Mobile App Analytics: The Top Metrics You Need and Why

The Benefits of Accurate Mobile App Analytics Metrics

Analytics tools that give product managers (and others) a complete look at what users are doing (and why they’re doing it) are indispensable because they allow you to make informed decisions on where to invest your resources.

Here are just a few things you can do with a tool that gives you accurate analytics from your mobile app:

• Build a smart product roadmap. When you know every detail of how your customers behave, you can identify pain points and prioritize fixes. 

• Compare mobile analytics vs. desktop analytics. A good product analysis tool will show you any gaps that exist between your mobile and desktop experiences, along with the different ways users navigate each. 

• Discover which features users engage with most often, and where they’re experiencing friction. When you know what keeps bringing users back to your app, you can optimize these experiences or build in new and similarly engaging ones. It’s very important to be able to identify UX gaps, logjams, and areas where users are dropping out of your funnel.

• Evaluate success of new product launches. Did that new product feature work the way you expected it to? Good mobile app analytics will give you an immediate answer.

• Forecast revenue. Once you know the exact ways your app is (or isn’t) providing a seamless experience for users, you can focus on measuring the key metrics below to better forecast your revenue and set higher goals.

Even if users aren’t experiencing any obvious friction in your product, knowing how they use your app can open doors to new ideas that may enhance their experience further. Furthermore, when you have access to all user behavioral data, you can build sales and marketing strategies targeted at specific groups of users who behave a particular way.

Interested in behavioral analytics for mobile? Read our guide to see how to prepare!

The Top 20 Mobile App Analytics Metrics You Should Be Measuring

There are numerous mobile app performance metrics that are helpful to measure, but we’ve gathered some of the top ones that all app developers should pay close attention to. Many of them are indicators of user engagement and are helpful in forecasting user retention, user acquisition, and revenue.

App Downloads

It might help to think of a download from the App Store, Google Play, or the web as your first conversion for any given unique user. App download data for iOS and Android typically includes new downloads and re-downloads per user. If you’re publishing mobile apps to the above platforms, you’ll have easy access to download data either in App Store Connect or Google Play Console, but it can also help to have a third-party platform that tracks more granular information.

While knowing your app’s download count can give you a pulse on how many people you’re reaching via marketing campaigns or word of mouth, it won’t give you any data on how often people are actually using the app. 

Want to know why Google isn’t the best place to get your mobile analytics? Read our article here.

Installations

Installations are often a part of app usage metrics and typically happen automatically after a user downloads a mobile app. When you’re measuring installation data, you’ll typically get the number of installs your app has per user ID and per unique device. Install data can also include re-download on the same device, downloads to multiple devices, and family-sharing installations. As with download count, it helps to track net new installs vs. re-downloads/re-installations for the same user and will help you gauge brand and product awareness.

Registrations

When a user actually registers on your platform, it’s an entirely different type of win. Typically, a user will provide you with an email address at the very least. They’ll be more likely to buy what you’re selling and make purchases through your app—always a good sign for the bottom line. You can also use registration data to market other products!   

Subscriptions

Often, revenue is driven by subscriptions to an app. Your publishing platform will likely give you an overview of this sales data, including the daily number of active paid subscriptions, data on overall subscription performance, cancellation reasons, and more. In addition, if you can measure how long the average user takes to subscribe, it can help you predict—and perhaps influence—user behavior down the line.

App Crashes

Apps are likely to crash eventually for one reason or another. When users opt in to send you crash data, your app publisher will create logs that you can access using development programs like XCode, Google Android Studio, or others.

Ideally, you’ll want to review crash logs in a way that shows you a full backtrace of events that led to the crash. When you know the cause of app crashes, you can improve your app’s performance, which can ultimately help you retain users and ensure app success.

Load time/latency

People don’t like to wait, and when your app takes forever to load, you risk losing them! You can track load times using developer tools like XCode, Google Android Studio, or third-party plugins.

Load time isn’t limited to when you start the app. It also refers to any latency (or delays in time) each screen takes to launch after taking an action. This metric boils down to helping your users avoid frustrations.

Upsells and purchases

Upsells happen when a user makes an in-app purchase of any sort. Purchases don’t just include subscriptions. Depending on the app, they can include premium features, new upgrades, eCommerce merch, and more.

Depending on how you set up tracking for purchases, you can measure the amount of time each user takes to buy something, along with the average revenue per user (ARPU). The more purchase data you have, the more you can design your app to facilitate revenue growth.

User growth rate

This general key performance indicator (KPI) can help you measure how much both your user base and your consumer base is growing or shrinking.

