Case studies
Search & catalog quality
Flipkart — Supermart grocery marketplace
50%lift in search engagement
20%better autosuggest click-through
15%fewer seller defects and complaints
View as table
| Measure | Start | After 2–3 quarters | Change |
|---|---|---|---|
| Search engagement | 100 | 150 | +50% |
| Autosuggest accuracy | 100 | 120 | +20% |
| Seller defects | 100 | 85 | −15% |
The problem
Flipkart Supermart’s search and autosuggest needed to become more relevant for customers, and catalog quality across 300+ new SKUs a day needed governance to keep seller defects and complaints down.
The approach
Optimized catalog structure and tuned search relevance for autosuggest. Ran data taxonomy and catalog governance for 300+ daily SKUs. Analyzed 1,000+ customer reviews a week and NPS telemetry alongside 50+ weekly vendor partnerships, turning friction points into 3–4 actionable feature recommendations a month.
The impact
Autosuggestion click-through accuracy improved 20% in six months, search engagement rose 50%, and seller defect rates and complaints fell 15%.