At G2E Las Vegas, G3 spoke with Andy Mace, Head of Casino Personalisation at Sportradar, about the company’s collaboration with betPARX, integrating VAIX AI technology to create a more engaging and data-driven player experience.
Andy, what challenge did betPARX want Sportradar to help solve?
As with all of our discovery sessions, we begin by identifying the client’s pain points. betPARX wanted to differentiate its product offering and deliver a better user experience than its competitors. That focus on creating a truly personalised experience formed the foundation of the project.
More broadly, this aligns with a wider industry trend: operators are competing not just on game titles but on experience quality, using AI-driven insight to strengthen retention and lifetime value.
Why was VAIX Casino AI selected as the right fit for betPARX?
It came down to experience and depth. VAIX was one of the industry’s first AI-driven personalisation engines, and its maturity gives operators a wide range of use cases. That combination of proven technology and flexibility made it the natural choice.
VAIX has evolved over the years, combining deep-learning and transformer models refined over nine years with Sportradar’s unparalleled betting and gaming data. This gives operators a scalable solution with fast time-to-market and measurable ROI.
How was VAIX integrated into the betPARX platform? Were there any operational challenges?
There are always technical hurdles with any integration, but betPARX had an excellent partner in Playtech, which handled much of the front-end work efficiently. The process went smoothly overall. Integration was completed via Sportradar’s single API framework, which also powers its broader iGaming and sportsbook solutions, ensuring a future-proof setup that can easily expand into new content verticals.
How quickly does the AI begin to deliver relevant recommendations once it’s live?
Our models start reacting after just one session of gameplay, though it usually takes a few sessions to reach optimal accuracy. The system learns quickly and continuously improves as more player data becomes available. That ability to adapt dynamically means operators can start seeing measurable uplift in engagement within weeks, a key advantage compared to building in-house systems.
You deployed VAIX across three content carousels. How were those areas selected?
That was a joint decision. In the discovery phase, we worked with betPARX to identify the most valuable use cases. The first phase focused on three core carousels where personalisation would have the greatest immediate impact. This modular approach mirrors Sportradar’s personalisation framework, start narrow, prove success, then expand, ensuring every personalisation initiative is tied to clear business KPIs.
The case study showed a 200 per cent increase in unique titles played. How did the AI drive that level of discovery?
The VAIX models analyse the operator’s entire game portfolio when generating recommendations. This ensures players are exposed to titles most relevant to them, rather than just the most popular games. The results clearly show that when players are guided to suitable content, engagement rises dramatically. It also reduces dependency on top-tier providers, helping operators surface a wider variety of games and drive more balanced content performance across their portfolios.
Session duration rose by 273 per cent. What does that tell you about the quality of the personalised experience?
Casino is a very visual experience. Players choose games based on what they see, but true engagement depends on delivering content they’ll actually enjoy. That increase in session duration tells us our AI is successfully matching players with games that fit their preferences, even those they might not consciously recognise. Longer sessions translate directly into improved retention, conversion, and wagering activity — reinforcing that effective personalisation benefits both player satisfaction and operator profitability.
With 53 per cent of players engaging with AI-powered carousels, how did behaviour differ between those who used personalisation and those who didn’t?
The difference was significant. The fact that more than half of players engaged with just three personalised sections, out of 12 on the app, shows how effectively those experiences resonate. Those who interacted with AI recommendations showed higher repeat-visit frequency and stronger cross-vertical movement between casino and sportsbook, proving how data-driven experiences enhance loyalty across the ecosystem.
Which metric best reflects the business impact of the collaboration?
For me, it’s session duration. betPARX wanted to build a more engaging, dynamic user experience, and longer sessions directly demonstrate that players are spending more time enjoying content tailored to their tastes. From an operator standpoint, that translates into measurable revenue lift and lower acquisition costs, both crucial KPIs in today’s competitive iGaming market.
Were there any findings that surprised you?
The uplift in wagering was a pleasant surprise. We expected to see improvements in engagement and retention, but the increase in wagering volumes exceeded expectations, an encouraging indicator that players feel comfortable and confident in the personalised environment. It also validated Sportradar’s “responsible by design” approach to AI, creating experiences that build trust and long-term relationships rather than short-term spikes in spend.
How much control does betPARX have over the AI’s recommendations?
betPARX uses a tool called “Boost,” which allows them to override the AI when necessary, for example, to promote specific titles or campaigns. So, while the recommendations are automated, operators retain full control when they need it.
What role did operator feedback play post-launch?
Operator feedback is integral. We maintain regular meetings before and after deployment to ensure everything runs smoothly. In betPARX’s case, the feedback has been universally positive, both on the technical integration and the performance results.
How do you ensure players aren’t overwhelmed with too many recommendations?
We don’t flood players with content. Our models replace specific sections of the site with personalised carousels rather than adding extra layers. This keeps the experience seamless and natural, without overwhelming the user. The focus is always on quality of engagement, relevance over volume, ensuring that personalisation enhances discovery without disrupting user flow.
How do you plan to build on the success of this partnership?
betPARX is already planning to extend personalisation to additional sections and explore new use cases for the recommendation engine. There’s also interest in deploying other Sportradar AI products in the near future. This collaboration is a strong example of how our AI stack, spanning VAIX, Boost, and ad:s marketing services, can work together to deliver a full 360° engagement journey, from acquisition to retention.
What’s the potential for replicating these results with other operators in the US?
The opportunity is huge. Compared to Europe, the U.S. casino market is still relatively small, but operators are looking for ways to stand out. For mid-tier operators especially, personalisation can be a real differentiator. Sportradar’s collaboration with betPARX stands out as a concrete demonstration of measurable results. It’s clear evidence that players respond to relevant content, and that personalisation, when done right, delivers value for both the player and the operator. We see this as just the beginning, a blueprint for how AI-driven personalisation can accelerate the convergence of sports betting and iGaming experiences across regulated markets.
The post Personalisation That Performs appeared first on G3 Newswire.
At G2E Las Vegas, G3 spoke with Andy Mace, Head of Casino Personalisation at Sportradar, about the company’s collaboration with betPARX, integrating VAIX AI technology to create a more engaging and data-driven player experience. Andy, what challenge did betPARX want Sportradar to help solve? As with all of our discovery sessions, we begin by identifying…
The post Personalisation That Performs appeared first on G3 Newswire.