and focus groups, points to the same conclusion: gameplay is much more habitual than discovery-led. For the majority of returning sessions, the player is trying to complete a task. Tey want to get to a market, place a bet or play a game they already know. Tey are not necessarily in an exploratory mindset.


Te behavioural science is clear on this. Once a behaviour becomes habitual, motivation and deliberation largely drop out because it becomes routine. So, if someone is logging in every Tuesday evening to play the same game, surfacing recommendations at that moment may be working against their psychology rather than with it.


Tat doesn’t mean personalisation has no role, but it does mean its value is concentrated at very specific lifecycle moments. Onboarding is one. Reactivation is another. New product launches can also be relevant. But applying hyper-personalised experiences as a persistent layer across every session, regardless of context, is where the industry often gets it wrong.


every time they visit, or navigation shifts session to session, those habitual paths are broken.


Te safest model is a static structure with personalised content inside it. So, a “recommended for you” component can exist in a fixed place, while the titles within it change. Tat works. But when the architecture itself starts moving around, that’s when personalisation becomes disruptive.


Tere’s a good anecdote from Apple when it introduced shuffle on the iPod. Te system was genuinely random, but users complained it didn’t feel random because hearing the same artist twice in a row felt wrong. Apple had to make shuffle less random so it felt more random. It’s a useful reminder that algorithmic logic and human perception are not the same thing. Personalisation can be technically correct and still feel jarring in practice.


Discovery often happens off-platform rather than on it. If that’s the case, are operators over-investing in on-site personalisation at the


the data foundation is often much weaker than people assume.


Add legacy technology stacks that were never designed for real- time activation, and it becomes clear that the infrastructure challenge is just as important as the data challenge. Building a


genuinely complete picture of player intent is extremely difficult in an industry where behaviour is fragmented by design.


At what point does personalisation start getting in the user’s way? What does over-personalisation look like in a live casino or sportsbook environment?


It starts getting in the way when it interrupts the journey instead of supporting it. A user in an in-play sportsbook environment or a live casino context is usually high-intent and low-tolerance for friction. If they have to navigate past recommendations, changing content hierarchies or shifting layouts just to get to a known destination, you’ve made the product worse in the name of relevance.


Tere’s a core UX concept called wayfinding, which is about helping people orient themselves and move confidently through an interface. Users rely on familiar landmarks and patterns. If a lobby is reordered


60


FRASER DUNK CEO, Jurnii


expense of fixing core UX fundamentals?


In many cases, yes. Tis is not unique to gaming, of course. Across digital industries, a lot of purchase decisions and discovery moments happen before the user ever arrives on-platform. Tat comes through peers, affiliates, search, social, influencers and other external channels.


In iGaming, that pattern is particularly strong. A lot of site traffic arrives with intent already formed. Te player has already seen the game, the market or the brand somewhere else, and by the time they land on site they already know broadly what they want to do - which creates an attribution problem. On-site recommendation engines can claim credit for engagement that may have happened regardless, simply because the content was surfaced at the point of visit. Tat can inflate the apparent


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