Over the past years, we have seen trends in our industry rise and fall in the blink of an eye. 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 question, we’ve 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.
Our key focus was to explore whether or not there is a difference in a game’s daily metrics that could indicate its success or failure.
Our findings show that:
Explore these findings and discover how you can exploit them in making your next or current title a success. Find out where your focus should lie, and determine the key areas your investments should go towards.
The results are broken down by day over a period of 3 months, starting with the date at which the games either launched (where this was evident from the data) or reached 1000 installs. The data is smoothed to capture the important patterns and leave out irrelevant noise.
The distribution of genres of the 415 games mirrored what is seen in the app store.
The 415 games analyzed were across iOS, Android and Facebook platforms.
The games included in our sample were divided by quantiles, on their cumulative revenue over the complete period of the 90 days after launch. Group 1 represents the most successful games – the 10% of games with the highest cumulative revenue, whereas Group 4 includes those games with cumulative revenue below the median.
This distribution was chosen as it provides a general understanding of the patterns found in each of the metrics, and their evolution over time, making it easy to conclude upon differences.
For this analysis, we split the 415 games into four groups based on how much money they made over 90 days post-launch.
What our findings come down to is the chart below, which illustrates the difference in the cumulative revenue increase rate when considering quantiles.
The apparent difference in the cumulative revenue increase rate when considering quantiles. Check out the log scale on the X axis!
But what determines this difference? While all games have a close start in terms of DAU, the performance of other metrics (namely retention, conversion and ARPPU) will imply a large difference in revenue almost immediately after the game’s launch. Let’s see how that happens.
Conversion to paying appears to be one of the crucial metrics in the early stages of a game. The graph below clearly shows that Group 1 games are better at converting users into monetizers. An interesting insight here is that Group 2, though it starts out with a lower conversion rate than Group 3, performs better over time.
Conversion to paying users: a crucial metric in a game’s early stages.
From our sample, successful games also achieve a high ARPPU from the very beginning. For the top 10% this comes close to $15. At the other side of the spectrum, as seen below, ARPPU for games in the lower 50% quantile is under $5 and declines rapidly, becoming approximately $0 after the first month.
Successful games achieve a high ARPPU from the very beginning.
Let’s now corroborate the findings above: higher ARPPU and conversion rate will mean higher ARPDAU, so Group 1 games are all around better at monetizing their players, regardless of DAU size.
Regardless of DAU size, Group 1 games are all around better at monetizing their players.
Retention plays a key role in determining the success or failure of your game. As shown below, games in Group 1 have consistently higher retention, especially in the first weeks after being launched.
While groups 1 and 2 manage to maintain a stable Day 1 and Day 7 retention after the initial drop, for groups 3 and 4 this downward slope continues and reaches below 20% and 3%, respectively.
Games in Group 1 have consistently higher retention, especially in the first weeks after being launched.
For less successful games (Groups 3 & 4) Day 7 retention drops below 3%.
But the top tier games in our sample also start out with higher install rates (likely from app store featuring, promotion and acquisition efforts), which supports a higher DAU growth rate.
Top tier games in our sample started out with higher install rates.
This circulates back to our initial findings around high conversion and retention rates. Here’s why: being better at converting and retaining players means Group 1 will take full advantage of the app store feature or heavy promotional efforts. The increase in DAU that the latter generate is the last piece of the puzzle, which clearly differentiates them from the other groups.
What does this all mean:
Of course, games are much more than numbers. And there are a lot of other variables that come into play. What our findings come down to is the importance of iterating before heavily promoting your game. This speaks not only for how critical the beta period is in your game’s lifecycle, but also stresses the importance of game analytics.
As those first metrics are hard to turn around once your game has launched, data analysis should be introduced into your development process as early as possible. Continuously monitor retention, conversion and ARPPU from an early stage. Transform these insights into actionable points, use them to improve the mechanics that influence them, and you could propel your game into that top 10%.* This paper was originaly published on the GameAnalytics blog