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The 7 most impotant metrics in Mobile Analytics

App analytics is very important in order to prepare new versions and functionalities. It’s crucial to analyze what happens within our application and how users are interacting with it. Take into account that the usage of apps varies greatly depending on the category. Flurry already indicated it in the following table:


Although the app usage varies depending on the app category, here we will detail those generic app metrics that all applications should consider in their app analytics:


1) Active Users

Download an application is the easy part. Get the user to re-enter costs a little more. It is for this reason that we must consider both monthly active users (MAU) and daily active users (DAU).

Knowing all about them, how they use the application, where they are from, etc. allows you to segment them and define custom actions to each one of them, in order to retain them in the application.

Active users are important but also is our ability to attract new users. The percentage of new users is another metric for apps we must not forget: every time this percentage decreases our alarm should sound!


2) Using the application

One of my favorite questions is: in which screen do you lose most of your users? Do you know it? This is a key figure!

It is very important to understand the flow of navigation within the application because it allows us to know why users abandon our app and in which screens. In a game app this data can tell us if a level is too difficult.

Another issue to consider is the navigation within each screen to see if users really are following the process we had thought. The heat maps are a tool we can use in these cases.


3) Session length

For how long users use your application? If you see that they don’t spend a lot of time, it may mean that users found something they didn’t expect. However, it will depend on the app. For example in weather app, people only use it between 1 and 3 minutes. But if it is a productivity app, they might have longer sessions.


4) Retention

20% of mobile applications are used only once. Did you know that? It’s important to detect it before is too late. We can measure retention as the percentage of users returning to the app after their first visit. And not only it’s important to know the user retention but also how often they return to the app. As most committed and loyal are our users are, better monetization strategies we can develop.


5) Customer Acquisition Cost (CAC)

It’s important to know how much it costs us to acquire a new user because based on this data we’ll calculate how much we can spend on advertising. The CAC is calculated by adding all costs employed in getting the new customer (marketing, commercial and infrastructure) and dividing them by the number of customers we achieved in the same period.

CAC = Expenses required to capture customers / New Customers acquired


6) Average revenue per customer (ARPU)

We calculate ARPU by adding all the revenue per user (price of the app, in-app purchases, ads, etc) and divided by the number of users.

Then, we can compare the CAC with the ARPU and know if we are achieving our objectives.


7) Customer lifetime value (LTV)

Do you want to know the total value of your users for all their interaction with the application? It is the result of multiplying the ARPU for the expected life of a customer. Given this information we can make predictions about releases and needs of capital.

As I mentioned, these are some metrics that all apps should use in their mobile analytics. However, each application should find their particular mobile analytics metrics. Do you use any other?

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