User Growth and Engagement: A Hacker Metric

If you’re like me, you’ve had enough of the Facebook IPO story. For tech entrepreneurs struggling to build stuff, the cacophony of recent press is just more noise. That’s why when my friend Andrew Chen posted an insightful analysis of Facebook user data, I was happy to get back to learning from what the company did right instead of debating what its bankers did wrong.

Chen calculated Facebook’s historical ratio of daily active users (DAU) to monthly active users (MAU) and the stats are startling. Since March 2009, when the earliest data is available, approximately 50% of Facebook users logged in daily.

As other technology companies struggle to maintain DAU to MAU ratios of 5% or less, Facebook’s numbers appear stratospherically high in comparison. But what is equally surprising is the consistency of that ratio over time. Despite periodic user revolts in reaction to changes in the site, the ratio remained strangely stable. In fact, the number has risen over the past year and is now hovering at 58% as of March of this year.

It’s as if Zuckerberg has steered the company by this golden ratio. Which raises the question: is there some wisdom here regarding this ratio as a predictor of Internet success? Obviously, there are no guarantees and starting cutting edge tech companies will always be risky business. But, assuming you have a solid business model, there are good reasons to believe that if there is one metric to focus on while building your business, it’s the percentage of users who come back daily as expressed by this ratio.

As I’ve written previously, I believe a mastery of the mechanics of habit design is increasingly deciding startup winners and losers. Not only because habits cement user behavior in an increasingly cluttered digital world, but because a high-engagement product is also a high-growth product. The two are one and the same. A high DAU to MAU ratio is a great indicator of the strength of user habits and, ceteris paribus, I’d bet on a business with the higher ratio over a competitor every time. Here’s why:

More is More

When it comes to web and mobile startups, high DAU to MAU is more important than the size or growth rate of an entrenched competitor. Case in point, Facebook defeated much earlier competitors like MySpace and Friendster, both of which had healthy user growth rates and millions of users by the time Facebook got started.

This is because of what I call the “more is more principle.” High user engagement has an exponential effect on user growth. As David Skok points out on his blog, “The most important factor to increasing growth is not the Viral Coefficient, but the Viral Cycle Time.” Viral Cycle time is the amount of time it takes to complete a viral loop and it has massive impact on user growth. “For example, after 20 days with a cycle time of two days, you will have 20,470 users,” Skok writes. “But if you halved that cycle time to one day, you would have over 20 million users! It is logical that it would be better to have more cycles occur, but it is less obvious just how much better.”

Having a greater proportion of DAUs dramatically improves Viral Cycle Time for two reasons. First, daily users initiate loops more often – think tagging a photo on Facebook. Second, more daily active users means more people to respond and react to each invitation. The cycle not only perpetuates; with high DAU to MAU, it accelerates.

One Way to Grow

Those who talk tech split into two dogmatic camps. Some prioritize user growth and accept low user engagement, while others believe a company needs to nail user engagement before focusing on user growth. I believe this is a false dichotomy. If you have only one or the other, congratulations, you’ve got squat.

Let’s first take a look at user growth. Distribution, of course, is critically important and no company can survive without a sound customer acquisition strategy. Not only is user growth essential but it is something engineer-driven companies love to work on. In fact, the title of “Growth Hacker” has recently become a badge of honor among Silicon Valley digerati. Tweaking viral coefficients and instantly seeing the results is intoxicating. It’s startup feedback at its finest.

But optimizing user growth without user engagement has its pitfalls. As Peter Thiel recently told his class at Stanford, the effectiveness of distribution channels tends to follow a power law. Just as businesses tend to have only one revenue stream, they also have only one good user growth strategy – the effectiveness of which is 10x the results of other distribution channels. The problem with having only one real way to grow is that the method becomes obvious to others and is quickly copied. For example, in its early days, Facebook capitalized on users importing their email contact list to drive user growth. But soon thereafter, so did everyone else.

