In Game marketing, Game monetization, Games Analytics, Player retention

Making money is tough when you’re giving a game away for free. If engagement rates are low, and acquisition costs are high, it’s near impossible. Our data shows that across the thousands of games on the deltaDNA platform, retention rates in free-to-play are less than 40% after one session. That’s a lot of players you’re just not seeing again. So, how do you improve this as a marketer? The answer lies in looking at the game from the player’s perspective, but since not all players are the same, to do this, you have to use segmentation.

We’ve put together this quick and simple guide to using segmentation in games, with some practical steps you can apply to segment players in your game.

Identifying why players are leaving

Before we go into the basics of segmentation, it helps to know why players choose to leave a game. Below are the 10 the most common reasons for poor retention.


The 10 top reasons by churned players choose to leave games


It can be tempting to act on this information alone and dive into making changes to your game, however, segments of players will react to gameplay differently, and therefore their reasons for leaving (and not monetizing) will vary. This is why segmentation matters, and why a one-size-fits-all approach just won’t work.

Looking at where there is a drop off of players in your game is usually the first step in the segmentation process. For example, if you have a low Day 1 Retention rate (the % of players returning one day after install), then the first places to look would be on-boarding and early missions.

Let’s take another scenario: if there is a drop in retention on level 3, then you could analyze the health levels of players entering that level. This would show you which players are taking the most attempts to complete it, or which are achieving the fewest kills.

Tools like Slice&Dice and Funnels on the deltaDNA platform have been created to analyze the player journey and reveal such drop off points. Using them doesn’t require specialist knowledge of SQL report writing, but an understanding of the events you have set-up within your game is important. Once you’ve identified where in the game the problem resides, you can look at which players are affected and set out to fix it.

Practical steps to segment players

Once you’ve determined which criteria you want to segment on, you’ll need to use an analytics platform to interpret your game and player data to create your segments. Measures of competency, such as the rate of acquiring XP, are a common metric used to segment players, but there are many others you can look at too, such as how competitive players are, resource usage, purchase decisions, momentum, reward outcomes, competency, and collaboration with other players.

Here’s an example of how this is done in deltaDNA using our Data Mining tool. We have filtered players by Mission Completed, Lives Balance, and Total Days Played.


The deltaDNA Data Mining tool can be used to segment players within games


The platform performs the analysis work for you and reveals the results; here, red players are loosing lives and failing to complete missions, so you can hypothesize that they are at risk of leaving the game.

Segments derived using this process are often relatively very small, but this grants you the opportunity to create highly-targeted intervention strategies to engage these players, that have a far better chance of improving your key performance indicators (KPIs). Games succeed or fail on small margins after-all.

Using segmentation to improve game KPIs

Once you’ve identified under-performing segments, you need to intervene and change their experience, and what’s more, make sure your interventions are actually working. Whether you want to send a gift, ease off the difficulty, or offer hints and tips to have get them through that particular mission, using tools like those in deltaDNA’s Engage will let you apply changes to selected segments. This means other groups of players who are happy in the game are not affected and their experience is not unnecessarily upset. But even in the most effective games, most only see 5% of players paying, so what about the other 95%?

Players who are persistent Grinders with no intention of paying for an in-app purchase (IAP) can often be highly social. They contribute to organic downloads, or interact well with advertising. Identifying and targeting these players with campaign messaging, incentives or a higher ad frequency, can make a big difference to the monetization potential of your game. Similarly, Novices are often more responsive to ad serving and rewarded videos, appreciating the extra resource.

There’s a wealth different things that you can do to optimize monetization, so the best way to prove that changes are working is to use AB Testing. DeltaDNA’s toolset, for example, offers you unlimited variations that can be evaluated against 50+ dashboard charts to fully understand the consequences for both your players and the game.

Making segmentation work for you

The philosophy of segmentation is to take a player point of view and look at the game from their perspective, an approach all marketers should feel familiar with. When it comes to applying this practically, optimizing key performance metrics can require as much as 6 – 10 solutions, perhaps more; there’s no one big fix, as issues often lie in several places and sit with several types of players. Analytics and Marketing tools are there to simplify this job for you, and to take the guess work out of decision making. Though you can test and optimize variables like messaging to get the most effective outcomes, the art remains in devising engagement strategies that your players will love.


If you liked this article, you may be interested in reading our 5 top tips for AB Testing

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