you sell car insurance, there may not be a ton of ways to capture those emails.

If that’s the case, I find, it’s best to move forward on net new content and offer creation. Also, reconsider your content strategy and stop playing to vanity metrics like page views.

When: Beyond Simple Exit Intent Popups

When does your offer fire? This is where we talk about one of my favorite topics: behavioral targeting.

Behavioral targeting is just what it sounds like: delivering a given experience based on behavioral indicators (as opposed to demographic, psychographic, etc.).

It’s a broad term, but through lots of good work by companies like BounceX, behavioral targeting has mainly become associated with conversion optimization.

Even more specifically, it’s usually known now as mouse and scrolling behavior on a website.

The most common example of behavioral targeting is probably the exit intent popup. I’m going to go to GrowthHackers.com and click on a random post, and it’s almost certainly going to have an exit intent popup. Watch this:

First try! It’s super common, at least in the marketing space.

Another common one: scroll depth triggered popups. That’s how I’ve got mine set up. It triggers when you’ve scrolled 50% of the way down a page:

Pro tip: set up scroll depth tracking with Google Tag Manager. It’s super easy to do and you can then see how far most people are scrolling down on a given blog post. Your report will look something like this:

Only 324 out of 1081 hit 50% on this page, meaning perhaps I should consider a better triggering time in order to reach more of my audience?

Another common one: a popup upon first arrival. This is especially true in ecommerce, where you’re usually trying to quickly capture the attention of casual shoppers. Many stores use a discount offer to do so. This is an extreme example, but not uncommon:

Sometimes, your “when” doesn’t actually need to be explicit, active behavior like scrolling or moving your mouse to exit the page. Sometimes it can just be based on time on page. Often, marketers trigger opt-ins with some combination of all of these:

• After 10 seconds on site
• After scrolling 50%
• Excluding visitors from Hacker News
• Excluding mobile visitors

…And on and on. In my mind, it’s not so much the spread of your impressions but the accuracy of your targeting. The fewer uninterested or irrelevant people you can target, the better, simply because it’s a better user experience for everyone involved. Also, because you don’t want a bunch of unqualified and uninterested people on your email list. Read this CXL post on unsubscribing 83000 emails to learn why. More isn’t always better.

The best timing trigger, in my mind, is based on a behavioral signal that implies strong intent. For instance, if a user clicks on a link that says “download our free spreadsheet template,” there’s a lot more intent than simply throwing an exit popup with the same offer for everyone.

People usually call that a “content upgrade,” but it’s really just a prequalified click that triggers your form

Here’s a glimpse of one form of behavioral targeting I’m working on right now…

At HubSpot, we have tons and tons of “templates” blog posts. They cover topics like “sales email templates,” “follow up email templates after a networking event,” and “follow up email after job interview.” They get tons of traffic, and there’s lots of room to test out different conversion pathways and timing triggers.

Anyway, I’ve set up a test where, when a user copies text to their clipboard from a given email template, they get a message that tells them the message was successfully copied (kind of delightful, right?), and that we have a tool for templates, tracking, and automating emails (sell it!). It looks like this in action:

I think there’s a lot of creativity regarding the “when” of a content offer. I gave a few common examples and a somewhat more creative one here, but this is one area where marketers are continuously innovating. I think there’s a lot of room to optimize here, especially beyond the common “exit intent” and hit-you-right-away email popups.

Where: Placement and Real Estate

Where you place your email capture form matters a bunch, too. It’s hard to speak for specific websites, but Andrew Anderson, one of the smartest CRO people I know, had this to say about patterns he’s seen regarding split tests:

“Real Estate usually has a much higher beta and longer half life than copy changes. Spatial changes tend to be better than contextual changes for long term monetary value. Even in those cases you better be designing your efforts to see if that is true in this case and going forward.”

In other words, the space that website elements occupy on a page really affects user behavior and conversion.

Before you run off testing a million and one different locations for your email capture form, though, remember this CRO heuristic: meeting customer expectations is a simple best practice. Do what people expect and you’re most of the way there.

Users expect to navigate a site in a certain way, with the broadest categories branching out into specific filtering (e.g. Home > Category > Subcategory > Product). They expect clear, action driven CTAs, that accurately explain the next step. They expect lead generation forms to be in certain places on your site.

A few common locations include…

On the blog sidebar:

Bottom of the page:

On a dedicated “subscribe page”:

On a dedicated landing page (above the fold):

Lightbox popup:

Scroll box popup (or anything on the bottom right or left side):

My advice: use the expected placements before you start experimenting with creative real estate changes. People generally expect forms to be in those places, so don’t reinvent the wheel, at least right off the bat.

