IndiaMART Seller Scraper.
Structured. Exportable. Yours.
IndiaMART is where Indian manufacturers and wholesalers list what they sell. This extractor collects supplier records against a product category — company, location, contact and the products they deal in.
COMPANY RECORDS EXIST.
USABLE LISTS DON'T.
Business directories hold verified company records — trade names, categories, locations, contact details and, in some cases, statutory filings and director information.
Each record is designed to be read on its own. There is no way to export a category, so building a prospect list means opening profiles one at a time and copying fields by hand.
Category Search
You filter the directory to a business type and region.
Profile by Profile
Each company needs its own page visit to reveal contact details.
Manual Transcription
Names, numbers and addresses are copied across into a spreadsheet.
Incomplete List
The work stalls, and the prospect list covers a fraction of the market.
Turn a Category Into
a Prospect List.
Filter the directory to the segment you care about and let the extractor collect every record. What took a week of copying becomes a structured file you can hand to a sales team the same morning.
Category-Level Collection
Extract an entire filtered category rather than working through profiles individually.
Contact Details Included
Phone numbers, email addresses and websites are captured where the directory makes them public.
Consistent Field Mapping
Every record lands with the same columns, so the file is usable without cleanup.
Repeatable Refreshes
Re-run the same collection later to catch new listings and updated details.
Fields Captured by
IndiaMART Seller Scraper.
Each field arrives in its own column. Where a source does not publish a value, the column is left empty rather than guessed at.
Company Names
Contact Numbers
Business Addresses
Product Categories
Member Since Data
Response Rates
Company Type
Profile URLs
Four Steps, No Code.
Install
Add the browser extension. Nothing to deploy and no API key to manage.
Search
Open the source and apply the filters you would use normally — category, location, price, whatever narrows it.
Collect
Start the run. It follows pagination and scrolling through the full result set while you watch.
Export
Download as CSV or Excel with consistent columns, ready for your CRM or spreadsheet.
IndiaMART Seller Scraper is built for teams that need this regularly rather than once.
Used by:
These share aligned output columns, so collections merge without reformatting.
WHY SCRIBBLE LINKS?
Most tools hand you a raw dump and leave the cleanup to you.
IndiaMART Seller Scraper is engineered around the output — consistent columns, empty cells where a source is silent, and the same structure on every run so a second collection is comparable to the first.
Everything You Need
TO KNOW
Common questions about IndiaMART Seller Scraper, what it collects and how the data can be used.
Can I search by product rather than company?
Yes. Search IndiaMART for a product category and the extractor collects every supplier listed against it.
Is this useful for sourcing as well as selling?
Both. Procurement teams use it to build supplier shortlists, and sales teams use it to identify manufacturers in a segment.
Do I need to know how to code?
No. You select the data you want directly on the page, and the extractor handles the rest. There is nothing to install beyond the browser extension and nothing to configure in code.
What formats can I export to?
Collected data can be exported as CSV or Excel, with JSON available where the structure calls for it. Columns stay consistent between runs, so files drop straight into a CRM or spreadsheet.
Is this allowed?
The extractor works only with publicly available information — the same content any visitor can see without logging in. Login-protected and private data is not supported. You remain responsible for following the terms of the sites you collect from and any applicable data protection law.
Better Data.
Better Systems.
Better Businesses.
See IndiaMART Seller Scraper running against your own target source before you commit to anything.