Excellent translation丨Mobile APP analysis insights!

Data is beautiful, but the ultimate purpose of analysis is to generate insights from it so that you can take action.

Mobile APP analysis is the first core part of non-website platform analysis in GA. This reflects the user migration trend toward smartphones and tablets that we predicted six years ago.

In the past, we had to develop our own mobile app data tracking tools (which would eventually end up in failure because their reports looked the same as website data reports ). The new Google Analytics mobile app analysis presents data around the app in reports, making it easy for us to track user interactions in the app. Instead of tracking apps the same way they track websites, mobile app developers will be pleasantly surprised to find that the data reflected in the reports is very applicable to their business.

Data is beautiful, but the ultimate purpose of analysis is to generate insights from it so that you can take action. In this post, I will look at some examples of reports from GA’s new app analytics interface to show you how these reports can help us make some decisions for our business.

Release: How many people are using our app?

Let’s say we’ve just released the latest version of our Flight Search app. We received an email notification that our app had just passed the App Store review (finally) and we were ready to start operating . Or we have just launched some marketing campaigns targeting certain regions to encourage users to install our app. It is very important for us to monitor in real time the effectiveness of our user acquisition, the sources of users and how users participate in the APP content.

This is where real-time reporting comes in. Within seconds of user interaction, data can be presented in reports, allowing us to quickly take action based on the data. We can see the number of users for each app version, which screens they are active on, and their geographic location (down to the city level).

Monitoring and iteration: How do we optimize user experience?

There are many ways to acquire and attract users. It is very important for us to understand the user's behavior and behavior trajectory in the APP. We hope to answer questions like:

• Are there bottlenecks in our business?
• Why do users leave the app?
• How will user behavior differ based on different operating systems, languages, etc.?

The Behavior Flow Report tells us how users move through the app, where they leave, how they get to specific screens, and in what order they browse to get to those screens. Our Flight Search app report is shown below. It seems that the exit rate is high on some important screens (in red).

We would think of splitting the data and narrowing the problem down to a certain operating system, APP version, user type, etc. This approach allows us to iterate and improve the user experience over time.

Measure and Iterate: How do we prioritize problems?

Our APP can be downloaded from the app store, but user reviews show that the APP has some technical problems and sometimes crashes suddenly. To be realistic, bugs are an unpleasant reality for developers, and to some extent, they have always existed. The question is, how should we prioritize and allocate resources?

Crashes and Exceptions Reports will give us some important data that will help us get closer to the answer to our problem. This report will give us some information, such as:

• What abnormalities occurred in the APP?
• What impacts did the abnormality bring?
• Where/when do these anomalies occur in the app?
• On which devices, operating systems, and app versions does it appear?

Looking at the report below, it seems that a bug was fixed when upgrading to version 2.1, but it brought another bug. Segment the data to find out more information about the anomaly so we can take appropriate action. For example, maybe this bug only exists on the Android client and not on iOS. In this way, our Android development team will need to do more work, and our iOS development team can release the iOS APP earlier.

Evolution: What operating systems/features do we need to focus on?

As we prepared to further develop the app, new challenges arose and we needed to know how to allocate resources within the company. What operating systems should we be concerned about? What function of the APP, in other words, has the greatest impact on our profits?

Continuing with the Devices and Network Overview report, we are able to get some important information for our Flight Search app. For example, most of our Android users are running Android 4.0 or above, and only a small number of users are still using Android 2.3 or lower. This tells us that if we stop maintaining operating system versions below Android 4.0, the impact on users will not be significant.

Based on what has been mentioned above, we can start using some features of versions 4.0 and above, and we don’t have to continue supporting 2.3, which can help us save some trouble. On the other hand, we have almost no users of Android 2.3 and below, probably because our app is not optimized for Android 2.3. We need to observe this further. It is very important to look at this data from different perspectives so that we can make the best decision for our business.

Evolution: Which users should we focus on?

As our user base grows, so does our GA data, allowing us to identify issues and take action on important segments. Behavior reports, such as Session Duration and Loyalty, provide valuable insights.

Users with longer session duration and more sessions have higher conversion rates . This tells us that we should focus on user retention and engagement: we hope that our users can come back to our app after leaving, and we need to locate the points where users exit (the Behavior Flow report mentioned above can help us). Data shows that repeat users and users who participate in the app for a longer time have a higher chance of conversion. This information is very important for both marketing and design work.

Reporting: How can we present data to its best effect?

So far we have discussed ready-made reports. All reports are generated by default in GA. However, it is effective to customize reports with specific dimensions and indicators for a particular business. That is, the data in the report can reflect a specific business. I’ve previously written about some use cases for Custom Dimensions and how you can use them to improve your reporting.

Custom Dimensions are just like the default dimensions that already exist in GA, except that we can create our own, allowing us to collect additional data that GA doesn’t provide by default.

Custom dimensions not only allow us to obtain additional information about users and content, but also allow us to create reports that are applicable within our company. People within the company may not be familiar with the terminology and data presentation in GA.

By creating a custom dimension at the "customer level", for example, we can create reports and segments as shown below. This report is close to our business and is also easy to circulate within the company.

Similarly, custom metrics also allow us to send custom data to GA, but custom metrics send numeric values ​​instead of strings like custom dimensions. Let’s take our “Flight Search” app as an example. We want to add several custom metrics: number of searches, number of bookings, number of cancellations, etc. This will create a report like the one shown below. Such reports are still close to our business type and applicable within the company, even for those who are not familiar with GA.

The GA Mobile App SDK makes it very easy to install the tracking code on our mobile apps and opens up many powerful analytical features. By measuring and iterating on the app, we can continuously improve the user experience and ultimately grow our business. Sometimes it’s easy to find an obvious money-making bottleneck, but sometimes it takes more detailed analysis to gain more valuable insights.