How Every Executes: two tweaks that generated ~54% more paid subscribers

Real data from our business showing how execution is exponential

Jeswin Thomas / Unsplash

The big idea behind last week’s post was “execution matters a lot.” 

If you want to get fancy about it, you could go further and say “marginal improvements to each step in a process (like raising money, launching products, onboarding users, recruiting, etc) can compound into exponentially better outcomes.” 

The example I used was a fundraising process that had a 12x better outcome given good execution, but it came from a bunch of smaller improvements made to each step along the way, like getting intros, converting them into meetings, and getting meetings to a “yes.”

This week, we’re going to go even deeper into the topic of execution and explore three big follow-up questions:

  1. Can we go through a real example with real numbers? Yes, we can! I’m excited about this one. In this post I share two real improvements we made to our funnel last year that compounded together to generate roughly 54% more paid subscribers for the same volume of traffic. It took our engineers like three days to ship these two things, and now for every million visits we probably generate an additional $100k of revenue! In this post I will go through all the numbers, what the experiments were, how the math works, and what important caveats you need to know before you do this in your own business.
  2. Given limited focus and resources, how can a company determine where improved execution will be most impactful? One smart piece of pushback I got last week was that improved execution in some areas is obviously much more valuable than others. For example startups probably shouldn’t spend much time making sure internal IT is perfected, and should focus more on product and sales. But within these obvious broad areas there are many possible choices for where to focus. In this post I use the classic book “The Goal” to give you a framework for finding the most valuable use of your energy.
  3. Does improved execution in one area of a business really spill over into improved execution in other parts of the business? What about businesses that are famously good at some things and terrible at others? For example, Dropbox had an amazing product but was terrible at enterprise sales and lost the B2B market to Microsoft, Google, and Box.

I’m most excited about the first bullet point here. It’s (relatively) easy to be the hand-wavy guy who spouts frameworks and abstract mathematics—generating real results and showing real data is what matters. We did this previously with my post on bundling, but it’s been awhile, so I’m excited to get back to it. 

Read this (paid) post if you want to know an easy way to utilize the power of execution and how to know where to apply it.

1. How we execute at Every — a real example

One of our most critical business processes is converting people from looking at an article on the website to joining our email list. The way our article pages are designed can be executed better or worse to achieve this goal. 

Here’s three versions we recently tested. All had the same design, only the words were changed.

Version 1

(We stole this copy from The Atlantic

Version 2

(Focus on what the product actually is)

Version 3

(Focus on the larger purpose / benefit. Kinda shames people though, which I don’t love! lol)

And here are the results:

[REDACTED — become a paid subscriber to read the rest of this section with full data and analysis! ]

In case you’re on the fence here’s a substantial preview of the second section:

2. How to prioritize your execution energy

There is only so much time in the day. Where should you spend it? This is the age-old question that haunts Product Managers everywhere. There are frameworks galore, but in my opinion few are actually helpful. They are fill-in-the-blank exercises that assume you already know the answer. For example, one common framework is to list the metric you think would improve if you did a project, how much it would improve by, and how certain you are that it would actually improve. Then when you multiply impact by uncertainty, you get the risk-adjusted return.

The problem is of course that you have no idea what the risk-adjusted return is, because at the end of the day you’re pulling numbers out of your ass, and the framework doesn’t give you any leverage to come up with better numbers. All it does is quantify your prior beliefs, but what we really want is a method to come up with new, better beliefs.

That’s where the Theory of Constraints comes in. It is a management philosophy created by Eliyahu M. Goldratt and popularized in his perennial bestseller The Goal. The basic idea is as follows:

The output of a system is determined by the bottleneck. If you want to improve the output, you need to attack the bottleneck until it no longer is the limiting factor, and something else is. Rinse and repeat.

Let’s make it more concrete. For example, at Every there are a few key steps that make up our system:

  1. Write articles
  2. Get people to read the articles
  3. Convert new readers into joining the email list 
  4. Convert free readers into paid subscribers
  5. Attract the right advertisers
  6. Get readers to click on the ads
  7. Use the money we generate from subscriptions and ads to hire more writers

There are more steps, and each step can be broken down into infinite sub-steps, but this is a good basic outline of our system for the purposes of this essay.

The Theory of Constraints tells us if we want to improve our system, one of these steps is going to be the critical “limiting factor.” In other words, no matter how much we improve the other steps, it won’t make a big difference because all the improvements are being held up by the bottleneck.

In his book, Goldratt thinks about this in a manufacturing context. There is one big machine that needs to be used to create every widget, and that machine is slow and expensive. Therefore, everything should be organized so that the machine has as little downtime as possible, because the entire system can only output widgets as fast as that machine can run.

For Every, it’s a little more fuzzy but the basic principles still apply. If our articles attract very few new readers, we can technically still make more money if we do a better job with all the other steps, but it will be a small, marginal improvement compared to anything we can do to fix the real limiting factor. No matter how smooth our funnel is or how good our conversion rate is, we can’t sell ads or generate many paying subs from a small audience. So everything is basically limited by step 2: get people to read the articles.

How do we get more people to read the articles?

  • Writing better articles
  • Attracting more good writers
  • Promoting our articles in better ways

Those are the big categories, but again each of these is massive and contains many worlds of sub-optimizations. For example, within “writing better articles,” there is:

  • Improving topic selection
  • Writing better headlines
  • Talking to people who know unique things
  • Getting better feedback from each other
  • Learning more from the data on our existing articles

And within each of these bullet points there is again infinite complexity. It’s like a fractal: you keep zooming in and you keep seeing more sub-components.

The cool thing about the Theory of Constraints is that it helps you no matter what level of zoom you’re at.

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