What is Mobile Analytics? A Primer for Product Teams

Why is mobile analytics important? 

Understanding user behavior is the only way to improve your user experience. If you don’t know what folks like and dislike - what features they use and don’t use, how users find their way through your mobile app or site -  how are you going to make their experience better? The problem is, for many years this kind of user data was only available for web teams. Mobile teams, in comparison, were often left shooting in the dark.

Today, however, a host of analytics tools are finally able to give mobile teams the user data they’ve been looking for some of the benefits mobile analytics offers your business include:

• Improved user engagement: businesses can understand how users interact with their mobile platforms and optimize the user experience to boost engagement. 

• Increased retention: businesses can analyze user behavior and preferences to identify areas where users are dropping off or losing interest, and take steps to improve retention rates. 

• Data-driven decision-making: teams gather valuable insights into customer behavior and preferences, enabling them to make informed decisions based on real data rather than guesswork. 

• Better ROI on marketing spend: teams can track the performance of mobile marketing campaigns to identify what’s working well and what’s not, and adjust their strategy accordingly to improve ROI. 

• Competitive advantage: investing in mobile analytics can give a competitive edge by staying on top of customer trends and preferences.

Common challenges with mobile analytics 

Mobile analytics tools exist to analyze rapidly changing consumer expectations. Until recently, however, most mobile teams faced a host of problems with collecting and analyzing data. Here are a few that you should be aware of.

1. Data collection. Historically, collecting mobile data was a manual process. Each mobile platform had its own way of collecting data, and since the platforms changed often, teams had to keep updating their tracking methods.

2. Dirty data. As there were so many updates and folks had to regularly re-track the data, it became hard to know which data was trustworthy or not. Incorrect data can be harmful to overall business success.

3. Data volume. Mobile applications generate a vast amount of data, which can make it difficult to collect, store, and analyze it all effectively. 

4. Data integration. Integrating data from multiple sources, like social media and third-party mobile applications, can be a challenge because of the different formats and structures. This often left teams with incompatible data, which meant they couldn’t see what users did when they moved from web to mobile, or vice versa.

Mobile analytics vs. web analytics

Have you ever noticed how much more we expect from our phone apps compared to the websites we visit? With limited text space and different finger swipe commands, mobile websites are an intricate and interactive experience. Think about how often you scroll, zoom, type, switch between portrait and landscape, or even draw–all in one day. Now compare that to how you use your laptop. Chances are, your laptop receives far simpler commands, like typing and clicking, while also presenting everything on a bigger screen. 

Key differences mean businesses must measure an entirely different set of metrics for both mobile and web analytics. By tracking different metrics for each platform, you get a better understanding of user behavior, and can optimize your digital properties accordingly. Here are some common metrics that help differentiate your focus for both mobile analytics and web analytics. 

What are the right product metrics to track and optimize? Read our complete guide!

Where does Google Analytics fit in?

Google analytics can be a powerful tool for web analytics. But when it comes to mobile app analytics, it falls short–by a lot. That’s because it’s not as robust or user-friendly as other mobile analytics tools out there. It lacks important mobile-specific features that other mobile app analytics tools utilize. 

Learn more in our comprehensive guide to GA4.

How to get started with mobile analytics

Being able to understand mobile behavior and develop customer experiences tailored to your users’ needs will change the way you build products—forever! So how do you get started? 

To get a full picture of your users, you first need a tool that can automatically capture all behavioral data from mobile devices, all the time. Here’s a quick list of what to look out for when looking for a mobile analytics tool: 

• Automatically capturing all user data, across all mobile platforms. A single snippet grabs every click, swipe, tap, pageview, and fill — forever. There’s no need to rely on manual tracking. No need to choose what to measure. No need to wrangle engineers to write code.

• Integration with a web analytics platform, so you don’t have to modify your data to see what happens when users move from mobile to web and back.

• Automatic surfacing of unexpected user behavior, so you can optimize the real customer journey and continually iterate and improve. 

• Robust analytics, giving you the insights you need across the board to make data-driven decisions.

How mobile analytics solutions work 

A mobile analytics solution works by automatically collecting data from mobile apps and analyzing it to provide insights into user behavior and app performance. The solution typically involves incorporating a software development kit (SDK) into the mobile app, which tracks user behavior and sends data to the analytics platform. 

The platform then processes the data and provides metrics and reports for you to analyze–whether that’s user engagement, retention, conversion rates, and other important metrics. Mobile analytics solutions can also provide tools for A/B testing, user segmentation, and personalized messaging to help improve the user experience and drive better app performance.

What metrics can mobile analytics help you track?

Mobile analytics data can help track a wide variety of metrics related to user acquisition, engagement, and conversion within apps. Here’s a breakdown of some key metrics to track under user acquisition, user engagement, and conversion and purchase paths.

User acquisition metrics

• No. of app downloads: This metric tracks the total number of times your app has been downloaded from app stores.

• Cost per install (CPI): This metric helps you understand how much you’re paying to acquire each new user. It’s calculated by dividing the total cost of your user acquisition campaigns by the number of app installs.

• App store optimization (ASO): These metrics help you determine how your app is performing in app store search results. 

User engagement metrics

• Daily active users (DAU): This metric measures the number of unique app users who engage with your app on a daily basis.

• Feature adoption: This metrics tracks how many users are using specific features, and how many are doing so on mobile vs. web. 

• Session length: tracks the average length of time that users spend in each session of your app

• Retention rate: Helps you understand how many users are returning to your app over time.

Conversion and purchase paths within apps metrics

• Click-through rate (CTR): This metric measures the percentage of users who click on a specific call to action within your app, such as a button to make a purchase.

