E-commerceGenerative AI & ML
Semantic Search & Personalisation Engine for a High-Traffic E-commerce Platform
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The Challenge
A fast-growing e-commerce platform with 2M+ SKUs found that 38% of searches returned zero relevant results.
Keyword-based search couldn’t understand intent or natural language queries, and there was no personalisation layer connecting browsing history to search results — driving shoppers to competitors.
Our Approach
- Replaced keyword search with a dense-vector semantic search engine powered by product embedding models fine-tuned on the client’s catalogue
- Built a user-preference model blending collaborative filtering with real-time session context for result re-ranking
- Implemented multi-lingual query understanding supporting 8 languages
- A/B tested against legacy search and rolled out progressively to 100% of traffic over 4 weeks
Results
38% → 4% drop in zero-result searches within 2 weeks of launch
+34% search-to-purchase conversion rate uplift
+22% average order value through personalised result ranking
Related Services
This project drew on our work in Vector Database Consulting, RAG Systems, Data & AI Engineering.
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