From Analytics to Action The next phase of iGaming insight
As automation and AI reshape how data is used across gaming, operators are reassessing the limits of traditional analytics. Jurnii CEO, Fraser Dunk, discusses why proactive UX research and automation are emerging as key differentiators.
Fraser, from your perspective, what are the biggest analytics challenges facing operators right now? I tend to group them into three areas. Te first is that most analytics products are, by their nature, reactive. Tey report on what’s already happened. In gaming, by the time a player has experienced enough friction for it to show up in your analytics, they’re often gone. Tere’s no shortage of alternatives, and switching costs are very low, which creates a gap, because analytics typically surface problems after the damage is already done.
Te second issue is the disconnect between behavioural data and commercial data. Behavioural analytics on their own only tell part of the story. Many operators don’t clearly understand how changes in behaviour correlate to commercial outcomes. For example, if conversion improves by X, what does that actually mean for net gaming revenue? If churn reduces by Y, what’s the downstream impact? Tis kind of KPI correlation analysis is still relatively immature in gaming, but it’s critical. Behavioural and commercial data are two sides of the same coin.
Te third challenge is fragmentation. Data sources often sit in silos internally. Analytics tools have their own dashboards, logins and visualisation layers, while executives are looking at entirely separate management dashboards. Without interconnected data, it’s very difficult to do the kind of joined-up analysis operators actually need.
So where does Jurnii fit into that landscape? What differentiates your approach? Te first thing to say is that we’re not an analytics platform. We’re a research platform. Traditional analytics tell you what is happening: conversion rates, time on page, drop-off points. Jurnii is a proactive research solution designed to help operators understand why those things are happening, before customers feel the pain.
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Historically, this kind of insight has come from expensive agency work: UX audits, competitor reviews, deep design analysis. Tose exercises tend to be point-in-time, slow, and not very scalable. By the time the findings come back, they’re often already out of date, especially in a fast-moving sector like iGaming.
What we’ve built allows operators to run deep UX analysis repeatedly, at scale. Crucially, it also includes competitor benchmarking. Analytics might tell you your conversion rate is three per cent, but they won’t tell you whether that’s good or bad relative to the rest of the market. We objectively compare UX performance against direct competitors, which helps operators prioritise initiatives based on evidence rather than opinion.
You’re already working with tier-one operators. What are they typically coming to you for? Most come expecting a UX audit or a competitor benchmarking report, the sort of thing they’d normally commission externally. What tends to surprise them is the breadth and depth of insight we generate.
A single analysis typically produces 80 to 90 UX optimisation recommendations, and those analyses can be run as often as needed. Tat scalability is particularly valuable for large, multi-brand, multi- jurisdictional operators. Doing that level of analysis manually across dozens of brands and markets would cost hundreds of thousands and simply wouldn’t scale.
Another element operators find valuable is that this isn’t just a static reporting tool. Because we run analyses continuously, we can track changes across the market. If a competitor launches a new feature, promotion or A/B test, we can detect that and notify clients. Tat visibility into how propositions and experiences evolve across the market is extremely powerful.
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