How do you combine a customer’s historical data and current browser activity for use in a real-time recommendation engine?
Recommendation engines and algorithms are a huge business at companies such as Amazon, Wal-Mart, and Netflix. But how do you take into account a current shopper’s browser activity when making e-commerce recommendations?
Most recommendation systems rely on static data, such as purchase history and customer segmentation. However, in-memory computing platforms now allow “context-aware” recommendations that can link that static data to real-time browsing actions.
In this solution brief, you will learn:
- Benefits of context-aware recommendations.
- Challenges of personalized e-commerce systems.
- How in-memory computing can deliver on the promise of real-time recommendations.
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