User engagement metrics are the key to developing a habit-forming product. But if you're looking at the wrong metrics, or misinterpreting the right metrics, you'll make misguided product changes.
It's easy for even the best product managers to misread data by overlooking some variable or overestimating one metric's importance at the expense of another's. Simple mistakes like these cost you valuable developer time, spending on user engagement tools, and—most importantly—customers.
Here are the most common mistakes we see when we talk to people about their user engagement metrics.
1. Don't Measure DAUs Through Logins
“Daily Active Users” are typically measured by the amount of people who log into your app every day. Most people fall into two camps about this metric: Either they think it's useful for measuring growth, or that it's complete nonsense.
The second camp calls DAUs a “vanity metric,” because a customer could log into your app day after day, experience friction, get frustrated, and log out. A DAU could be days, hours, or minutes from churning, and you wouldn't even know it just by looking at that metric.
Take a look at this graph from Amplitude comparing the number of users logging into a music app with the number of users playing songs.
At the end of the curve, less than a quarter of the DAUs are actually using the app. Even though they're logging in daily, they're not getting any value from it.
But this doesn't mean that it's wrong to calculate DAUs in the first place. It's a matter of aligning your definition of a DAU with your business's goals.
Redefine what “active” means
Stop measuring DAUs by logins, and redefine “active” to mean the people who complete core actions in your app. By changing the way you measure DAUs, you can predict (and prevent) churn. You can do this in one of two ways.
- Target action. Measure based on a low-effort, basic action that signifies usage. For example, if your product is an email client, a DAU could be someone who reads or re-rereads one email per day.
- Time in app. If your app doesn't require one specific action beyond logging in for users to get value from it, consider measuring your DAUs by the time they spend in your app rather than just the act of logging in. For example, if you're an analytics company with a super clear dashboard, you can mark a DAU as someone who spends more than two minutes per day looking at that dashboard.
Neither of these metrics measure the best user, or who's getting the most value from your app—tools that track behavioral metrics, like Mixpanel, can do that. But unlike daily logins, it provides an accurate baseline for who is getting value from your app on a daily basis.
2. Eliminate Bounce Rate False Alarms
A high bounce rate on your marketing site means that visitors aren't interested in engaging with your pages.
Your Google Analytics dashboard indicates that your website visitors are dropping off at an alarmingly high rate—which means that they're not signing up for your product. No matter what you do, all of the subtle ways you try to push your visitors towards engagement, the bounce rate keeps hovering at around 85%. That's cause for alarm, right?
Not necessarily. Someone “bounces” when they come to a page and leave without clicking on anything—but not all pages require a click for their viewer to get value. A dedicated blog follower can open one of your posts, read through it, decide that they got the information they needed, and leave. You write your blog posts to build your brand engagement, and your viewer did exactly what you hoped they'd do, but it still counts as a bounce.
Your bounce rate is supposed to be a red flag for when your viewers are becoming disengaged, but there are many instances when bouncing doesn't signify disengagement. Here's how to make your bounce rate a more meaningful metric.
Adjust your bounce rate
Use an “adjusted bounce rate” instead of a standard one by adding a time minimum.
Bounce rate is supposed to identify disengagement, but any user who spends more than 30 seconds on your page shouldn't be considered a bounce because they may have engaged with your product. By taking into account people who might be reading your content, checking out your pricing, or writing down a phone number without interacting with your page, you can eliminate false alarms in your bounce rate data.
In Google Analytics (and many other platforms), all it takes is a simple line of code that specifies how long someone has to spend on your page to not be considered a bounce. This is a standard Google Analytics tag, and you should add your own tracking ID where it says “UA-XXXXXXX-1.”
You can personalize the time minimum to be whatever you like in your code. And once you've added the minimum, Google Analytics will still calculate your Exit Rate, so you won't be missing any important data about viewers who leave your site.
3. Optimize Your Session Duration
The dialogue surrounding user engagement is always more, more, more. We want more people in our apps, we want them to spend more time there, and we want everyone to log in more frequently.
