Why it’s never too early to add product analytics to your app

When you’re in the early stages of launching a new app, you’ve already got an enormous number of challenges with little time and resources to get it all done.

So it’s tempting to think the additional add-on of measuring user events in your code (i.e., implementing product analytics) is something that can wait until your team is bigger, until you have more users, or until you have more money.

But, speaking from experience, I can assure you that implementing product analytics from the go can be well worth it. And even better, those few reasons you have for putting it off are more than likely not the concerns you think they are.

Here’s why.

The first excuse I see often is “We’re too small (as a team) to focus on analytics right now.” The logic is that the team is already at max capacity on other priorities like actually building features of the app, and there are just not enough humans and hours available to add yet another layer of complexity before the first or next launch.

This is a very compelling story (especially if you’ve got only one or two engineers or developers on your team who may or may not include yourself). If you don’t get your features built, you won’t have an app to launch, right?

The problem with this framing is it fundamentally misunderstands the reality of your situation.

For example, let’s say you’re on the verge of launching a new dating app and you get a handful of complaints from your beta users. The main message is that one of your centerpiece features is “confusing” or “doesn’t make sense.” You might be tempted to think you were wrong about the feature and should scrap it. It’s true that without product analytics to show you exactly where users stopped engaging, you could be looking at hours of user interviews and tons of manual forensics to find the issues (far too much work for your small team). But with something like Mixpanel in your toolbox, the process of isolating the true pain points, making appropriate fixes, and getting yourself to a version 1.0 release becomes far more manageable.

What happens next is that your official app launch pulls in more downloads than you ever could have imagined. From here, it’s easy to assume what you’ve put out into the world is delivering high value to your users right out the gate—but you might also just be seeing a positive initial response to things like your icon, marketing/branding, and mission, without your new users really engaging with your app’s features at all. With product analytics, you can know the difference. Even with a sudden influx of new engagement, your not-yet-scaled-out team could see exactly where users are clicking and how often, which leads to a more holistic understanding of whether those downloads translate to meaningful usage. Then you can tweak things as needed while you’re still riding the initial wave of your launch.

The bottom line the best way, especially for small teams, to continually determine viability and future direction in a somewhat automated way is to lay a strong product analytics foundation that gathers data points that can only be practically gathered in this particular way.

Another excuse that comes up all the time is “It’s too soon: We only have a handful of users and it’s not worth the effort for such a small amount of data—especially when we can just talk to beta testers.”

First of all, when it comes to product analytics, no amount of users is too small to glean invaluable insight. Remember, product analytics involves tracking events in your app. You know where users clicked and didn’t click, when they clicked, and in what order. You have nitty gritty data on how they engaged with features and how they didn’t. You only need a handful of users to challenge your expectations.

Say, for example, you just launched your app with three features that you believe are going to be a big hit. You’ve only got five users/beta testers, and they all claim to love all the features equally, as expected. At the same time, when you review the product analytics, you notice four out of five are using the biggest feature incorrectly. They’re taking steps in the wrong order and completely misinterpreting the intent. This is a problem because you have a bunch of additional features planned that build upon that feature, but only if used as designed. So the feature needs to be tweaked lest the feature roadmap gets derailed. As such, your product analytics provided a critical insight from just a small number of users.

A larger lesson here is that taking user feedback at face value will only get you so far—even when you have so few users that you can comfortably manage speaking to each one personally. Just because a user claims to “like” a feature, it doesn’t mean they will continue to engage with it or even use it correctly. A user is only ever responding to their personal interpretation of the user experience. They are not rigorously evaluating long-term value or even necessarily responding to a feature itself versus the fact that the UI utilizes two of their favorite colors. The events you track as part of your product analytics (regardless of how few events they are early on) reveal what users are actually doing separately from what they are saying they’re doing or feeling. It allows you to piece together the whole truth where the alternative could only ever provide slivers of the truth. And the sooner you get exposed to the fullest slice of the truth you can access, the sooner you will be on a path toward app success.

The third excuse is “We’re trying to launch as lean as possible, so we can’t afford to add any additional monthly expense at this time.”

Here’s the good news: You don’t have to add any monthly expense initially since most analytics platforms offer a free tier that covers the basics early on. Mixpanel even goes way beyond that with a free tier that allows up to 100k monthly tracked users and rich features other tools either lack or place behind an expensive paywall. (And if you’re an early stage startup, you may qualify for free credits toward paid features via Mixpanel’s Startup Program!)

But the more important point is that tools like Mixpanel really aren’t expensive even once you start to succeed at scale. Would you pay $200 to save yourself a month of engineering time? Sure you would. Engineering can cost tens to hundreds of thousands of dollars in a month depending on your app, and insights from tools like Mixpanel can prevent you from going down product rabbit holes that burn through months and don’t yield results.