Onboarding Mobile Users: You’re Doing It Wrong

When you think about mobile onboarding, do you just focus on how to do it, the techniques?

Are you wondering why your retention rates are in the gutters and you aren’t seeing the onboarding rates that you want?

You’re not alone with those problems. When we talk about onboarding, teams tend to focus a whole lot on the techniques rather than what actually drives retention. In this article, we’ll move beyond the techniques and look at what you need to truly focus on to drive better onboarding rates and retention.

Don’t get me wrong here. These techniques are definitely important:

• Function-oriented
• Benefits-based
• Progressive
• Tooltips
• Onboarding screens
• Videos

They’re excellent tools to utilize and definitely things to consider…after you figure out what drives retention. What you want to avoid though, is every app blindly following the same “best practices.”

Just think about it for a second. Every app is unique. What works for one app doesn’t necessarily work for another.

Rather than applying a template onboarding process technique, you need to figure out what specifically affects retention in your app and bulldoze any friction standing in their way.

So here’s the exact framework you need for onboarding:

1. Use data to find your app’s Aha! Moment
2. Eliminate friction between new users and the Aha! Moment
3. Iterate

I’ll show you exactly why this framework works and how to do it.

The Aha! Moment

We most widely understand the Aha! Moment as that stereotypical lightbulb moment where everything suddenly clicks.

A more specific product definition is “an action or set of actions that separates users who return from those who don’t.”

This means that:

• users who take the action(s) tend to retain
• those who don’t tend to drop off.

Okay, so how do we find this?

Using your historical analytics data, you can observe if there is a high level of correlation between certain actions in your app and users that retain and test if a behavioral change increases retention metrics. Visualized, it looks like this:

The process itself is one long post, so I won’t dig into all the specifics here, but here’s a brief overview of the steps:

1. Get a baseline for retention
2. Create hypotheses on possible actions that affect retention
3. Plug the numbers into a simple spreadsheet
4. Calculate the percentage correlation between key actions and retained users (I’m oversimplifying)
5. Track the difference in retention using behavioral cohorts
6. A/B test variants that drive users toward Aha! Moments to determine causation

Going through this process reveals specific actions that are highly correlated with retention, and allows you to focus on getting users to those actions. After we find this, the challenge is simply getting users to take those actions so that they’re more likely to retain.

Inciting Behavioral Change

The next step is to get as many users to the Aha! Moment as you can. To this, we’re going to dig into a simple psychological model for a second: BJ Fogg’s Behavioral Model.

Fogg’s Behavioral Model basically says this: in order for a behavior to occur, three things need to be present:

1. Sufficient motivation
2. Sufficient ability
3. A trigger

If motivation and ability are present in adequate amounts, a trigger will prompt a behavior (our Aha! action) to occur.

Most of the motivation part of the equation comes before the user ever downloads an app. This can include advertising, app descriptions, word of mouth recommendations and more. While we can improve motivation with techniques such as social proof and personalization, our efforts are best leveraged by focusing on increasing user ability.

Eliminating Friction

What we really want to focus on is driving users to the actions that drive retention. This means making it easier for a user to complete the desired Aha! action. There are a lot of ways we can do this, including:

• Refining the mobile login/registration experience – often the biggest barrier, there are many tweaks you can use such as showing passwords, social logins, increasing usability of form fields, or allowing alternative logins.
• Remove flow blockers like onboarding tutorials – As we’ve seen in tests with both Gametime and Vevo, onboarding tutorials can simply introduce unnecessary steps in the process.
• Prioritizing responsiveness and speed of the app
• Decreasing the cognitive load
• Reducing decision fatigue – when users are overloaded with choices, they tend to freeze up and drop off rather than proceed. Simplifying their new user experience to a highly guided flow (or using tooltips) can help alleviate this.

Each change you make that decreases friction increases the likelihood that a user will reach the Aha! Moment and retain. And that’s all we ultimately want: for users to activate and retain.

Do be careful when improving your onboarding though. You need to track your before and after retention data to make sure it’s actually helping your cause. Using A/B testing can help you do so, as can using retention cohorts.

A Fresh Approach to Onboarding

Rather than applying the newest best practices, the Aha! Growth Model provides an efficient, data-driven way to activate users and set them up for success. Once we find the Aha! Moment, we can simply start driving users toward the right behaviors that we know are correlated with retention.

Alright. That’s it! As for your action steps:

1. Find your app’s Aha! Moment using data
2. Brainstorm techniques that help bring the user closer to Aha!
3. Track the effectiveness of each change using A/B testing and retention cohorts