The Player Lifecycle
The About page tells the story of a fictional player. It is a rare story, one shared by less than 1% of the daily players of the average mobile freemium game. There are several steps of the story.
It starts with Acquisition. It is the time where a unknown person becomes our player. We are interested in who the player is and how she found the game.
We also want to know if she returns. That is Retention. Not only we are interested in knowing if the player returned to the game but also why or at least at what point did she leave.
At this point we know she knows the game and is interested in it. Engagement is how we know if this is a meaningful love story. We want to know how she plays the game, what she likes in it and what she avoids.
Virality is in fact a very important part of acquisition. However “pure” acquisition is related with marketing while “pure” virality is related with design. This is how we measure if a player brings other players to the game through in game mechanics.
In the end, commercial titles exist to make money. Understanding who, how and why players make in app purchases or use advertising services has a big impact in making games more profitable. This is Monetisation.
Last but not least, the arch-villain: Churn. It is the big black hole in which we loose all our beloved players sooner or later. Churn is the opposite of retention and like it, it’s present through the story.
I call this story The Player Lifecycle.
At each step, the player either moves forward or churns. The player is acquired, is retained or churns, is engaged or churns, is monetised (or not!) and then, sooner or later — but always sadly — churns. Viral actions are a whole special category. On one hand it is a form of engagement. On the other hand it is mostly related with acquisition. For this reason I don’t isolate virality churn.
These parts are not self contained bins. Data wise they are not separated. The player lifecycle is a conceptual model of the player behaviour. It allows us to focus on specific problems, to segment on particular needs and to find outliers. This is what I have in the back of my head when I’m looking at a game’s data. This is the story I’m trying to tell.
Originally published at ongamesndata.wordpress.com on July 9, 2015.