If you run a search on mobile analytics best practices, you will find many. However, if you don’t know how to use these mobile analytics, you will only collect the information you will never be able to use.

Here are a few things you need to keep in mind if you want to gather the correct data in the right way and use the right metrics to optimise your app:

Track Three to Four Primary Metrics Instead of Relying on a Single One

One common mistake that many make when it comes to using mobile analytics is relying on one single metric. This will not only restrict your perception of your app performance; it will also skew the reality altogether.

For instance, if you focus on tracking daily active users of your mobile app, you will never be able to know for how long they have been using your app.

So, try tracking three to five metrics at once. Try not to go beyond five, as you might lose focus.

If you don’t know where to start, consider your business goals. What is it that you wanted to achieve by launching your mobile app?

Do you want to increase in-app purchases?

Are you looking at increasing the number of downloads?

Or are you planning to improve user lifetime value?

Write down the KPIs (Key Performance Indicators) that you want to track, depending on your business goals.

A few common KPIs to track include user engagement, features often used, conversion rates, and crash reports.

Prioritise UX-Related Metrics Over Money Metrics

If you are obsessed with tracking the number of in-app purchases made, you will never be able to answer your key question – How valuable do your features seem to your users?

The UX-related metrics will lead you to understand how your app is performing. However, this doesn’t mean you focus only on the crashes and the ANR (Application Not Responding) metrics. Your focus has to be on monitoring in-app user behaviour. It is this data that will help you make informed decisions.

Focus on Studying Cross-Platform Analytics

You will never be able to guess which device your users will use while making their purchases. More often than not, they tend to switch between websites and mobile apps. So, if you rely only on mobile analytics, you may be making a huge mistake.

It is cross-platform analytics that will help you focus on the bigger picture. This will inform you about the features driving conversions and what stops your users from making their purchases. Here are a few things you can do while studying cross-platform analytics:

  • Find out how your users are interacting with your mobile app and website.
  • Identify the features that they are using.
  • Check how much time they spend each session.
  • Find out why and when they switch devices or cross platforms.
  • Identify the stage in the funnel where your users convert

Make Sure Different Teams Track Different Metrics

There is no benefit you can expect if all your teams are tracking just one set of companywide metrics. The metrics that seem relevant to your product team might seem useless to your marketing team. Collaborate with your teams to determine which metrics seem most appropriate. Make sure they get the data that they need.

Make Sure all Teams Have Access to Mobile Analytics Data

None of your mobile analytics best practices will be used if your mobile analytics data is inaccessible. Everyone needs this data to make informed decisions in their respective teams. Make sure this data can be forwarded in the correct format.

Try Not to Digest Mobile Analytics at Face Value

Mobile Analytics is about more than just tracking metrics. It is also about using this data to improvise app development.

It all depends on how you interpret the data that you get. Any biased approach here can limit your ability to make informed decisions.

Talking about biases, here are a few types of biases you need to be aware of:

  • Confirmation bias: In this type of bias, you have a hypothesis that you need to confirm by seeking, interpreting, and recalling data. In your attempt to confirm your existing belief, you fail to consider alternative possibilities.
  • Narrative fallacy: This is the kind of bias that makes you create narratives around the data you have gathered to explain those data points. You only make casual interferences since you are not digging deep into that data.
  • Backfire effect: If the data does not align with your existing belief, you tend to doubt the credibility of that data. This is called the backfire effect.
  • Bandwagon effect: As the name suggests, this bias is all about interpreting data in a particular way only to copy others.

A curious mindset is highly essential if you need to overcome such potential bias. Don’t just accept the data at its face value. Always ask ‘why’ and dig deeper into why the data says whatever it is saying.

Track Both Numerical and Behavioural Data

Tracking only numerical data can lead you towards making biased decisions, as it is one-dimensional. It identifies the problem, but it doesn’t help you get to the root of that problem. This is where behavioral analytics will help.

Behavioural data can help you analyse the problem in its entirety. It helps you find out what exactly is causing that problem and how it has impacted your users. You can collect behavioural data by interacting with your users regularly and tracking in-app User Interactions. Here are a few things you can try:

  • Watching Session Recordings – You can record sessions to find out how your users interact with your app, right from when they install it till they quit. This will help you understand why and at what stage they abandon your app.
  • Tracking Navigation Paths – This will help you monitor your user’s journey throughout the purchasing process. It will help you understand their confusion and identify the reason behind their app abandonment.
  • Using Touch Heatmaps – This can help you determine which features are grabbing your users’ attention. You can gather data by going through user gestures while they are interacting with your app.

The Conclusion

Many such mobile analytics best practices can help you collect the correct data and use it correctly to make the best decisions. Nevertheless, one thing you need to remember here is to take your users’ consent before collecting their data. By respecting the privacy of your users, you will gain their trust, which will take you a long way towards your success.

References:

https://www.smartlook.com/blog/mobile-app-analytics-best-practices/

https://blog.prototypr.io/5-ways-to-track-user-behavior-in-your-mobile-app-97cc9ac04151

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