Back to Work
Data ScienceClient: RetailMax
E-Commerce Recommendation Engine
35% increase in sales
In e-commerce, personalization is king. RetailMax needed to move beyond generic "bestsellers" lists to truly individualized shopping experiences.
Hybrid Filtering Approach
We implemented a hybrid recommendation engine combining collaborative filtering (users like you bought...) and content-based filtering (items similar to this...).
Real-time Personalization
The engine updates user profiles in real-time as they browse, adjusting recommendations instantly to reflect their current intent and session context.
Results
A/B testing showed a 35% increase in cross-sell revenue and a 20% uplift in average order value (AOV).