Looking at conversion from the perspective of time since install provides key insights into general conversion patterns. Very consistenly your paying users are converting soon after install. And if you look at average time to convert the data you are seeing might be misleading.
A quick way to go back in time and see how your times to convert changed as your title ages. This illustrates why you should stay away from average times when considering behaviors in your game.
When you are in soft launch, you will be looking at multiple KPIs. But should you be looking at day 1, day30, day90? This post suggests a way to help you decide.
I’m following up here on my previous posts about having game-centric metrics. With this query you should be able to have in one same data
This post considers different ways to look at your active userbase. In particular, looking at how much your active userbase has spent in your game – what your active userbase is worth – can help you identify important changes in your game and think differently about the way your game monetizes.
Looking at how many customers (i.e. active useres who have paid at some point in the past) are in your game – and what % of your active users are customers – is crucial to understand your userbase and define a Live Ops strategy.
This post discusses different ways to consider your active users and payers.