Blog Mobile app analytics: Key metrics and best practices for optimal results

Mobile app analytics: Key metrics and best practices for optimal results

App marketers rely on their data to find ways to streamline the user funnel and optimize app performance. App analytics is also essential to growth by improving user acquisition and user engagements performance. This is why almost a third of marketers would spend a budget increase on data analytics. In this guide, we will define common terms related to app analytics, explain why this process is essential to app marketing and look at how tracking different metrics helps you achieve your company goals.

What is app analytics?

App analytics is the accumulation and analysis of data gathered from mobile app and mobile web activity. Carly Fiorina, former CEO of HP, says “The goal is to turn data into information, and information into insight.” Your data can be used to better understand the user journey and make informed decisions that will optimize metrics such as engagement, churn, conversions and downloads. It is also used to learn more about app performance and identify common problems with an app’s user experience.

Why is app analytics important?

Once developers have launched an app, it is important to know ways in which that app can be optimized for growth, performance and customer satisfaction. There are more than 2 million apps available on the App Store and 2.87 million apps on the Play Store, and app analytics provides critical opportunities to ensure your app succeeds in this competitive market.

The insights gained through app analytics are key to understanding your users and essential to your company’s growth. Without app analytics, you won’t be able to identify the best ways to spend your resources and push towards your targets. For example, it shows you when users churn, the average revenue per user (ARPU) for each campaign, and your users’ lifetime value (LTV). This enables you to make data-driven changes to your app for greater success.

Which metrics are useful for app analytics?

There are many metrics you can focus on to improve your performance, so it’s important to define your KPIs and use those to identify which metrics should be your focus. You will also need to consider how different metrics can be used together to be informative. To get started, here are examples of key metrics and how they are useful for optimizing user acquisition and user engagement.

4 useful metrics for user acquisition analysis

  • App attribution: This will show how your users were acquired, whether that be through marketing spend or organically. App attribution informs you of the performance of a campaign, while event tracking can show you the value of those users (more on this later). This gives you the information needed to know which campaigns were successful and which ones are not worth your investment. You can learn more the importance of app attribution here.

  • Cost per acquisition: This will tell you how much was spent to acquire each user. It can be calculated by dividing the total cost of a campaign by how many users were acquired as a result of it. This is a critical metric that enables you to calculate ROI and identify the most cost effective way to acquire new users. Adjust’s global benchmarks show that the average cost per install was $1.37 in 2019, although this figure will be different when filtered by app vertical and region.


  • Average revenue per user (ARPU): This tells you the average revenue generated for every user acquired. This is a smart way to estimate whether you are on track to hit your revenue targets. This metric is also an essential component to LTV (lifetime value) calculations. However, it is important to note that ad whales can make your ARPU misleading.

  • Lifetime value (LTV): This is how much a user is expected to spend before they churn. You need to know your users’ LTV because it informs you how long users must be active before they have generated their maximum revenue. LTV also tells you how much your app can expect to make over the coming months.

Once you have calculated your users’ LTV, you can focus on ways in which it can be optimized. This involves identifying why users churn and what would make them spend more in your app. The LTV of different user groups can also be compared to learn which users are cost effective. In the video below, Michael Paxman, Global Product Communications Manager at Adjust, explains how to go beyond simplistic LTV calculations and learn how users are generating revenue without spending money themselves. For example, by tracking the right in-app events you can learn which users are inviting friends to your app or increasing engagements by sending frequent messages – both important events that are important to your app’s success.

You can also learn more about LTV testing, validation and error analysis here.

5 useful metrics for user engagement analysis

  • Events: Tracking events will provide insight into user behaviour related to in-app activity. For example, you can track events such as purchases, page visits and when a user has added an item to their cart or completed a level. By tracking every stage of your user funnel, you can learn ways to optimize this process.

  • Installs: A downloadbecomes an install the first time the user opens an app. Knowing how many users have installed your app is essential to learning which campaigns have performed best.

  • Sessions: This is when a user opens and engages with your app after install. You need session data to know how often users are opening your app and how a user is moving through your user funnel. By viewing sessions by device, location and time, user metrics also show how, when, and from where your users are accessing your app. For example, you will learn how many sessions it takes the average user to complete a purchase. This metric will also tell you your daily active users (DAU) and monthly active users (MAU).