But having competitors copy you is a high-class problem. It means something is working. Worse yet is discovering a fantastic viral loop that drives user growth only to see user engagement crater when users realize there’s little long-term value in the service. Ringtone businesses, sheep-throwing Facebook games circa 2008, and today’s social video sharing apps using questionable growth tactics, are just a few of the “leaky bucket” businesses that occur when distribution outpaces user engagement.

When it comes to building a big business, clearly a good acquisition channel is mandatory, but not sufficient. Given the power law of user growth, you will likely only have one major way of acquiring customers and it won’t be much of a secret. You’ll need some other competitive advantage.

User Engagement as Advantage

As opposed to distribution channels, the mechanics driving user engagement do not follow a power law. In fact, it is the nuances of user behavior that make the competition irrelevant, just as it did in the case of Facebook’s early rivals.

Discovering non-obvious user needs and creating accompanying habits is accomplished through deep observation grounded in solid behavioral theory, followed by methodical trial and error. It takes time to create new habits and getting the user to act the way you’d hoped is accomplished by uncovering a thousand tiny insights into the user’s psyche. The process of uncovering latent needs is characterized by understanding more about users than they know about themselves.

The distribution strategy will always be obvious, but the behavioral insights are important secrets that can only be discovered through rigorous testing. Zynga had one obvious way to acquire users, namely Facebook ads. But the company has a cadre of behavioral insights it uses to craft engaging games. It collects terabytes of information daily to alter game dynamics to boost user engagement. Quora primarily drives users to its site through Google search traffic. But the conjecture about all the reasons why the service is so sticky spills over a long question thread. Instagram posted images to Twitter and Facebook to drive user acquisition, placing its user growth strategy in plain sight. However, the founders, one of whom studied psychology as a Symbolic Systems major at Stanford, acquired a deep understanding of what makes users tick and click.

But why can’t behavioral design be copied like a distribution strategy? Because competitors are not able to recognize and act upon these kinds of insights. You can know the competition’s product feels better to use, but you won’t know why. Engaging products gain their advantages by leveraging tiny improvements, which together create huge advantage. From the outside, you can’t tell what’s working and what isn’t.

For example, the iPhone is objectively a better designed, more user-friendly, and ultimately more engaging product than the Android experience. But why? Nearly everyone, when given the choice between an Android interface and an iPhone, chooses the iPhone. There are plenty of good reasons to own an Android, but intuitive interface ain’t one. Google knows this and yet they can’t replicate Apple because they don’t know the answer to “why?” You can’t make decisions between seemingly identical interface choices unless you’ve walked the path of user behavior. Without this knowledge, copying the competition becomes a game of throwing darts at features.

Habit design requires a fundamentally different, though complementary skill set to growth hacking. Designing high-engagement products is an art which is increasingly becoming a science. The craft crosses the disciplines of psychology and design – both fields which are hard to learn in a short period of time. Unfortunately, designing habits often falls in the organisational abyss between the founders’ vision and what is technically feasible.

But those companies able to habituate users quickly enjoy massive advantages. Not only does engagement drive user growth for the reasons stated above, but users tend to shut out other, sometimes superior, solutions. In fact, business history is peppered with technically inferior products beating competitors because of the fierce loyalty of habituated users (I’m looking at you, Apple enthusiasts). Users only have time and brain cycles for a limited number of services. If a high proportion of users are using your service daily, they aren’t using the competition’s.

Can’t Have One Without the Other

But focusing on user engagement without user growth is also a losing proposition. For one, virality is not something that can be bolted on to a product after it is in the wild. Distribution is not an afterthought and it needs to be built into the core of the experience. Either the company has a viral user growth mechanic or it doesn’t. So no matter how engaging your service is, it will remain niche unless there is a way to get it in front of new users en masse.

Creating a company with both high user engagement and high user growth requires a sound distribution engine fueled by active users. Both user engagement and user growth are essential to a company’s viability and by adhering to the tao of DAU and MAU, founders have an accurate point of focus to increase their odds of success.