Betting and gaming companies face challenges in personalizing their offerings to drive player engagement and retention. Building custom recommendation systems is costly and complex, often requiring dedicated data science teams. Player Engagement solutions on AWS use pre-built machine learning models and partner offerings to streamline this process. By rapidly implementing personalized game, bet, and promotional offer recommendations, these companies can enhance patron experiences and maximize engagement. This cost-effective approach allows businesses to focus on core operations while maximizing responsible player engagement.
Partner Solutions
Software, SaaS, or managed services from AWS Partners
![](https://d1.awsstatic.com/Gradient-Divider-orange-blue.317b0a6e1db69aa03ede8c5fd6fad7ee117a626f.jpg)
Guidance
Prescriptive architectural diagrams, sample code, and technical content
![](https://d1.awsstatic.com/Gradient-Divider-orange-blue.317b0a6e1db69aa03ede8c5fd6fad7ee117a626f.jpg)
Total results: 2
- Publish Date
-
Real-Time Casino Player Analytics on AWS
This Guidance shows how your developers can build a real-time analytics pipeline that uses AI to deliver effective marketing offers during game sessions. By using gaming-machine and shuffler data to update machine learning (ML) models in real time, this pipeline predicts the best offers for individual customers. The analytics pipeline then returns these findings to your gaming machines and applications so that you can promote offers based on each user’s customer profile.