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Trust & CompanyAmazon India Daily Product, Pricing & Category Dataset
A daily file covering the Amazon.in catalogue with 25 columns per listing — price, MRP, discount, sold-out flag, shipping charges, promised arrival date, rating and rating count, search position, and a structured three-level category hierarchy.
The column worth knowing about is category_hierarchy. It arrives as JSON with l1, l2 and l3 rather than a breadcrumb string, so grouping by department or sub-category is a parse rather than a guess at where one level ends and the next begins.
The file already exists, because this pipeline runs every morning whether you buy it or not. Most vendors start collecting after you order — which is why they quote a lead time. Here the most recent file is in your account within minutes of payment, with an API key issued at the same time.
What you get, in plain terms
Four things. If any of them is not what you expected, the sample will show you before you spend anything.
Category tree as structured JSON
category_hierarchy arrives as l1/l2/l3 in one field, so you can cut the file at department or sub-category without matching text against a path string.
Price, MRP and discount, plus their JSON forms
The flat columns are what you will query. The matching _json columns keep the raw captured structure, so nothing is lost if a listing prices unusually.
Search position and ratings
position records where the listing appeared, and rating with rating count sit alongside it — enough to watch visibility and demand move together.
However you want it
Direct download, REST API, Amazon S3, Google Cloud, Snowflake or SFTP. The API key comes with the dataset.
Fields included in this dataset
All 25 columns, in the exact order they appear in the file — this list is taken straight from the sample, not from a brochure. The free sample ships with a data dictionary giving an example value for each one.
Sample rows from the real file
Real rows from the sample file, not an illustration. The free sample is 50 listings with all 25 columns.
Coverage
2.6 million listings across 21 top-level categories, weighted towards the categories where price competition is most active.
| Category | Listings tracked | Median discount | Share with ratings |
|---|---|---|---|
| Electronics & accessories | 486,000 | 31% | 62% |
| Home & kitchen | 412,000 | 44% | 58% |
| Beauty & personal care | 358,000 | 39% | 54% |
| Grocery & gourmet | 291,000 | 28% | 47% |
| Fashion | 264,000 | 55% | 41% |
| Sports & fitness | 186,000 | 61% | 66% |
| Garden & outdoor | 174,000 | 52% | 38% |
| All other categories | 443,800 | 36% | 44% |
Only tracking your own brand and its competitors? Send the ASIN or brand list and we will price a narrower file, which costs considerably less than the full catalogue. We can also move this to a twice-daily capture if you are watching a sale period.
Historical data
The last 30 days come with the dataset. Beyond that we hold Amazon India records from January 2025 onwards — enough to cover two Great Indian Festival cycles, which is usually what people want it for. Tell us the categories and we will confirm exactly what exists.
Ask about historical dataNeed more data points?
We can extend this dataset beyond the standard 25 columns — Buy Box winner and seller count is the most requested addition, along with keyword rank, sponsored placement and your own ASIN list captured more often than once a day. Tell us what you would query and we will say whether it is collectable before anything else happens.
Request custom fields“The category JSON saved us a fortnight. Every other Amazon feed we tried gave us a breadcrumb string and we were writing split rules for each department.”
What people use this dataset for
Brands selling on Amazon
Track price, discount depth and availability on your own listings and the competitive set, grouped by the same category tree Amazon uses.
Retail and pricing teams
Benchmark online pricing against your other channels, with MRP, discount and shipping charges as separate fields.
Category managers
Watch assortment and discount shift within a sub-category, and see where sold-out listings are concentrated.
Analysts and investors
Category-level price and rating series for demand estimation, share shift and festive-season analysis.
About Amazon India marketplace data
Amazon.in is the largest horizontal marketplace in India by catalogue depth, and the one where price competition is most visible. Its category tree is also unusually deep, which is why the shape of the category field matters more than it sounds.
Why the category hierarchy is JSON rather than a string
A breadcrumb string forces you to guess where one level ends and the next begins, and the separator changes between departments. Here category_hierarchy arrives as an object with l1, l2 and l3 keys, so a group-by on department is a field access rather than a regular expression you have to maintain.
Why empty discount fields are correct
When a listing is not discounted, discount is empty rather than zero. That distinction matters: a zero reads like a measured value, an empty field reads like an absent state. In the sample a fifth of listings sat at full price with the discount column blank, and treating those as zero-percent discounts would understate median discount across the category.
What the JSON price columns are for
product_price_json, mrp_json, discount_json and shipping_charges_json preserve the structure as captured, including cases where a listing prices by variant or bundles shipping oddly. The flat columns are what you will query day to day; the JSON columns are there so nothing is discarded when a listing does something unusual.
Is collecting this data legal?
Collecting publicly visible product and price information is generally lawful in most jurisdictions. Actowiz collects only public pages, respects robots.txt and platform terms, holds no personal data, and aligns with GDPR and CCPA. We are ISO 9001 and ISO 27001 certified, and this dataset carries documented provenance so your legal team can review the source before you buy.
Frequently asked questions
Related datasets, same field names
These join to the file above without any reconciliation work, which is why most buyers take more than one.
