Mobile App Analytics: Your Essential Guide to App Analytics
Analyzing your mobile analytics is a science, just like conducting a research study. The objectives of search engine optimization (SEO) for a mobile app are clearly different from those of a website.
The ultimate goal of mobile app marketing is to translate your ad budget into installs and those installs into long-term app use and in-app purchases. App store optimization (ASO) is your mobile app’s version of SEO, and it comes with its own set of metrics for performance analysis.
In this blog, we will provide you with a guide on how to perform mobile app analytics so that you can improve the performance of your app. Continue reading to learn more!
Why is Mobile App Analytics Critical?
Mobile apps give you another channel to engage prospects with your business. Every new piece of data you learn about your audience gives you a better understanding of the value of your app based on the size of the audience and the number of downloads.
Three main reasons make analytics essential for enhancing your business’s app:
Data strategies: As you collect data, you uncover insights that will enable you to create more effective strategies for your next campaign.
Demographic strategies: App analytics enable you to segment your audience to target them with custom-tailored strategy.
Goal management: Mobile app analytics allow you to understand which channels will help your brand attain maximum success. You can utilize this information to strengthen weak channels and focus more on the strongest channel to encourage more app installs and engagement.
Mobile App Analytics: Key Areas to Analyze
Tracking your audience and how they interact with your app is critical. You can use mobile app analytics to analyze your data and gather interpretations to help you make future marketing decisions and for creating effective App Store Optimization strategies.
Here are four key areas to evaluate to determine your mobile app’s success and areas for improvement:
It is critical to track installs and the sources of the installs. You can do that by using a tool like Google Analytics for Mobile Apps. Your downloads are possibly the most important way to track your progress over time.
Installs can also reveal trends such as whether your app performs best during specific seasons, days, etc.
Install timing can reveal a lot about your audience and business. You can see when people are most likely to download your app and use that information to boost your marketing efforts during those seasons.
App usage and retention
Retention metrics show how much time users spend in your app. Marketers calculate retention by dividing the number of daily app users by the total number of users in the monitored group.
The churn rate, which is based on the number of users who do not return to the app, is the inverse of the retention metric.
These metrics are a prerequisite for examining the user lifetime metric. The average number of days that a user from the original group interacted with your app in total is calculated as the user lifetime.
You can use mobile app analytics to see how frequently people interact with your app. It gives you a good idea of where you need to improve your app to increase its popularity.
If you want to do mobile app analytics correctly, you must first examine your revenue. You can do so by reviewing your Customer Lifetime Value (CLV). The CLV calculates how much revenue a specific user generates throughout their lifetime, allowing marketers to assess their return on investment (ROI).
The phrase “lifetime” refers to the amount of time a customer spends with the company while using the app.
The average revenue per user is another critical revenue metric (ARPU). This metric is calculated by dividing total revenue per user by user lifetime.
The CAC metric divides the total marketing cost by the total number of app downloads in a given time period. Your app will be profitable if your user acquisition cost is less than your LTV.
Cohort analysis aims to determine which advertising channel generates the most downloads. Cohort analysis divides a large group of users into segments, or cohorts, based on specific characteristics that emerge over time.
Marketers frequently create cohorts based on demographics such as device, channel source, country of origin, and others.
Cohort analysis aids marketers in more accurate metric analysis. A dietary nutrition app, for example, would not want to compare a weight-loss audience with athletes looking to maximize their protein and carbs.
Both of these audiences have different tastes and come from different backgrounds. Once these groups are organized into cohorts, the marketer can more accurately evaluate and interpret their engagement.
Want professional help with mobile app analytics?
Navigating the worlds of ASO, the app store, and mobile analytics on your own can be difficult, especially when you have a business to run.
The Hyper Fuel is a full-service digital marketing agency that can assist you in analyzing mobile app analytics and making actionable decisions to improve your app.
Our experts understand how to optimize and market apps for increased revenue.