How game developers can drive more revenue
|Offer Yehudai in Game Development Monday, September 23, 2019|
Offer Yehudai, President at Fyber explains how identifying user patterns, segmenting users into clusters, and customizing the gameplay experience based on behavior can bring game developers more revenue.
Game developers tend to follow standard templates for monetizing their apps. Mid-core publishers focus on IAP and time-gated ads to be shown at a later date, usually based on their studios' recommendation. Meanwhile, hyper-casual ones go all-in on advertising, while casual games fall somewhere in between. These default strategies leave money on the table because they are based on past assumptions but now, by applying machine learning, all types of game developers can hone their monetization strategies in new and different ways to their game genre.
How can game developers drive more revenue?
Here's how: most game developers have more than one game. By looking for patterns in the behavior of, say, their IAP whales in one game, they can predict who the whales will be in their next game and who's not likely to spend at all. As users begin playing in earnest and more flock to the game, the algorithms get better at predicting behavioral patterns.
Once these patterns are identified, publishers can then segment users into clusters, which in turn, allows them to apply a highly nuanced monetization strategy in their games. Mid-core publishers have long assumed that advertising dissuades players from becoming whales, but that assumption might not be accurate. We worked with a mid-core publisher that discovered their IAP hurdles caused players to churn before they had a chance to get hooked on the game. A Thinking Ape (ATA), the publisher of Party in My Dorm, used rewarded ads to allow people to play who couldn't afford to make in-app purchases. The rewards, a wholly new currency in the game, were so successful that in-app ads are now a core part of that game experience.
Once publishers cluster their users they customize the gameplay experience based on behavior (i.e. show fewer ads to IAP whales; keep users in-game long enough to get hooked with rewarded ad formats; target users with IAP incentives).
Of course, a publisher can't know for certain if a user who follows a specific set of patterns will become a whale, but they can take a wait-and-see approach by applying a longer time-gate to the cluster. Conversely, users who are not likely to make purchases can have a shorter time-gate applied. Time gating is a useful tool, but its usefulness is diminished when the same timeframe is applied to all users.
On the opposite end are the hyper-casual games which can be crowded with ads. These games enjoy such widespread scale that hyper-casual publishers are less concerned with advertising-induced churn. But every game has some set of users who are likely to make purchases, especially if it allows them to see fewer ads. Once again, if publishers were to apply machine learning to identify these users, they can target them with a promo or special offers with the game's currency. Right now less than 10% of their revenue comes from IAP, and there's room for it to grow.
Casual games publishers have the most to gain from finessing their monetization strategy. Typically their revenue breakout is 70% advertising and 30% IAP, but they can grow their in-game spending. The key is to understand user behavior on an individual level and to create automatically the right game experience ad frequency, rewarded ads, and special offers based on that behavior.
Let's say a user has played a match 3 game a few times, has run out of moves, wants to play again, but doesn't want to lose everything she's achieved so far. The game has two strategies for keeping her in the game: watch a rewarded video or make an IAP. If that particular user is cost-sensitive, and she has declined to make a purchase, the game can show her rewarded ads. This approach allows her to continue playing, and the publisher to earn revenue.
This strategy can also be applied to test the right dollar amount for virtual currency bundles. For example, a publisher offers $5 and $20 game packs only, and that some users will spend $5 but never $20. The publisher can target those users with a promo for $10 and see what happens. If those users cross the $10 barrier then the publisher knows their limit and can target them appropriately. In other words, this strategy targets users who are about to churn (games know when users can't continue without making a purchase) as well as increases their IAP.
All this to say that there are compelling reasons for game developers to start thinking about ways to diversify their revenue. The long-held notions about monetization strategy leave too much money on the table.
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