  • Retention: This is the measurement of how many of your users return to your app. You can use retention rates to observe when users will churn and at what point they should be reengaged. You can also use retention rates to detect ways in which your app isn’t performing well. Our study revealed that 26% of users are retained on Day 1, and this drops to 11-12% by Day 7. The average retention rate at Day 30 is 6%. However, retention rates will depend on the app vertical.

    You can also use retention rates to learn which campaigns are giving you users that are most valuable over time. It may not be the campaign that delivers the most downloads that is generating the most revenue and allowing you to reach users that stay loyal to your app.


  • Churn: This will tell you how many users have abandoned your app. This means that a user has either uninstalled the app or is no longer recording sessions in your app. This is a critical metric that allows you to determine LTV and identify reasons a user will typically lose interest in your app. For example, if you have a high churn rate after the first session, you may have critical issues with your onboarding experience or technical issues with login.

App performance analysis

It’s also important to use mobile analytics reports to test the performance of your app’s functionality. For example, it’s important to know how often your app crashes during a session, the speed of the app and any network errors that are ruining the user experience. Listening to user feedback and reading reviews for your app in the App Store are great ways to know whether users are satisfied with functionality.

6 mobile app analytics best practices

  1. Define every step in your user journey

    Your user journey (or user funnel) maps out how a user will be guided from install to purchase. It’s important to define the steps in this journey so you can track the right events and start learning where users churn. Knowing this is the first step towards optimizing your user funnel and ensuring your users will generate revenue for your app: by looking at the conversion rates from step to step, you can identify the area of improvement that will result in increased revenue.

  2. Only measure what matters to your goals

    With so many metrics from which you can learn, it’s essential to identify which measurements are critical to your performance optimization. Without honing in on the most important metrics you risk wasting time and money on less impactful optimizations.

    Andrew Chen, General Partner at Andreessen Horowitz (and former Head of Rider Growth at Uber) has the following advice: “Don’t build metrics that aren’t going to be part of your day-to-day operations or don’t have potential to be incorporated as such. Building reports that no one looks at is just activity without accomplishment, and is a waste of time.”

    Once you have defined your company goals and know the steps in your user funnel, you can use this information to understand which metrics will provide critical insights. Less can be more in this case, meaning you can set a clear plan of action as a result of your analysis. Outline the questions that are most important to you and ensure you are tracking everything you need to answer those key questions.

  3. Test your app on as many different devices as possible.

    It’s important to test your app on many different devices so that performance can be reviewed for every potential user. This will ensure customer satisfaction and can also help with your analytics. Test thoroughly and ensure your app performance isn’t preventing you from reaching your targets or damaging your reputation.

  4. Prioritize your onboarding experience

    No matter how great your app is, users need adequate onboarding to help them navigate your app and know how to get the most out of their user experience. Without this, you are failing to introduce customers to the true value of your product. This is true for all app verticals except hyper-casual games, which are designed to allow users to tap and play with minimal onboarding. You can improve your onboarding experience by making sure the first action is easy to achieve, using persona-based onboarding and simplifying your sign-up process.

    Andrew Caplan, Growth Team Lead at Wistia, explains how his team looked at the behavioural patterns corresponding to long-term retention. “The most important thing we've done to improve our user onboarding was to define our activation metric and get serious about tracking the inputs to that metric. Agreeing on what a successfully "activated" account looked like, and understanding all the individual actions to get there, allowed us to take our new user onboarding to the next level.” This enabled his team to prioritize actions based on their definition of success.

  5. Use A/B testing to improve your funnel’s conversion rates

    A/B testing is a great way to test the effects of a change in your user funnel. It is particularly effective because you are isolating a change and comparing it to a control group, giving you confidence in your results before implementing a change.

  6. Use app analytics to find new initiatives

    In addition to improving upon key metrics, you should also use app analytics to learn new ways in which your app can grow. Matin Movassate, Cofounder and CEO at Heap Analytics, says “Analytics software is uniquely leveraged. Most software can optimize existing processes, but analytics (done right) should generate insights that bring to life whole new initiatives. It should change what you do, not just how you do it.”

  7. Use industry benchmarks to inform your targets

    Industry benchmarks are a useful way to gauge how your app is performing. Adjust’s global benchmarks, for example, give insight into user behaviour prior to install and app engagement metrics. This can be filtered by vertical, region, platform and acquisition type. It’s important to look at industry benchmarks per vertical because user behaviour will be different depending on the app’s function.

To learn more about app analytics, read how Smule uses Adjust to enrich data. You may also be interested in our guide for choosing the best attribution tools and everything you need to know about A/B testing for mobile apps.

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