Data 101


I’m starting this category “All things data” to write posts about data for the sake of data. Some of them are simple but play a big role, like this one. Others are complex. There will be a twist, though. The examples I’ll show will be in the context of games analytics. There will be no Iris dataset to fit a logistic regression. If you are smiling you know what I’m talking about. If you are not, don’t worry, we’ll get to that. Continue reading

A/B Testing and RCTs 101


I have a love/hate relationship with A/B testing. On one hand, I love it because it is the tool that allows me to say that something we changed caused some behaviour. This is pure actionable power. The reason I hate it, on the other hand, it’s because the expression “A/B Test” is a symbol of how badly treated these tests are. I have nothing against A/B Testing and I believe there’s a lot of bad A/B Testing. Continue reading

Virality 101

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I’m looking forward to moving to more practical stuff. To do that I need to wrap up the 101 posts of The Player Lifecycle. The one missing is Virality.

So, what is virality?

Virality is the game’s ability to acquire new players through actions of existing players. Facebook shares, tweets, SMS, invite codes, etc. All of these actions count as virality as long as they are trackable. This means that things like word of mouth don’t count. It’s a pity I know! A good game gains traction pretty fast through word of mouth, but we want measurable virality.

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Acquisition 101

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And so it begins. Acquisition is that special moment where someone opens our game for the first time. As magic as it is (and it is!) there’s quite a bit going on. Acquisition is important in a couple of different areas: the first, more business oriented, is marketing and user acquisition. The second is early knowledge of the player. Let’s begin.

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Engagement 101

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Engagement is the most misunderstood and complex part of game analytics. The reason for this is that engagement is about fun and fun is something very difficult to infer. Average session length (measured in short units of time) and average session frequency (measured in a number of daily sessions per user) are often the metrics used to measure engagement. If we think about retention on a user count basis it is easy to see engagement as a session count and/or length basis. After all, the frequency at which players return and the amount of time they spend in the game should be good indicators of this, right?

As I see it, the difference between retention and engagement is not a matter of differentiating users from sessions. Retention is about returning to the game. Engagement is about interacting with it meaningfully. Sessions alone won’t tell you if players are having fun. Let me tell you a true story that will illustrate it perfectly. Although the story is a true one, data are illustrative.

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Monetisation 101

My grandmother told me that great men have their faces on bills. Observing the picture above I believe it’s fair to say she raised me well! Or that I asked Pedro to put my face in it. You’ll be the judge of that.

On to more relevant matters…

Monetisation is the end result of our analytical journey, The Player Lifecycle. I’m a firm defender that retention is king and engagement the successor to the crown. After all without players that stay and love our games there won’t be anyone to monetise. But not admitting that the end goal in freemium games as a product or service is monetisation is to be naive.

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