Seven best practices for industry-leading mobile app analytics

App marketers rely on data to streamline the user funnel and optimize app performance. That’s why tracking app analytics on both iOS and Android is essential to improving user acquisition and engagement. But let’s start from the beginning.

What is mobile app analytics?

App analytics is the accumulation and analysis of data gathered from your mobile app. This includes data from platforms which lead users to your app, such as web pages and connected TV (CTV).

Why do you need mobile analytics?

In a competitive market with over 2.2 million mobile applications available on the Apple App Store and 3.5 million apps on the Google Play Store, the insights gained through app analytics are critical component to success.

Once you’ve launched an app, it is important to know how that app and its marketing campaigns can be optimized. The analysis of performance data is used to better understand the user journey and make informed decisions. These decisions are intended to optimize engagement, churn, conversions, downloads, and more.

Without app analytics, developers cannot clearly identify potential problems with their app and/or campaigns, nor can they identify corresponding solutions. In turn, this leads to inefficient use of marketing time and budget.

There are many metrics you can use to improve your performance. When determining which metrics are useful for your app analytics needs, it’s important to define your key performance indicators (KPIs) first. Then, you can base your primary metrics off of those KPIs. You will also need to consider how different metrics can be used together to provide the most comprehensive picture. Here are some examples of metrics that best correspond to KPIs.

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 most successful and which ones are not worth continued investment.
• Cost per acquisition (CPA): This cost model 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 return on investment (ROI) and identify the most cost effective way to acquire new users.
• 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. The LTV of different user groups can also be compared to learn which users are cost effective.

5 useful metrics for user engagement analysis

• In-app events: Tracking events will provide insight into user behavior related to in-app activity. You can track events such as purchases, page visits, when a user has added an item to their cart, or the completion of a level.

• Installs: A download becomes 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. Viewing sessions by device, location, and time, shows you 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 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 research shows that roughly 26% of users are retained on Day 1, and this drops to 11-13% by Day 7. The average retention rate at Day 30 is 6.5%. However, keep in mind that retention rates will depend on the app vertical.

  You can also use retention rates to learn which campaigns are delivering you the most value over time. It may not be the campaign that delivers the most downloads that is generating the most revenue or reaching the most loyal users.

• 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.

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 may be causing a problem Listening to user feedback and reading reviews for your app in app stores are great ways to know whether users are satisfied with functionality.

Seven 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 your user journey is the first step towards optimizing your user funnel and ensuring your users will generate revenue for your app.

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 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 key metrics, you should also use app analytics to learn new ways in which your app can grow. Understanding how your users are interacting with your app, the features they love, and what goes unused can spur new ideas that in turn spur new features and initiatives.

7. Use industry benchmarks to inform your targets

   Industry benchmarks are a useful way to gauge how your app is performing. It’s important to look at industry benchmarks per vertical because user behaviour will be different depending on the app’s function.

Whatever metrics you choose to measure and include in your app analytics, you will need a partner to provide you with accurate date.

The ultimate mobile app analytics tool: Adjust’s Datascape

Adjust’s Datascape brings together all your data in one place. Gain insight into your user acquisition, run custom reports, form cohorts in a variety of ways to get your KPIs, and take advantage of our SKAdNetwork Dashboard to help make sense of SKAN data from Apple.

To learn more about app analytics, read how Dagangan uses Adjust to track the success of its UA campaigns. Also, explore A/B testing techniques to boost ATT opt-ins on iOS and enhance your analytics with data from these users.