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E-commerce Recommendation Engine

Name: E-commerce Recommendation Engine
Author: Harsh Mehta

Personalized product recommendations that increase sales by 35%

E-commerce

Case study

Problem: Generic merchandising left revenue on the table; shoppers saw irrelevant products and abandoned carts.
Approach: Implemented hybrid recommendation models (collaborative + deep learning) with online serving and guardrails for inventory and diversity.
Outcome: Around 35% lift in attributed revenue from personalized suggestions and higher engagement on product surfaces.

Details

Built a sophisticated recommendation system using collaborative filtering and deep learning to provide personalized product suggestions, resulting in significant revenue increase.

Technologies Used

PythonTensorFlowRedisNode.jsMongoDB