How Query Quotient transformed Lenskart's search experience, delivering personalized product discovery to millions of customers with fast, relevant results.
Lenskart, India's largest eyewear retailer with over 500 stores and millions of online customers, faced critical challenges in delivering a first-class digital shopping experience:
5000+ SKUs with intricate attributes - frame shape, material, color, size and lens type - were undermining search accuracy.
Personalized recommendations for 10M+ users based on face shape, preferences and purchase history were computationally intensive.
During sale events traffic spiked 10x, causing search failures and lost sales.
Out-of-sync inventory between 500+ stores and online meant out-of-stock items kept appearing in search.
We designed an Elasticsearch solution that combined advanced search with machine learning-powered personalization.
Search that understands customer intent and preferences:
Real-time personalization that scales to millions of users:
Infrastructure that absorbs extreme traffic variation:
Search results that reflect what is actually in stock:
The work delivered clear business and technical results:
“Query Quotient revolutionized our digital commerce capabilities. The personalized search experience they built has become our competitive advantage. Our customers now find exactly what they're looking for in seconds, and our conversion rates have exceeded all expectations. The 300% increase in conversions speaks for itself.”
Natural-language queries, visual similarity and personalized re-ranking are the retrieval foundation for AI shopping assistants. Getting them fast and accurate on a complex catalog is what makes conversational commerce trustworthy.
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