I was recently treated to a gaming metrics overview by a product manager at a leading social gaming company. Like most game developers (small or large), he seemed to feel that acting on metrics is the key to success in social gaming (this Guardian article discusses metrics-driven social gaming success). But he also made the point that while there are plenty of ideas out there in terms of how to apply analytics to game optimization, very few people do so very rigorously and systematically.
According to this product manager, one of the top ways to gain a winning advantage through game analytics is to conduct cohort analysis, which happens to be one of my favorite activities. In this blog, I will discuss the how, why and what of cohort analysis for game developers.
What is Cohort Analysis?
A cohort is a group of users who share a common characteristic over a period of time.
Cohort analysis is a way of understanding user engagement with your game over time. It helps group gamers with similar characteristics (typically when they signed up or downloaded your game) and helps understand their behavior (game play, viral behavior, virtual purchases, level ups, etc.) over a period of time.
Why do Cohort Analysis?
As a game developer, your primary goals are to grow your user base (reach), get those users to stick around (retention), and make sure they’re so engaged that they can’t help but buy things (revenue). We call these the three R’s. Of these, retention and engagement are perhaps the most important factors to look at, because if you are doing this well the other two should fall into place relatively easily. In terms of engagement, cohort analysis helps you understand how gamers who signed up in, say, Jan ‘11 are doing and compare them to gamers who signed up in Feb, Mar ‘11, etc.
Cohort Analysis helps your reach, retention, and revenue efforts in many ways:
In our next blog, we will look at best practices in cohort analysis and typical challenges game developers face in trying to conduct it.
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