Insights Team

Monetization has been a hot topic in the games industry over the past years, ever since the rise of free to play games. How to optimize monetization, how to define correct pricing buckets or how to better convert players are just a few of the widely discussed questions concerning the topic. In this article, however, we’ll be approaching monetization from a different angle. Rather than discussing how to achieve a high conversion rate, we will dig into the differences in behaviour between converted players and non-monetizers. With this we’re looking to give you some insights into these players’ profiles, based on which you should be able to identify them early in the game. We will be working with two main categories (non-monetizers and monetizers), but 4 cohorts. For granularity purposes, we have broken down the monetizers category into 3 types:...

As you may know, at the end of May we released Benchmarks, feature that helps you bring more context to your analysis by allowing you to compare your KPIs to those of 5,800 (and counting) other games tracked by GameAnalytics. As trends in the industry are constantly moving, we will be updating these numbers monthly.   This month’s update was just released and is up now in the tool, for you to check out.   Here are the highlights for July 2015:   ARPDAU across the GameAnalytics network increased by almost 12% (from 2.37 cents to 2.66 cents), which was driven by increases in both conversion and ARPPU. This means that in July, not only have there been more people spending money in games, but they also spent greater amounts than in June.   ARPPU in particular increased by 50...

We are genuinely excited to share this first beta release of Custom Segments! With Custom Segments, you’ll be able to break down your users with ease by defining per user attributes. Now you can define segments by values such as spend, demography, time played and profile the type of players active in your game. We’ve worked hard to make this feature easy to use for everyone. The result is a cleaner way of using basic statements to define your segments. You’ll be able to run segments on different timeframes, which results in faster analysis. To top it all off, we’ll be processing your data in minutes, not in hours! Feature breakdown Define with per user attributes and statements You can define your segment through basic statements all calculated on a per user basis, making it dead simple to include or...

Benchmark feature released! Benchmarks allow you to compare your games’ performance to that of all the other games in the GameAnalytics’ network, giving you the context you need to make informed decisions that can improve your game.

In our last data science report on what makes a game successful we looked at the evolution of key game metrics over 90 days after launch, across 400+ games. (If you haven’t read that already, we definitely think you should before going forward with this one.) One of our findings was that most successful games show a better handling of their initial installs, dubbed the Golden Cohort. We thought it would be an interesting venture to dig a bit deeper into this. And so the queries began. Methodology Sample description We look at players from 208 games that hit 1000 installs during 2014. They represent the games that on a cumulative revenue basis are in between the 50th and the 90th percentile. This ensures we analyse the most successful games in terms of revenue in our network (games that pertain...

Each year brings with it a set of new fads in gaming, some make it, some falter, but one question is ever present: what makes a game successful? In an attempt to answer this, we looked at the evolution of key game metrics over 90 days after launch, across 415 games released in 2014 and spreading across multiple genres and platforms.