You can calculate it easily:

((Present # of Users - past # of users) / (past x of users)) × 100

Again, this KPI tracks back to your bottom line. For social media companies, it can also be a key indicator for projecting ad revenue.

Sessions data

You can consider each time a user opens and engages with your app a session. Note that simply having an app open doesn’t give you a good benchmark of how your app is doing. For that, you need data about actual interaction with the app.

While expectations for sessions data can vary, you should consider measuring the following:

• Sessions per user. This measures the number of times an average user has been actively using your mobile app. You can calculate it by dividing the number of sessions over a period of time by the total number of users.

• Session length. This indicates how long users’ sessions last. You can calculate individual session lengths by subtracting the time when the app was launched from the time the user becomes inactive. You can then use the results to find average session length. 

• Session intervals. This is the time between two sessions for the average user—a metric that can help you track your users’ patterns in usage and engagement. Once you calculate the times between each of your users’ sessions, you can calculate average session intervals by dividing the total session interval time by the number of sessions.

• Session depth. This metric shows you how close a user comes to performing a targeted action (i.e. a purchase, a CTA click, etc.) before exiting the app. This KPI can give you key insights into your user behavior, including when and where they’re straying from your intended path.

Daily active users (DAUs)

This metric shows the frequency with which unique users engage with your mobile app. Generally, it’s a good indicator of the value of your product—if people are using it every day, it’s safe to assume they’re gaining value from it. This metric is especially important for SaaS companies because it’s usually a key indicator of growth and retention. 

When measuring this metric, it’s important first to decide what an “active user” is. Typically, this refers to any user who takes an important action in your app, such as tapping a “like” button, making a purchase, or sharing a comment. This can be a more helpful metric than simply measuring how many people open your app each day.

Monthly active users (MAUs)

Similar to DAUs, this metric (measured by the month) tracks the frequency with which unique users engage with your mobile app. Again, it’s essential to determine what an “active user” actually is.

Once you do—and once you’ve tracked them over time—you can calculate the DAU/MAU ratio by dividing the former by the latter and multiplying by 100:

Ratio = (DAU/MAU) x 100

Customer acquisition cost (CAC)

This metric measures the average amount of money you spend on user acquisition. As such, it tracks directly to your company’s bottom line.

Your CAC metric can be very helpful in determining how effective your sales and marketing strategy are. Ultimately, it’s about making sure the amount being spent to acquire new users is worth the revenue they generate. To calculate CAC, simply divide the total cost of marketing and sales activities by the number of users who join (and engage with) your platform. 

CAC = Total cost (marketing + sales)/number of new customers

Retention rate

In a world that’s saturated with mobile apps, you’re going to want to know how well yours is keeping users engaged. This metric is one of the core AARRR “pirate metrics.”

With retention rate, you’re measuring how “sticky” your app is for users. Do they use the app every single day? Once per week? Once every few months? When you have a high retention rate (and when more and more users start using your app consistently), it’s a great indicator of total revenue growth over time.

Calculating retention rate is simple. Just choose a particular time period to measure from, and divide the number of continuing users on the last day of the period by the number of users you had on the first day of the period.

Retention rate = number of continuing users / number of customers you started with

Customer lifetime value (also CLTV, CLV, or LTV)

This metric measures the amount of money your average customer spends on your mobile app over the course of their time using it. But why does it matter?

First, it will help you figure out your CAC. Second, it will help you be able to quickly target users who have spent the most money on your mobile app over time. User segmentation (dividing your users into distinct groups based on shared characteristics) can make marketing campaigns easier and help you more easily predict revenue.

To calculate CLTV, multiply the average order value (AOV) by the average frequency of purchase and the average customer lifespan. For example, If the average customer makes two $40 purchases each year and does this for five years, your CLV is $40 x 2 x 5 = $400.

CLTV = AOV x purchase frequency x customer lifespan

Average revenue per user (ARPU)

This metric measures the average amount of revenue each user brings to your company during a specific time period (unlike CLTV, which measures average revenue over their entire relationship with your product). This revenue can come from all the different types of in-app revenue generators your brand offers, including subscriptions, upgrades, merchandise sales, paid downloads, ad impressions, and more.

You can calculate ARPU by dividing your total lifetime revenue by the number of active users you have.

NPS and CSAT scores

Typically measured on a 10-point scale, these metrics track the overall perception and satisfaction with your mobile app, brand, user experience, and services. NPS scores measure general satisfaction with your product over a long period of time, and CSAT scores measure shorter-term customer satisfaction (for example, a customer’s satisfaction with a particular service, product, or interaction).

