How to Integrate a Mobile App Analytics Tool

Let’s imagine you’re the owner of an extremely popular app that attracts millions of users per day. Yet, there’s a slight problem: the users don’t seem to buy one particular product that you think should be getting more purchases. If you try to play detective and deduce what could be the reason, you’ll face a huge number of possible issues:

• The users see the bad rating of the product and then leave the screen.
• The users fail to check out the product, and the app crashes.
• The users on average don’t even get to the screen with the product.
• They spend a lot of time reading the description of the product but eventually decide they’re better off without it.

But how do you verify which of all these hypotheses is the real reason behind your problem?

App analytics is the thing that can give you an answer. Using the right tool you’ll be able to see how much time your users spend on the screen, and which buttons they press, thus helping you to understand their intentions better.

Strictly speaking, app analytics allows you to measure user interactions within your app while giving you general statistics without breaking the privacy of the users.

But the problem is that there are numerous mobile apps analytics providers out there, and each of them works best only in certain cases. How do you know which of them to choose?

In this article, we’re going to answer this question, giving an overview of some of the analytics use cases, its main providers, and a couple of our own case studies.

📊 Mobile App Analytics Use Cases

Before choosing an analytics provider, you first have to define the tasks you want to solve. This section will give an overview of the major analytics use cases and its related terminology.

1. Tracking User Engagement

The main reason why you might want to implement analytics in your app is to track the engagement of your users. Engagement is a very broad term meaning the response of your users to your digital product. This includes:

• Installs of your app.
• Sessions when users open your app.
• Time they spend using it. This can also include the time users spend on specific screens in the app or on pages in websites.
• **Retention. **This is a measurement of how many users return to your app after the first open.
• Churn rate. This is a metric opposite to retention and shows how many users have abandoned the app. While this might not be a very useful metric in itself, it usually works well when comparing it with other data. For example, you might see a correlation that users who don’t buy a subscription (and so have limited functionality) tend to abandon the app.
• User events in the app. For example, you might want to track how many people press a specific button, or how many of them open a specific screen. This metric can be visualized as a heatmap, showing the places of most activity:

📱 Main Mobile App Analytics Tools & Providers

Another challenge you might get when implementing analytics in your app is choosing the provider itself. Different providers can vary a lot in terms of their visualization techniques, functionality, pricing, and platform support. This section will look at some of the most popular analytics providers and compare them.

Firebase

The most popular analytics tool is Firebase Analytics (a.k.a. Google Analytics). Some of its main features are:

• Event tracking. Here you can both define custom events (such as presses on a particular button), and get information about built-in events, such as app launches and user retention. The event tracking dashboard looks like this:

Pros:

• Supports most of the conventional metrics: engagement, conversions
• Custom events
• A/B tests
• Powerful visualization

Cons:

• Might be a bit harder to learn than other tools
• Has steep pricing (from $995/month, according to GetApp).

🚴 Our Mobile Analytics Integration Expertise: Sportplus

Sportplus, our recent mobile project, required a custom and complex analytics integration.

Sportplus is our Germany-based client, and a manufacturer of workout devices: cross trainers, treadmills, trampolines, etc. The problem was that there was practically no way to know the users without an app, as after selling the device all connection with the buyer was lost. Sportplus contacted our team to develop a tailor-made app that would connect to the devices, and gather analytics about users.

We needed the analytics in a couple of different places in the app:

• To log user events in the app, such as pressing specific buttons or going from one screen to another. For this we used Firebase Analytics, and its React Native SDK to integrate Firebase into the app.
• To integrate analytics with push notifications in order to know how many of them are opened. Since we used Firebase’s Cloud Messaging, we got an integration with Firebase Analytics out of the box, so to link the notification with an event all you have to do is to choose the event in the dropdown:

Then, all you have to do is to use the wrapper in your App.tsx.

Well done!

💡 Takeaways

Now, let’s make a quick recap by deciding which analytics tool to use in which case:

• If you want it to be cross-platform, including the Web, choose Firebase or Mixpanel.
• If you want strong integrations with a bigger development ecosystem, Firebase is a great option.
• If you require detailed and comprehensive visualizations of the data, with it being easy to understand, consider UX-Cam, Amplitude or Mixpanel.
• For small apps and projects without much funding, Firebase or Mixpanel sound like great options.

So, this is it! We hope you’ve liked the article, and in case you need any help with building analytics-integrated apps, feel free to reach out!