Mobile applications are essential for businesses as they engage and have a better user retention rate than websites. Companies use the collected app data to streamline users into marketing funnels and optimize their app performance. But precisely what is mobile analytics?
To simplify it, let's first understand what "analytics'' is. Analytics is the way of analyzing and measuring the user base data to get a "bigger picture" of the user's behavior and the performance of the website or application.
Thus, if this process is performed on mobile applications, it is called mobile analytics. Mobile analytics collects and analyzes users' interactions with the installed apps on their devices. There are many types of data that are analyzed during mobile analytics.
The collected data could include total installs, app launches, click rate, app retention, events, funnel analysis, etc. Mobile app analytics metrics are similar to standard website metrics like the number of new users and their country, device versions, links used to sign-up, etc.
The end goal is to turn the collected data into valuable information and use this information for app optimization and marketing purposes.
The collected data is valuable as it gives the ground reality of the app usage and forms the basis for market research and business growth models. Now that you know what is mobile analytics, let's discuss some important key terms related to it to get a better idea of how mobile analytics works.
Top 4 Useful Mobile App Analytics Metrics for User Acquisition
There are the most widely used mobile app analytics metrics for analyzing and measuring app data:
You can use this parameter to check the success of a marketing campaign. It shows whether anyone has acquired the new users through a marketing or affiliate link. You can determine which marketing campaigns are effective and worth your investment.
Average Revenue Per User (ARPU)
The Average Revenue Per User, or ARPU, tells you about the average revenue generated for each user acquired.
This is an intelligent parameter to check whether you are on the right track to hitting the desired revenue targets. ARPU is one of the applicable mobile app analytics metrics strongly recommended for businesses that want to evaluate their business revenue model.
Life Time Value (LTV)
Life Time Value, or LTV, estimates the total revenue generated by a user in their whole lifespan before they churn. Hence, it calculates how long a user should be active on the app to generate the maximum revenue.
LTV also gives a fair estimate of the revenue generated in the upcoming weeks or months. This all makes LTV one of the most useful mobile app analytics metrics.
Cost per Acquisition
Cost per Acquisition gives you an estimate of the total amount of resources spent on acquiring each user. The math behind it is simply the total cost spent on a campaign to the total number of users accepted per campaign.
It helps calculate return on investment (ROI), which further helps research the most cost-effective ways to acquire new users.
How does mobile app analytics work?
Primarily, mobile analytical tools are embedded into the mobile app's project code in the form of a library or Software Development Toolkit (SDK). This library initializes the code that tracks the app's usage and screen times.
The SDK differs for iOS, Android, Windows OS, etc. The SDK library is customized to track specific mobile app analytics metrics like device version, operating system, click rate, IP address, app crash, event, etc.
Mobile analytics is slightly different from web analytics in terms of its tools. Mobile analytics tools don't depend only on cookies or pixel tags, but they use individual SDKs for each mobile device to analyze user behavior. This is how mobile app analytics KPIs are commonly collected for business growth and marketing.
Mobile Analytics is relatively new and keeps on updating with time due to rapid changes in the expectations of users and the latest trends.
The biggest challenge mobile analytics companies face is the high chance of misinterpretation of data that can harm the whole campaign or even the business. Wrong data equals wrong app optimization and false reports. Ultimately, this crashes the entire purpose behind the mobile analysis.
Challenges of Mobile Analytics
Another challenge faced by mobile analytics companies is that critical user data requires proper segmentation to get a "bigger picture" of user behavior on mobile devices.
Often, improper data segmentation leads to a wrong understanding of user behavior that can turn into a disaster for any business. Hence, finding the right mobile analytics tool that measures and analyzes the necessary metrics and KPIs is crucial for making marketing funnels point in the right direction.
One such highly optimized tool is Appflow.ai. It provides mobile analytics tool services that help you manage both the iOS and Android platforms.
You get entirely segmented and real-time analyzed metrics data like in-app subscriptions, paywall A/B testing, and push notifications in one place. Appflow.ai also offers personalized and actionable expert advice to help your business grow in the right direction.