The goal with NPS and CSAT is to track how happy users are with your app—and how likely they are to spend their hard-earned money on it in the future. 

You can calculate NPS by finding the difference between the total percentage of people who would recommend your brand and the total percentage of those who wouldn’t.

NPS = total % of promoters - total % of detractors = NPS

You can calculate your CSAT score by adding up all the promoter responses, dividing the sum by the total number of responses, and multiplying the resulting number by 100.

CSAT = total of promoters / total responses × 100

Behavior funnels

Once a user downloads your app, are they using it the way you’re intending for them to? Are they taking actions that result in revenue for your business?

By analyzing behavior flows—the routes a user takes to get from point A to point B in your app (with B ideally being your intended result)—you can identify whether the design of your app is aligned with your business goals. Together, these actions create a funnel of behaviors that allow you to examine how many users achieve your intended steps vs. how many drop off (or churn) along the way.

Churn/drop off rates

If you’re losing users midway through their app journeys, your product may not be offering them the experience they’re looking for. Churn rate is a way you can measure this. It captures the percentage of users who stop using your mobile app over a period of time. The reason churn rate matters is because it gives you an instant pulse on your ability to retain customers and generate revenue.

To calculate your churn rate, find the difference between the number of users you have at the beginning of a particular time period and the number you have at the end. Then divide this by the total number of users you had at the beginning of that timeframe. 

Churn rate = (number of users at beginning – number of users at end)/number of users at beginning

Cohort analysis

A cohort is a group of users who behave in similar ways and share certain characteristics. You can have many cohorts within your user base and group them in different categories (i.e. by location, demographics, time they signed up for your app, etc.). 

Studying cohort behavior is a fantastic way to gain deeper insights into user behavior than you would get from a top-level analysis. Cohort analysis can help you identify new marketing channels, improve app conversion rates, identify user life-cycle patterns, find pain points that cause churn, improve LTV, and more.

To do cohort analysis, look at a certain behavior in your analytics tool, then see how usage changes when looking at the actions of different cohorts.

App Store optimization (ASO)

Apple’s App Store and Google Play are two major mobile app stores, and optimizing the information you share about your app on these platforms is a key way to get new users. Just as important as gaining these users is measuring how your app is performing with consumers. Are they downloading and installing it? Are they engaging with it? Are they giving it high ratings?

Here are five things to measure when analyzing your app’s performance in app stores:

• Content and keyword optimization. After using targeted keywords and phrases in your product descriptions—ideally ones that will ensure your app displays at the top of every user search for those terms—take time to track user journeys for each keyword or phrase searched. This will help you understand which keywords or phrases are giving your app the most visibility.

• Ratings. The better your app rating is, the more people will be inclined to download your actual app. Be sure to regularly prompt your users to rate your app so you can build up your ratings (and use them to gauge app performance and functionality).

• App store ranking. If you’re building an app people like, your store ranking should rise over time. This number is very important, because the higher your app ranks, the more visibility it will get, opening doors to higher pricing and revenue possibilities.

• Reviews. Positive reviews are a great engagement metric and a huge factor in converting potential users. Not only do they build trust, but they also contribute to an app’s overall ranking and visibility. Furthermore, the more you study your reviews, the better you’ll get at identifying your app’s weak spots. All types of review insights are helpful, and remember: if someone took the time to review your app, it means they were engaged with it enough to care. That counts for something!

• Views to installs. This refers to the number of times a potential user viewed your app before installing it (and hopefully registering as a customer). If you have a low number of views to installs, great! Your marketing and app description are doing their jobs. If your number is high, consider how you might improve the way you present your app.

Getting Reliable Mobile App Analytics Metrics With Heap

If your goal is to accurately track the metrics we’ve outlined above, you need a tool that makes that easy to do. That means it should capture all the data, keep it organized, combine it from different platforms, and make suggestions about what else you should look at. That's why Heap is the ideal tool for tracking these metrics and keeping them healthy. Heap has the largest range of SDKs available, including Xamarin and Flutter.

Because clean, accurate information is key, Heap also makes it easy to streamline data collection in a way that helps you avoid broken tracking, inconsistent tagging schemas, and poorly configured events. It also helps you combine data from different platforms into a single event or property so you don’t double-count events and muddy your data. Heap also gives you heatmaps and session replay.

Finally, when you have a data science layer like the one Heap provides, you can see how users behave across mobile and web properties and platforms—a big step up from simply using a platform like Google Analytics. This can help you figure out where to invest, which platforms are performing well and why, and whether there are any disconnects between your mobile app and web experiences. 

Learn more about Heap for Mobile here.