Oleg Smolerov: AI personalization as the key to iGaming success

Every year, the iGaming industry becomes even more competitive.

The market is growing and opportunities are appearing in the form of new players and new money entering the fray. To stay ahead of the curve, platforms and operators must adapt to new technologies. AI services, presently a hot topic, are a prime example.

I absolutely believe that the proper implementation of AI models is a key growth area for the coming years. Without personalization, accurate data, and behavioral predictions on every player, you'll become uncompetitive in 2-3 years.

Lessons from tech titans

But let's deal with the basics first. What do I mean by AI's influence on iGaming? AI algorithms analyze data faster and more accurately than people. They can identify unique behavioral patterns and preferences across all players, and adapt according to these patterns. This can cover marketing activities, tailored bonus offers, content personalization and more. With a smart use of AI, we can ensure that players will only see what interests them at a given moment, thus significantly reducing frustration.

You don't have to look far to see that this approach works. Spotify, YouTube, and Netflix have long understood the importance of personalization, so why is iGaming lagging behind? There are several areas where methods are similar, not least the homepage where you want to display the most suitable content in the top spots, so the user isn’t forced to scroll endless lists in search of something interesting.

And I'm not even digging deeper. For example, Netflix uses dozens of posters for each movie or series, to find the most engaging one for a particular user’s profile. The same can, and should, be done with the images on game cards in casinos.

One step ahead

Content personalization is precisely my main focus right now at ZingBrain AI. Every player, even the new one and even in the unlogged state, should see the most relevant games or sports events from the first touch.

It’s easy to understand how to predict relevant games for an active player because there's a lot of data on their behavior: what games they played and how often they played them, what game cards they clicked on, and from which sections.

But what if the player just signed up and we don't have all that data yet? Not a problem, because we can still draw upon informative data points, such as country and language.

Full personalization is achieved; everything is automated from the first touch, and there is no manual work. Sounds good, doesn't it? And I haven't even touched on the LTV and retention increases yet.

Prove to the player that you understand them and can accommodate their preferences, and they'll be happy. Personalized sections must constantly respond to the player's behavior. That’s the way to create happy players who want to come back for more.

Future of personalization

And I’ve got the statistics to prove it. On one brand that we’ve been working with for almost two years, the recommendations section generates 55% of all game opens from the entire site. It’s just a single-line section on the homepage with the option to click ‘See All’. Once a player becomes accustomed to this sort of personalization, do you think they’d find it easy to switch to a different brand without it?

Let's give another example. Imagine a standard player session. The player may have played some of their favorite games, spun the bonus free spins, scrolled through an endless field of unknown slots, tried a couple that they didn't like, got bored, and decided to end the session or even cash out the remaining balance.

But what if, when they end the game session and decide to close the game, they see a pop-up with a few similar games?

These could first be matched to the mechanics of the closing game, and secondly tailored to that very player. The player then tries a new game, then another, and continues to enjoy it. Anything the player reacts poorly to will be replaced with something new that they might like.

Can all of this be organized manually? Probably, yes. But how much time and effort would it take? You'll have to use cohorts and update the lists much less frequently. The accuracy of predictions will decline, and with it, player satisfaction.

The player is happy when they find a new game that they like. So make sure that the player experiences these emotions more regularly. They will repay you in kind.

Looking at generative AI (like ChatGPT, etc.), it's easy to see how quickly the industry is developing. Recommendation engines will become faster and more accurate, and new ways to understand players' behavioral factors, and then influence them, will emerge. In a few years, we will see games that adapt to the player in real-time, mixing mechanics and themes, and reacting to their behavior.

Sounds like science fiction? Well, it's closer than it looks.

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