Review data across six e-commerce and q-commerce platforms

The challenge

The client's customer sentiment was scattered across marketplaces, beauty specialists and quick-commerce apps, with no single view of what shoppers were actually saying about their products — or their competitors' — across the channels that mattered. Each platform exposed reviews differently, and pulling them together manually meant six incompatible formats and no way to compare sentiment across channels.

What we built

We built review and rating extraction across Flipkart, Nykaa, Purplle, BigBasket, Blinkit and Zepto — capturing ratings, review text, verified-purchase flags and dates. Everything was PII-scrubbed at the source (reviewer names and identifiers removed, the review content and metadata retained) and delivered in one unified schema so reviews could be compared and analyzed across all six platforms together.

How it's delivered

Reviews land as a single structured feed, one schema across all six sources, updated on the client's chosen cadence. Because the data is clean and normalized, it feeds directly into sentiment and theme analysis without per-platform reconciliation — supporting our reviews & ratings intelligence use case.

The outcome

The client gained a single, cross-channel view of customer sentiment — able to see how a product was received on Nykaa versus Flipkart versus quick commerce, track review themes across the full funnel, and spot issues early wherever they surfaced. The compliance-first, PII-scrubbed approach meant their legal team was comfortable with the data from day one.