At CXL, we used to have quite a few badass and creative email capture forms, thanks mostly to working with BounceX, who crushes it with creative lead generation methods. They’re not up live on CXL’s site anymore, so I can’t get a screenshot, but we had:

• A hover over lead capture trigger. When someone hovered their mouse on the header image, it turned into a CTA.
• A left sidebar pull away that took you to the left side of the screen (hard to describe without an image, but it was cool and dynamic).
• A callout quote box in the middle of articles with Peep pitching an ebook offer we had.

However you do it, please try to refrain from doing that full screen takeover, welcome mat bullshit. It’s bad UX.

Why: The Most Important and Underlooked Question

In retrospect, I should have started the article with this one, but editing and formatting is for chumps.

Your “who” is definitely important, but you should probably define this question first: Why are you collecting emails?

What do you plan on doing with the information? Haven’t you considered what your “lead nurturing” experience would be (what a terrible phrase “lead nurturing” is).

Essentially, drawing out a customer journey map, starting at A and ending with Z, helps you formulate a smart and gentle plan to capture emails and information in a way that balances succeeding at your business goals with providing a good user experience. Considering your end goals helps you craft your content, the content offer, how many email capture forms you really, and how much information you ask for within your forms.

To that end, the whole “why” thing is a pretty big topic. It usually leads me down a rabbit hole of digging into core marketing systems and email automation flows, instead of simply the email capture mechanisms. I recommend starting out reading some materials on customer journey mapping and following it up with some good content on lead nurturing (there’s gotta be a better word for that?).

How: Form Optimization (and Moving Beyond Basic Forms)

So let’s say you’ve reached a point where you have a pretty pristine idea of whom you’re targeting, with which offer, when, and where on the page. You’ve also got a pretty sweet email automation workflow that’s converting leads into customers like gangbusters.

Another angle you can use to improve your email capture results it by looking at “how” you’re asking.

• How have you designed your lead capture form?
• How many form fields are you using?
• Can you optimize the sign up flow?
• Can you get rid of traditional web forms altogether?

There’s a level of creativity that expands beyond simple lead generation forms (give me your email, I’ll give you an ebook on the thank you page, etc.). Most of it starts with implementing some good form analytics solution to know your current form performance. I like using a dedicated tool, something like Formisimo. You can, however, also use Google Tag Manager to set up some pretty sweet form tracking implementations.

In any case, you’ll want to know when and where people are dropping off of your forms. This allows you to make intelligent decisions in culling form fields or simply reordering them to make the process smoother.

Form optimization is a massive subject. Should you use single or multi step forms? Single or multi column? How much information is too much to ask for?

Maybe it’s a cop out, but I’m just going to link to my favorite resources we published at CXL. No need to reinvent the wheel here:

• 13 Empirically-Backed No BS Form Design Best Practices
• 7 Web Form Optimization Insights from Testing Hundreds of Forms
• 14 Steps to Building Sign-up Forms That Convert
• Should You Really Reduce Form Fields?
• Form optimization (paid course)

Another topic is on the lead form itself. Nowadays, many companies are testing out bots or other types of interactive/conversational forms.

There are a bunch of tools you can use to help you design a chatbot/conversational form yourself (there’s probably a difference between the two, technically, but right now they seem to be used interchangeable. Here’s one such solution:

I haven’t tested conversational forms or chatbot much myself, but I can say that, generally speaking, I mostly hate chatbots. I’ve seen a few good ones, but most of the time I’d much rather just use a simple form. Or if I want to talk to people, live chat. Chatbots seem to be a weird hybrid model that is just unsatisfactory. Maybe it’s just been bad execution, but they all seem to be written with cutesy, chatty copy that I find annoying and patronizing. I don’t know, feel free to change my mind.

Something I do like, though: interactive quizzes and surveys. I think those are completely underrated as a lead generation mechanism. Think of Buzzfeed quizzes, but ones that ask for email addresses in exchange for the results. This Greenpeace one is a good example:

There are also voice forms and lead generation to think about. I don’t know enough about that to write about it, but it’s a thing. Read more here if interested.

Point is, the world is iterating on the basic idea of a form. I’m sure there will continue to be inspiring and interesting ways to collect visitor information in the future. If you’re just getting started, there are a lot of basics to cover first. But if you’re passed that point and want to start thinking about “how” you’re actually capturing information, there’s a fast moving world of innovations to look into.

Conclusion

Email capture is a huge topic. Frankly, this guide is probably too long as is, but I haven’t even covered lead magnet creation and the various types you can create, and I haven’t even touched upon things like GDPR, which do matter for information collection now.

That said, this guide should give you a core understanding of how to build out an email capture strategy, and it should give you more than enough ammo to know how to begin optimizing an existing set. Just ask yourself the questions every good journalist or police investigator (or Ludacris) does:

• Who?
• What?
• When?
• Where?
• Why?
• How?

If I’ve missed anything crucial, be sure to call me out in the comments! Hope this helps you capture some emails leads & subscribers.

The post How to Capture Email Leads (using Journalism’s 5 W’s technique) 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.

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