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How an Indian B2B Firm Scraped 50K+ Seller Profiles for Lead Generation

Author : Actowiz Solutions | Published On : 21 Aug 2026

https://www.actowizsolutions.com/indiamart-findgst-google-seller-scraping.php


At a Glance

  • Client: Indian B2B lead generation / sales intelligence firm

  • Geography: India — Pan-India seller coverage

  • Platforms Scraped: IndiaMart, FindGST, Google Business

  • Project Duration: 7 weeks

The client operated a B2B lead generation firm helping its customers reach Indian businesses across categories — manufacturers, wholesalers, distributors, service providers. Their target prospect universe was the millions of small and mid-sized Indian businesses that operated below the radar of enterprise sales intelligence tools (ZoomInfo, Apollo) but represented enormous addressable demand.

Three platforms were strategically important:

  • IndiaMart — India's largest B2B marketplace, with millions of seller listings across categories

  • FindGST — registered GST data showing verified business identities, addresses, and registration details

  • Google Business — store-locator-level business information with reviews, ratings, and contact data

Building a consolidated database across these three sources, with consistent entity resolution (matching the same business across all three), was the operational challenge. Manual research was impossible at the scale the client's outbound motion required.

The Approach

Actowiz Solutions built a tri-platform Indian B2B seller intelligence pipeline:

  • IndiaMart seller extraction — captured seller listings with business name, category, location, contact information where publicly displayed, and listing depth signals

  • FindGST data extraction — verified business registration data including legal name, GST registration number, registration status, and state-level filings

  • Google Business profile extraction — captured business listings with reviews, ratings, hours, and contact information

  • Entity resolution across platforms — used a combination of business name normalization, address matching, and GST number cross-referencing to identify the same business across all three sources

  • Quality scoring — assigned confidence scores per business based on signal density across platforms

The Solution Architecture

Indian B2B seller data has enormous variation in quality and structure. The same business might appear with slightly different names across platforms, with addresses in different formats, with category tags in different taxonomies. The extraction pipeline handled this with normalization logic and entity resolution that the client's team validated against known reference businesses.

Output was delivered as a master B2B seller database, with category-level and geography-level drilldowns for the client's lead generation customers.

Results

  • 50,000+ verified seller profiles — consolidated across the three platforms

  • High-confidence multi-platform records — businesses appearing across two or three platforms with consistent data (a high-trust signal for outreach)

  • Reduced lead research time — for the client's B2B customers from days to minutes — they could query the consolidated database directly

  • Compliance attribution — every record included source platform and timestamp, supporting the client's compliance posture for outreach

  • Reusable infrastructure — same pipeline architecture extended to support additional Indian B2B platforms (TradeIndia, Justdial Business, etc.)

Why This Matters For You

If you operate B2B sales, marketing, or lead generation in India, the standard global sales intelligence tools (ZoomInfo, Apollo, Lusha) have meaningful gaps in Indian SME and mid-market coverage. The data that actually matters for Indian B2B sales lives in IndiaMart, FindGST, Justdial, Google Business, and adjacent Indian platforms. Building a consolidated intelligence layer across these sources is what separates serious Indian B2B operations from those running on global tools that don't fit the market.

The same pattern works for other emerging market B2B intelligence: Latin America (Mercado Libre B2B, regional directories), Southeast Asia (Lazada Business, regional B2B platforms), and similar geography-specific business intelligence needs.