But what is mostly unknown is whether players of one genre tend to play the same genre, or a similar genre, or perhaps a completely different genre? Do Casual gamers only play Casual games or do they also play more advanced Role Playing games?
From the gaming studios’ point of view, genre diversification is on the rise as a growing number of companies are looking for the next niche and patches of less busy ground to make money from.
An analysis of 800 gaming studios which have been working with us in the past three years found that:
- 28% increased the number of genres between 2018 and 2020, compared to 18% who had fewer active genres and 54% unchanged.
- 6.5% had running games in 5 or more genres in 2020, while nearly 30% were active in 2 to 4 genres.
Likewise, marketers are constantly on the lookout for growth opportunities and ways to optimize their campaigns with sharper targeting.
One way is through genre-driven segmentation.
So which games should studios develop or acquire? And which genres should marketers target, now that contextual advertising is about to make a comeback in the absence of IDFA? (after Apple enforces its AppTrackingTransparency framework)
Our new gaming genre affinity matrix can provide some answers ahead!
The global affinity matrix
We analyzed over 350 million unique devices from November 2020, and here are the results, based on the current categorization in the app stores:
- By row: The numbers tell us what the share of users who play genre x and also play genre y, genre z, etc. For example, we can see that 26% of Puzzle players also play Action games, while 38% also play Casual games.
- By column: The numbers in the column show the share of genre x players who play other genres. As such, it is not as impacted by the genre’s scale as the row. To follow-up on the above example, the Puzzle column cell that intersects with Casual shows that the same 38% are also 19% of Casual users.
Now, let’s assume that you want to run a campaign for your Puzzle app, should you target Casual games (19% of whom play Puzzle), or would Word games (36% of whom play Puzzle) be a better choice?
In most cases, despite the fact that 19% of Casual players represent a much larger number than 36% of Word players, it would be wiser to run on Word games with an affinity rate that is almost double that of Casual.
If you are running a CPM campaign, your chances of success in Casual are less than half compared to Word, so Word is the obvious choice.
But even if you are only paying for installs in a CPI campaign, it appears Word is still a better choice because it has a closer affinity with Puzzle. And with higher affinity, there are better prospects of improved performance and lower churn.
1. Size matters, to an extent
The matrix data shows that Action, Casual, and Arcade games are by far the most popular genres, which means the likelihood that these games are installed on the average smartphone are high, regardless of the types of other games the user plays.
In fact, in only 2 of the 16 genres the highest share of a specific genre was the same genre. In most cases, the highest share on average was found in one of the biggest genres.
But as we’ve mentioned above, higher affinity (as seen in the column) is often a better indicator.
2. iOS and Android dominate different categories
A platform level analysis shows that some genres are completely dominated by either iOS or Android.
Android’s average share of Music users who play other genres is 140.8% higher on average than iOS. The same goes for Action (56.7%), Arcade (58.3%,) and Strategy (38.7%). On the other hand, iOS dominates Puzzle (27.8%), Social Casino (31%) and Word (42.4%).
The reason for this gap can be found in the operating system split in each sub-genre and the relative popularity of different genres in different countries. In the categories dominated by Android, the average ratio is 76/24 in favor of Android, while iOS dominates its categories thanks to a 55/45 split in favor of iOS.
3. Social Casino players hardly play other types of games
The largest gap in the share of players who stick with their own genre belongs to Social Casino apps. According to matrix data, 32% of Social Casino players also play at least another Social Casino title, 7 times more than the average of all other genres. The only genre with a decent result is the similar Card genre at 16%.
The fact that people who like these games don’t really play other games as much is probably the result of how these games are designed (it is important to stress that Social Casino games are not gambling/real money games).
4. Affinity demonstrated among mind games
The matrix shows that the percentage of users who play mind games like Puzzle, Word, Trivia, Board, and Card is much higher amongst these genres compared to their number among Midcore and Hardcore games.
5. Some players mostly stick with their type, but some mix it up more
A sub-category* level analysis (see the end of the blog for more details which genres make up the different sub-categories) found that:
In some cases players mostly play games in the same group, with Social Casino leading the way at 32%, which is 7 times more than the average of other genres. Hardcore players also have a higher affinity with other Hardcore titles (57% higher than the average among other genres), as do Hyper Casual players (20% higher).
The Casual group had the lowest share of users in their own genre compared to other genres. As such, 65% of Hyper Casual players and 56% of Social Casino players also play Casual games, compared to only 46% of Casual players themselves.
Similarly, although 57% of Midcore title users play other Midcore games, it is far less than their share among Hardcore players (74% of whom play Midcore titles), and even less than the 65% of Causal and Hyper Casual who play Midcore titles.
How matrix data can help inform decisions
For developers — suggest genres suitable for portfolio expansion.
With genre diversification on the rise, developers can use this data to suggest a potential course of action to expand their portfolio: either via acquisition or in-house development.
For marketers — inform decisions on multiple activities, including:
1. Segmentation for UA:
Genres with a high level of affinity to a particular genre/s should at the very least test a campaign with this segmentation. In the age of privacy, particularly with the pending limited availability of the IDFA due to Apple’s AppTrackingTransparency framework (ATT), contextual targeting becomes more important.
Running a campaign segmented by genre is just that: it’s like running ads for luxury cars on luxury travel destination websites.
2. Smarter monetization of ad space:
Apps that generate revenue through ads can prioritize genres with high affinity to their own. They can blacklist or whitelist apps on the campaign level (based on genre or list of apps depending on what their ad network can offer). These users are more likely to install and play games in high-affinity genres, which can yield higher ad revenue.
Even if the publisher is paid on a CPM basis, it should still care about how the buy-side and ad network perform. After all, if users are more likely to install and engage with a high-affinity genre, the network will earn more in a CPI or CPA campaign, leading its algorithm to prioritize the app.
Knowing the value of its real estate to certain genres, the advertiser can also increase its CPM, and the network may agree if it delivers high-quality users.
Marketers can even choose to run ads for games in their own genre, particularly in cases when their share is high as seen in Action, Casual, Puzzle, Word, Role Playing, and Social Casino.
Although they can be considered competitors, there are times when this can make sense. For example, if and when apps are able to recognize that a user is about to churn, and they do not have another of their own apps to cross-promote. In such a scenario, they could decide to sell ads to a competitor for the right [high] cost.
3. Cross-promotion optimization:
Studios with multiple genres in their portfolio can pinpoint cross-promotion campaigns with matrix data, and inform their optimization for increased effectiveness.
4. Private deals:
If a high percentage of users who play genre x also play genre y, it is worthwhile to close a private deal for a user acquisition campaign with app/s in this genre (often facilitated by an ad network).
As mentioned above, this is a form of contextual targeting that is becoming increasingly important in the age of privacy and Apple’s ATT framework.
5. Private marketplace (PMP):
In the framework of a private marketplace (programmatic auctions for an exclusive and select number of buyers and sellers), premium publishers can sell their real estate for a higher value to a select group of interested buyers. On the other side, buyers can decide to offer more for what they consider to be top real estate that will deliver high-quality users.
To sum up, genre affinity data can be very useful for developers, marketers, and ad networks alike.
Use it wisely!