• Conversion rate: measures the percentage of app users who complete a specific action, such as making a purchase or signing up for a subscription.

• Average revenue per user (ARPU): helps you understand how much revenue your app generates per user on average. Calculated by dividing the total revenue generated by your app by the total number of users.

How your teams should use mobile analytics

Mobile analytics serves more than just your mobile development team. Here’s a breakdown of how different teams will use your mobile analytics data: 

Product teams

Product teams will use mobile app analytics to understand how users are engaging with your app and to identify areas for improvement. They may measure metrics such as user retention, session length, and user feedback to guide decisions around new features or updates. They’ll also use mobile app analytics to track the success of new features and to optimize the user experience.

Customer success / support teams

Customer success and support teams will use mobile app analytics to understand common issues that users are experiencing within the app. The metrics that matter are user feedback and app crashes, so they can identify trends and prioritize bug fixes or feature improvements. CS teams may also use mobile app analytics to track user adoption of new features or updates and to identify users who may need additional support or training.

Sales and account management teams

Sales and account management teams will use mobile app analytics to understand how users are interacting with their app and to identify potential upsell opportunities. They may look at metrics such as user engagement and app usage patterns to identify users who may benefit from additional features and services. 

Marketing teams

Marketing teams will use mobile analytics to track the success of different marketing campaigns to understand user acquisition and engagement patterns. They may look at metrics such as cost per install (CPI), conversion rate, and click-through rate (CTR) to optimize campaigns.

Executive leadership

Executive leadership will use mobile analytics to gain a high-level view of app and product performance in order to guide overall strategy. They may look at metrics such as user acquisition, retention, and revenue to understand the health of the business and to identify areas for growth. 

Mobile analytics case studies

Alo

Yoga apparel company Alo Yoga wanted to see a more detailed story from customer acquisition to site browsing and purchase. See how they solved the problem!

Pocketsuite

Pocketsuite wanted to better understand user segments while also increasing mobile activation and customer retention. What did they do? Find out here.

Hellosign

HelloSign is a cloud-based electronic signature tool. The team wanted to improve tracking and analytics and create a more data-driven culture. How did they do it? With mobile analytics!

The best mobile analytics solutions compared 

By nature, mobile analytics tools are all different. Learn which one is best for you by seeing a side-by-side comparison of the key competitors in the space.

1. Heap

Heap is a product analytics platform that gives your product, marketing and customer success teams access to 100% of your customer data—sign ups, segments and cohorts, checkout flow, device type, pageviews, and more. Session replays are fully integrated with this captured data and cued to the exact moments you wish to examine. Additionally, a powerful data science layer scours your dataset to automatically uncover the insights that lead to the biggest business results—even on untracked events.

Heap has more SDKs than other solutions, including Xamarin and Flutter.

Top features:

• Autocapture collects all of your data, all of the time

• Integrated session replays guide you to key moments in the user experience

• Heap Heap Illuminate helps pinpoint hidden friction points and opportunities

• Heap Connect exports to your data warehouse

Top use cases:

• Perform cross-channel CRO

• Encourage positive experiences that make your products sticky

• Increase engagement by leveraging user data to build stronger products

• Improve retention across all stages of the customer lifecycle

• Get definitive answers to make better decisions and achieve real impact

2. Mixpanel

Mixpanel is an analytics platform that helps you measure and track user behavior across devices. While Mixpanel offers the ability to track specific events, teams will have to manually configure those events similarly to the way Amplitude operates. If you’re willing to devote expensive engineering resources to maximize your investment in Mixpanel, it can be a good alternative — particularly for massive organizations that have high volumes of transactions.

Top features:

• Behavioral analytics

• Interactive reportings

• Dashboards

• Scalable infrastructure

Top use cases:

• Understand how users navigate your digital properties

• Increase engagement, signups, and conversions

• Analyze lots of microtransactions

3. Amplitude

Amplitude is a product analytics platform that enables you to track user behaviors and events as they navigate your digital properties. Unlike FullStory and Heap, Amplitude requires a nontrivial amount of manual configuration to get the platform up and running. The platform also forces users to tag events manually, which drains precious team resources.

Top features:

• Behavioral analytics

• Secure collaboration

• Customizable data structure

Top use cases:

• Improve the user experience

• Increase engagement and conversions

• Understand the onboarding flow

To learn more, read all about alternatives to Amplitude.

4. Fullstory

Fullstory is a digital analytics platform that helps businesses understand how customers interact with their websites and mobile applications. Upon install, FullStory captures user sessions, including mouse movements, clicks, scrolls, and keystrokes, as well as device and browser information. The platform enables companies to monitor user behavior, analyze customer journeys, identify opportunities for improvement, and fix issues that may be causing friction in the user experience.

Top features:

• Analyzes conversion funnels

• Detects signals of friction in your UI

• Visualizes aggregate user trends over time

• Heatmaps

Top use cases:

• Pinpoint where sales are made or lost

• Earn customer loyalty

• Deliver trusted services

Still interested? Check out our complete guide to Fullstory Alternatives!

5. Pendo

Pendo is an analytics platform that helps product teams increase adoption of software solutions across web and mobile devices. While Pendo provides decent insights into employee and user onboarding, it lacks the robust analytical capabilities needed to really put your fingers on the pulse of user sentiment.

Top features:

• Behavioral analytics

• Self-service support

• User feedback collection

Top use cases:

• Onboard new users

• Increase user engagement

• Reduce customer churn

Ready to learn more about mobile analytics? 

Get the insights today to transform your user mobile experience with Heap.