Personalisation That Performs

Summary

At G2E Las Vegas, G3 spoke with Andy Mace, Head of Casino Personalisation at Sportradar, about how Sportradar integrated its VAIX AI personalisation engine with betPARX to create a more engaging, data-driven casino experience. The collaboration used a phased, modular approach — starting with three personalised content carousels — and leveraged Sportradar’s mature models and betting data to surface the most relevant games for players. Results included a 200 per cent rise in unique titles played, a 273 per cent increase in session duration and strong uplift in wagering, all achieved with a single API integration and operator controls for campaign overrides.

Key Points

VAIX is a mature AI personalisation engine combining deep-learning and transformer models with nine years of data refinement.
Integration with betPARX was completed via Sportradar’s single API framework, with front-end support from Playtech.
The deployment began with three personalised carousels chosen during discovery to deliver quick, measurable impact.
The AI starts to react after one gameplay session and typically reaches optimal accuracy after a few sessions.
Outcome highlights: 200 per cent increase in unique titles played and 273 per cent longer session duration.
53 per cent of players engaged with the AI-powered carousels, showing stronger repeat visits and cross-vertical movement between casino and sportsbook.
betPARX retains control via a “Boost” tool to override or promote specific titles or campaigns when needed.
Unexpected but welcome: wagering volumes rose significantly, supporting Sportradar’s “responsible by design” approach to AI personalisation.
Approach is modular: start narrow, prove success against KPIs, then expand into additional sections and use cases.

Why should I read this?

Short version: if you’re in iGaming and want to move the needle on engagement fast, this is worth your time. It’s a neat, real-world example of AI-driven personalisation delivering measurable lifts in discovery, session length and wagering — without a massive rebuild. The interview cuts to the practical bits: rollout, speed of impact, operator controls and real results.

Author style

Punchy: this piece emphasises clear, business-facing outcomes. If you care about retention, revenue and a practical path from pilot to scale, the details here matter — it’s not just hype.

Context and Relevance

Personalisation is becoming a key differentiator in regulated iGaming markets, especially in the US where operators seek ways to stand out beyond game catalogues. This case study showcases how a proven AI stack can accelerate discovery and cross-sell between casino and sportsbook, lower acquisition costs via better retention, and provide a repeatable blueprint for mid-tier operators. The success signals strong potential for wider adoption as operators prioritise player experience and measurable ROI.

Source

Source: https://g3newswire.com/personalisation-that-performs/