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What KPI’s Measure the Performance of My App?

ARPDAU (Average Revenue Per Daily Active User) and LTV (Lifetime Value) are the king and queen of measuring user performance in apps! 

ARPDAU aggregates monetization and daily user session behavior into a single metric, where LTV extends that by incorporating retention and later session behavior.

These are high level metrics, but they depend on more detailed KPI’s such as Retention, session length, clicks per session or engagement in the session. And even these detailed KPI’s inherent relationships to other metrics which help define your apps performance. Measuring the performance of your app can be done on multiple levels as you can see by the cascade above. 

Let’s continue with an example.

Let’s say, you’ve just added a Live Video Stream feature to your app, and we want to measure its performance.

Session length and sessions per day would be a good starting point

A higher session length would suggest a more engaged user. The higher session length more likely than not would correlate with a higher ARPDAU.

We can easily measure this wholistic level, but what about on a user level. What if we want to know why the session length increased? Were all users that engaged with Live Video stream effected the same? To do this analysis, we would need to cohort interacting users and see how they behaved before and after engaging with the Live Video. This could lead to correlations with users interacting with other app features driving session length! These are called correlations and can be used to measure performance on certain elements and products within your app.

In addition, funnels and conversion rates are paramount for determining if a product in your app is receiving the attention you suspect.

Defining conversion rates on different screens can help you see what your users engage with and when (another way of measuring in app performance). Back to the Live Video stream example above- conversions rates will be able to suggest if your Live Video feed should be on another screen!

There are packages such as Firebase, Apple Analytics, GA Analytics etc. which can give great insight into a lot of these high-level metrics. But by the same hand, these are out-of-box products which may not be beneficial for in depth data searching (they would especially not good for the example above). Not to mention, these products sometimes do not accurately measure ARPDAU and LTV as they do not take revenue data from the main source and rather approximate it.

This is where our service fits. We can use raw data from Big Query, your local database and API hit revenue data straight from the source. With this flexibility we can quantify performance on all levels in your app (not just high-level)!

It’s a beautiful thing to create an app with the desire to make something better or easier! But being able to monetize and allow for the BEST user experience possible is another art on its own.