Seller-level view of Indian marketplaces: storefronts, assortment by category, ratings and monthly unit and revenue estimates for 1.4 million active sellers.
Data product · Listing updated 11 Nov 2026
India
Monthly file by the 7th business day
1.4 million active sellers and 52 million seller-product pairs
Mid-market, Enterprises
Public seller storefronts and product listings on Indian marketplaces; anonymized partner-seller sales for calibration
Monthly collection (weekly for top sellers) with model-based sales estimation calibrated on partner data
See who sells what on Indian marketplaces and how fast it moves, at seller and product level.
Seller storefronts and listings are collected from public marketplace pages every month, with weekly snapshots for the top 50,000 sellers. Sales estimates come from a model that combines sales-rank movements, review velocity and observed stock depletion, calibrated against anonymized sales figures shared by partner sellers. Median absolute error on the calibration set is about 22% at product level and lower at seller level, so the estimates are best used for ranking and trends rather than exact revenue. Seller names are business display names as published by the marketplace; no personal contact details are collected or delivered.
13 fields as documented by Bazaarlens Commerce Data.
| Field | Type | Description | Example |
|---|---|---|---|
| seller_id | string | Bazaarlens seller ID | — |
| marketplace | string | Marketplace where the storefront operates | — |
| seller_display_name | string | Business display name as published | — |
| seller_city | string | City shown on the storefront, where published | — |
| active_listings | integer | Number of live listings | — |
| top_category | string | Category with the most estimated sales | — |
| private_label_share | number | Share of listings under the seller's own brands | — |
| seller_rating | number | Average seller rating | — |
| rating_count | integer | Number of seller ratings | — |
| est_monthly_units | integer | Estimated units sold in the month | — |
| est_monthly_gmv_inr | number | Estimated gross merchandise value, INR | — |
| estimate_confidence | string | high, medium or low | — |
| first_seen | date | Date the storefront was first observed | — |
Free sample available on request
The provider sends a sample file so you can test fit and quality before you buy.
Prices in USD, as published by Bazaarlens Commerce Data
single category, 12-month history
all categories, monthly refresh
Converted amounts use DataStoa display rates and are approximate. Bazaarlens Commerce Data quotes the final price, taxes and terms.
Request detailed pricing1 country.
Time coverage: 2021 to present.
Provider-reported
Latency: Monthly file by the 7th business day
DataStoa has not audited these figures. Ask the provider how they are measured, or test them on a sample.
The licence is agreed directly between you and Bazaarlens Commerce Data. This summary is provider-reported; the linked terms prevail.
Not listed: use in commercial products, AI / ML model training, AI retrieval and grounding, redistribution allowed, research use. Ask Bazaarlens Commerce Data if you need any of these.
Product, price, seller and review data from Indian and SE Asian e-commerce
Bazaarlens tracks product catalogs, prices, promotions, sellers and reviews across leading Indian marketplaces and D2C stores, with growing coverage in Southeast Asia. Every product is matched to a stable Bazaarlens product ID so buyers can compare the same item across stores and over time.
Also available on: Snowflake Marketplace, AWS Data Exchange
What buyers say about Bazaarlens Commerce Data. Reviews cover the provider, not only this listing.
from 3 reviews
Aspect-level sentiment on noise, build quality and after-sales service showed exactly where our mixer grinders lost to competitors. Reviewer identities are stripped, which kept our legal team happy.
Arjun P., Product insights manager, Kitchen appliances maker
The assortment data is very good. Estimated sales for sellers are useful for ranking competitors but were off by a fair margin for two sellers whose real numbers we know. Treat them as relative, not absolute.
Neha K., Category strategy lead, Consumer electronics brand
We track about 3,000 SKU and store pairs every day, including flash-sale prices, and the file is in our bucket before the pricing stand-up. Product matching to our catalogue needed one round of corrections in the first week.
Rohan M., Pricing manager, D2C personal care brand