In Data analysis, Games Analytics

It’s common practice for games to track player event data, such as with our own deltaDNA platform. However, as the volume and granularity of your data increases it becomes harder to gain insights about what your player base actually looks like. For example, in what ways are players interacting with your game? Dashboard-level performance indicators (e.g. day one retention or conversion rate) have their uses, but typically don’t contain useful insights from the players’ perspective.

To do that we need to build visualizations that dig deeper into the data and try to reconstruct key elements of player-game interaction. Here are two of the most common visualizations which we use most often at deltaDNA.


One of the simplest, yet most powerful, player visualizations we can build is a Funnel Plot. A common application of a Funnel plot for a F2P game is the First Time User Experience (FTUE) funnel:


By joining together events which must happen consecutively in your game, Funnel plots allow us to see what fraction of the player base progresses past key milestones. In the example above, it’s clear that the tutorial is a problem area, as only 60% of players complete it (versus 80% who start). Funnel plots don’t have to be limited to only early gameplay; they can also be used to track progress past any common milestones in a game (i.e. missions played, level reached, minutes of play, days played).

However, a key limitation of funnels is that they can’t be used to track events and behaviors which don’t happen in a given sequence e.g. paying, inviting friends or completing certain objectives.

A simple way to include these into a funnel plot is to simply segment the players in the funnel plot by key criteria (e.g. spenders/non-spenders):


With a plot like this we can compare the progress of players that are split by a certain criteria.  Here, we can see that the spenders and non-spenders progress similarly except for mission 3 & 4, and so the game may be too difficult for many players at this point and only the most competent players are passing through to monetize.


The funnel approach works well for when we have a single progress metric (e.g. missions completed) and possibly a few criteria to split the data by (e.g. spenders and non spenders), but this may not be enough to reveal underlying trends in games with a richer data structure.

A good visualisation that allows us to look at two dimensions is a heatmap. A heatmap is effectively a colour-coded  2D binning, or pivot table. This example heatmap takes missions completed and level reached:

We can see that most players are leveling up at a steady rate, but there are some players that are stuck on low levels (e.g. 2 to 5) at Mission 10. These players may be struggling and likely to leave, so maybe some changes to the game, or some intervention to just these players, is needed.

In conclusion, understanding how players are interacting with your game is an important step towards optimizing both the player experience and game performance. Visualisation of metrics is key to understanding the player experience and even easy visualizations such as simple funnels can reveal critical areas that may be holding back your game.

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