In Data analysis, Games Analytics

The Games Analytics Conundrum: Where to Start?

Unlike many other sectors, the  games industry is awash with data.  Players are trying to tell you what they like, what they don’t like and how they want to experience your games.  But are you really listening?

It’s a real challenge for developers in the industry to truly understand player behaviours. Online games are now configured to write player level event data into analytics databases.  Typically a relatively complex game may have over 100 different types of events configured.  Each of these events, such as ‘Select Weapon’, ‘Invite Friend’ or ‘Start Mission’ will have associated data parameters so that player histories and status can be tracked in detail.

On a moderately successful game, there may be 1,000,000 MAU, each generating many event records per each minute of gameplay.  So before you know it, you’re up to your neck in data with no clue where to go next. So how can we interpret this data and start to really understand our players motivations and potential?

The answer is surely not in dashboard metrics.

The old industry perception has been that if only we could think of the right metric, then we can unlock a universal understanding of players.  But, sad to say, this metric does not exist. The reality is that metrics look backwards – they tell you what has happened (good or bad) but they don’t tell you what to do next.

At GamesAnalytics we don’t always believe in Fairy-tales but valuable lessons can be learned from some of them.

The Goldilocks Rule: collect the right amount of event data – not too much to become overwhelmed, but not too little to limit the depth of analysis.

There are some critical decisions to make when configuring event collection.  Getting this wrong is career limiting.  So have a good reason for each event; ask yourself – ‘What value will this data item allow us to deliver?’ and don’t default to collect everything because it might be useful sometime.

For example on a FPS, you probably don’t want every shot but you may want to take every ammo reload.  Being smart about event collection is worth the effort, believe me.

The Three Little Pigs Rule: break down the objective

Let’s solve retention! Ok, but there are different types of retention issues and we need to differentiate them to get to the heart of the issue.  So are we solving early game play defection?  – those that leave in the early levels before engaging with the game; or is it mid-game defection? – previously engaged players who have, for some reason, become sporadic players. Or is it late defection? Perhaps players running out of levels and features.

All are separate objectives with a different focus, approach and solution.

The Seven Dwarves Rule: Be multivariate

This is a fancy term which means look at all the data together not metric by metric.  By using statistical and visualisation techniques we can analyse the combination of each player’s behaviour to characterise their game play.  Being holistic about each players’ playing lifecycle is fascinating, rewarding and worth the effort.  This is how we unlock a clear understanding of player behaviours.

The Sleeping Beauty Rule: be player centric

Think players not game. Repeat this ten times.

If you abide by these four rules then clarity, insight and a sense of calm await you.

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