Use Mobile Analytics to Transform Your Digital Product

What Is Mobile App Analytics?

Mobile analytics is the process of collecting and analyzing in-app data. This data gives you precise information about app performance and in-app user journey, letting you fix ineffective elements.

Mobile analytics is one of the key elements to improving conversions, retention, and user engagement. It’s the foundation of great digital products that engage target audiences.

How Does Mobile Analytics Work?

Mobile analytics software integrates with your mobile application to gather and analyze the data produced by users and the app itself. For example, an analytics tool can be embedded as an SDK into the code. You need different SDKs depending on the platform release of your app (e.g., iOS, Android).

Analytics lets you hypothesize, make assumptions, and evaluate experiments. It’s the key to refining and adjusting your product so that it matches the real-life behaviors that users display in your app.

With analytics, you know how users are using your app, what in-app actions they take, and what features they’re using (or not).

For example, you can check the completion of onboarding or how the buying process looks from the user’s perspective.

How Mobile Analytics Can Be Used to Build Great Products?

Because mobile analytics gives you granular data-based insight into a variety of processes and funnels, you know exactly what’s amiss within either.

Instead of rewriting a whole process or eliminating it from the app, you can look into analytics to pinpoint specific areas or steps in the process and adjust them based on your hypothesis.

In other words, mobile analytics yields hard numbers that can either back your assumptions or disprove them.

Think of analytics as the infamous smooth operator from Sade’s song: “He moves in space with minimum waste” — that’s exactly what you want to be doing with your mobile product.

The data from mobile analytics software lets you “see” what’s going on inside your app. The conclusions drawn from mobile analytics can be useful across all departments, from sales and marketing to product management and development.

You can combine your efforts in a cross-departmental fashion and align on goals inspired by data from analytics. This way, all teams work to polish the elements of the app and strategy that can be observed and measured in user metrics. As a result, the app becomes more refined, in tune with the user’s needs and behaviors.

Sample user actions and user behaviors that analytics can reveal:

• Unique users
• User logins
• App launches
• Crashes (caused by events/actions)
• Returning users
• Acquisition attribution
• Churn rate
• Stickiness (ratio of Daily Active Users to Monthly Active Users DAU/MAU)
• Information on operating systems, devices, user location

For example, you can analyze what happened in a certain process during the last 30 days. How many steps were completed? Or which steps were most problematic, causing a drop in successful process completion?

Mobile analytics will also tell you how long it takes users to complete an action. For example, how long does the buying process take? 

Over time, mobile analytics will reveal patterns and trends, giving you precise information on the length of every step in a process. This can help you eliminate or change ineffective steps or their elements.

For example, analytics might show that manual form filling is too cumbersome and causes users to abandon a whole process because of that single ineffective step. From this insight you can infer that an autocomplete/autosuggest option could decrease process abandonment.

Another metric you can track is retention. Analytics can show you when users take an action and/if they repeat it again in the future. You can specify retention within a select time frame, which can yield some actionable conclusions.

For example, if during 30 days user interest in a feature decreased, you can quickly start implementing mitigating strategies. Long-term analytics can also tell you the potential loss or increase in interest in a given feature or the app itself.

For mobile analytics to be useful, however, you have to know what metrics to measure and how to read them in the context of a specific app type. For example, which in-app behaviors and analytics results are acceptable and which should be worrisome in a mobile commerce app.

Analytics Give You Actionable Insight

The point of analytics is to answer business-focused questions equipped with real data and numbers — for example, how many sellers on a mobile commerce app have posted an offer?

If a feature or the app has no traction, analytics can help you decide whether you should pivot or abandon your idea before any more money is invested.

Note: Mobile analytics isn’t devoid of errors and always has to be read by a specialist with experience. It’s also good practice to combine results from many analytics tools to draw better insights and gain a broader perspective.

How Do You Analyze App Data?

You need to create a mobile analytics plan well before development work begins. Ideally, you’d want to build a comprehensive mobile analytics plan with documentation so that you can let the development team know how to structure the app.

Documentation with defined events and properties will keep everyone on the same page.

Start with a detailed testing plan. Specify the business objectives and then assign and describe events that will measure every business objective’s success.

Note: Adding mobile analytics after the development work started, will create an overhead, prolong development time, and consume resources.

You can supplement mobile analytics with A/B testing. This way, you can check how half of your users respond to changes in design and whether it’s a viable option to pursue permanently.

Best Practices in Mobile Analytics

Measuring Screen Transitions

Be careful with measuring screen events (transitions). Conclusions can be too vague when there are three or more on-screen action elements. Specific events are much more precise.

Minimum Number of Users to Start Mobile Analytics

There’s no minimum number of users that you can gain insight from. Start from no users — as you move forward, you’ll quickly see that every insight is important.

Keep Your Data Clean

When starts coming in, sift out active users from inactive, real users from employees, test users, or fake accounts.

What to Avoid in Mobile Analytics?

One of the biggest mistakes people new to analytics make is to track every little thing and metric.

But tracking too many things is a waste of time and resources because you have to prepare analytics, prepare the code, and go over the data.

The key is to measure fewer events but be more specific.

How Google Analytics Can Be Used for Mobile Applications? What Are Its Advantages?

Google Analytics is a great tool for analyzing website traffic. But not everyone knows that there’s Google Analytics for mobile, which offers some useful insight into how your users move around your app.

To use Google Analytics for mobile, you’ll need the Firebase SDK, either for iOS or Android. You can also use the Tag Manager + Firebase method for mobile analytics.

What Tools Are Used for Mobile Analytics?

There are many useful mobile analytics tools out there. The choice depends on the different metrics and business objectives you want to track. It might happen that the best analytics results for your business will be achievable with a combination of different analytics tools.

Here are some of the most popular mobile analytics tools:

• Mixpanel
• Firebase
• Amplitude
• UXCam
• Adobe Analytics
• Countly
• Heap Analytics
• Segment

Note: Pricing usually grows with the user base, so keep that in mind when picking your tools.

Mobile Analytics Helps Teams Build Better Products

Analytics provide you and your team with user intelligence crucial to building products that solve for target audiences. It’s a must in almost every product’s strategy. Mobile analytics tools let your team members make informed decisions about different aspects of products:

• Product managers can base and measure their product decisions on real-life data, with minimum waste of resources. 
• Developers learn about the technical setup of target audiences, which gives them the insight necessary to further optimize the code.
• Marketing teams improve campaigns equipped with detailed acquisition channel analysis.
• UI/UX teams tweak designs to improve user experience.