Best Practices for Mobile App Analytics

So, you have developed and launched a mobile app! Great! But your app development journey does not end there. Smartphone users are expected to grow from 6.3 billion today to over 7 billion in just 4 years. Mobiles consume over 70% of watch time, and over 90% of people spend time on mobile apps. (Data source: https://rentechdigital.com/swipecart/blog/t/mobile-app-analytics).

Nearly 5 million mobile apps are available today, with approximately 30,000 added monthly. (Data source: https://www.statista.com/statistics/1020964/apple-app-store-app-releases-worldwide/). According to Statista, an app user spends an average of 5 minutes on an app session. Therefore, if you want your user to return to your app, you must provide them with the best possible experience within this short time.

The only way to ensure your app is visible to users and is used regularly is to improve the user experience continuously and engage users to keep them locked into using your app. And how do you track and improve your app user experience? By using mobile app analytics.

Mobile app analytics

Mobile app analytics are tools and processes that convert raw data received from your app users into actionable insights by tracking, observing, and mapping user behaviour on the app. Mobile app analytics can help you get several insights, such as:

1. User behaviour data
2. Impact of new features
3. New opportunities for app development
4. Refine and improve the User Experience (UX) of your app

Mobile app analytics use a combination of quantitative and qualitative research methods to help you develop a best-in-class mobile app.

Main metrics for useful data analysis

You can pull out and evaluate any number of metrics to improve your app. However, the following metrics are used across most industries and categories to set up mobile app analytics:

1. App attribution: to check if users were acquired organically or through marketing campaigns
2. Average Revenue Per User (ARPU): to see if your average user is generating enough revenue for your app
3. Cost Per user Acquisition (CPA): to calculate the ROI of your marketing campaigns and determine the most cost-effective way to get new users
4. Life Time Value (LTV): the total revenue expected from a user before they drop out

Other metrics include backend data such as the number of times your app crashes during a session, app speed, and network errors that can affect the user experience.

Best practices for mobile app analytics

As an app developer, you must make sure you use globally accepted best practices for mobile app analytics. This will help ensure that you collect and use the most relevant data used by app developers worldwide and can provide a user experience on par with the best apps in your category.

There are several best practices, but the following are the gold standard of best practices for setting up your mobile app analytics:

1. Clearly define each step in your app user journey
   • The user journey shows how your user is taken from app download to purchase
   • You can determine the conversion rates at every stage of the user journey and check at which stage the user tends to drop out
   • This will also help you optimise your app to generate the maximum revenue possible
2. Test your app on as many devices as possible
   • With millions of smartphones in use across the world and new models appearing regularly, it is important to make sure that your app functions smoothly on all devices
   • Check your app functions on as many devices as possible so that you can review performance on all operating systems
   • It will also help provide the best user experience to customers across a wide spectrum
3. Prioritise data that improve the user onboarding experience
   • Your users must know how to use your app and get the maximum benefit out of it
   • Without adequate understanding, your users will not appreciate the true value of your app
   • Measures such as a simple onboarding process make all the difference in providing a smooth and quick acquisition of potential users
   • Your mobile app analytics setup must always provide qualitative and quantitative data on the user onboarding process.
4. Measure what matters
   • There can be plenty of data points to measure in mobile app analytics
   • Not all data points are necessarily relevant to your app
   • You must identify measurements that are important to optimise your app user experience
   • This will help save time and money by avoiding unimportant information and non-critical improvements to your app user journey
5. A/B testing to improve user conversion rates
   • Your user experience funnel is a function of your app customer’s preferences
   • By implementing an A/B testing system, you can test the effects of a modification in the user funnel
   • This will help you understand how effective the change could be before letting it go live on the app
6. Use industry benchmarks
   • Your app is in a particular category that may have established players who have set benchmarks for comparison of apps within that category or industry
   • These benchmarks will determine if your app succeeds or fails
   • Every industry or vertical has users with different requirements, and your app must meet the benchmarks of that industry or vertical
7. App retention rates
   • The app retention rate is the number of users who return to your app in a fixed timeframe
   • Retention does not require any expense, while acquisition has a marketing cost
8. Daily Active Users (DAU)
   • The number of users using your app every day
   • Ideally, this number should not be viewed in isolation because the frequency of logging in depends on many factors
   • This benchmark works best when viewed together with user satisfaction rates and behaviour in the app journey
9. Average Revenue Per User (ARPU)
   • If your app is not making money, it could indicate dissatisfaction with one or more elements of the app
   • ARPU helps you determine the average Customer Life Time Value (CLV) of each customer
   • It helps in determining the usefulness of your marketing spend to acquire new users and retain them over a period of time

Conclusion

Mobile app analytics help you as the app developer improve your app’s chances of success by providing important and valuable insights into user behaviour. Mobile app analytics are very important in your overall app marketing approach.

As the app developer, you must identify best practices for your mobile app analytics setup relevant to your app industry and category and implement them as quickly as possible. You must also keep refining and improving your analytics setup to always get the most relevant data.