But more isn't always better when it comes to session duration. The amount of time users should spend in your app is completely dependent on your product. [source]
In this app, most users spend 3-10 minutes per session. But imagine if this was an alarm clock app, and it took users 6 minutes every time they set an alarm. They'd be looking for a new clock.
Find a target session duration
Instead of focusing on increasing your session duration, focus on optimizing it for your product. Create a target session duration based on how long it should take a user to complete a core action inside of it.
Tools like UserTesting employ people to test your product and record their user journey. With a product like UserTesting, you'll see directly what roadblocks stand in your user's way. Once you've eliminated those barriers, the optimized session duration isn't just a pat on the back—it's a baseline. Conducting user tests helped HubSpot achieve a 400% lift in one of its metrics.
Once you know how much time a user should be spending in your app, you can help them accordingly, for example, by making it easier for them to complete tasks or activate a new feature.
4. Conversion Rate Comes Later
In the SaaS business model, the only way to survive is to retain your customers. It's not enough to acquire new ones if you are hemorrhaging customers left and right.
With a subscription business, you front-load your marketing, sales, and product spending for every customer in hopes that it will pay off and profit over time. But a customer can cancel their subscription at any moment. If your customers are churning, you'll never get back the cost to acquire them (CAC).
Your paid conversions are worth paying attention to because they tell you how many people want to try out your product, but it's far more important to nail retention first. Focus on conversion later, when you know you have a product that people want to stick with. Customer retention is what pays off your CAC, determines your profits, and sets up your business for success.
Use acquisition cohorts
From there, organize your retention data into acquisition cohorts to understand what's keeping customers around and what's driving them away.
Acquisition cohorts divide users by when they first downloaded your app. Analytics experts at CleverTap explain, "By measuring the retention of these cohorts, you can determine how long people are using your app and where you’re losing them.”
By tracking exactly who started with your product when, you can assess what features made people stick around, and what made people leave. If lots of people converted when you rolled out Product 2.0, you could use acquisition cohorts to compare retention between old customers and new customers. You can see whether your new onboarding process is helping customer retention or driving customers away.
By organizing your conversion data into cohorts, you'll know what keeps customers around for you to earn back your CAC and more.
5. Find the One Metric That Matters
One of the most common mistakes is using too many metrics at once. All product initiatives need a clear goal, and if you're focusing on all of your engagement metrics, you won't truly measure the impact of how those initiatives are affecting your company's growth.
Ben Yoskovitz's principle of the One Metric That Matters is about basing your company's growth off of a single, measurable metric. The metric should help answer the most pressing questions about your company's growth and help you make changes moving forward. Here's how to pick the right one.
Use your whole toolkit—but not all at once
Your One Metric That Matters should change as you grow and achieve your goals. But to give you somewhere to start, Ben Yoskovitz outlines how to pick your metric based on these stages of business development.
- Viable product validation. At this stage, you're looking to see whether your solution to people's problems (your product) is viable. Metrics like Net Promoter Score and amplification (the way people share your product on social media) measure a baseline of how happy your users are with your product, before you move on to the trickier stuff.
- Attention generation. Once you've got an audience who's happy with your product, you're going to want to expand that audience by acquiring more users. Use a conversion metric to test how well your attention generation and marketing initiatives are working.
- Feature development. When you have a happy, large user base, it's time to expand and hone your product. Measure the impact that developing certain features (and the way you roll them out) has on a key metric, like churn rate.
Every product, no matter how successful, will have different weak spots, and those weak spots will change as you achieve your improvement goals. Making a well-rounded product means continually checking up on all of these metrics—but doing it one at a time.
Avoid Error with Product Context
These mistakes and more are common, but avoidable.
It's always more important to think about your data in a personalized way than follow a formula. Regardless of what's in the product manual, you have to think about what the data means in the context of your product.
Once you nail down interpreting metrics in the context of your specific product, you'll be sure of which direction to build in—and the steps to take to make your company a success.