B2B Manufacturer Research & Data Verification

Conducted in-depth B2B research and data verification for Weknow Network, focused on the helmet and safety equipment manufacturing sector. The project required identifying, classifying, and fully profiling companies across multiple European countries to build a clean, structured dataset the client could use for targeted outreach.

The client had a raw list of 15+ companies across Norway, Sweden, Denmark, the UK, and Germany. But the data was incomplete, outdated, or unverified. They needed:

Every company classified as active or inactive

Business type identified (manufacturer, wholesaler, retailer, distributor, or service provider)

Only manufacturers fully profiled with verified data

Every physical location mapped separately (factories, offices, HQs) with dedicated entries for each

This wasn't a simple data cleanup. It required cross-referencing multiple sources, verifying information across languages, and structuring everything so each location had its own complete row of data.

1. Company status verification Started by confirming whether each company was still active. Checked official registries, company websites, and LinkedIn company pages. Inactive companies were flagged immediately so no time was wasted on dead leads.

2. Business classification For every active company, I determined whether they were a manufacturer, wholesaler, retailer, distributor, or service provider. Only manufacturers moved forward for full profiling. Others were tagged with their correct classification and left unpopulated per the client's instructions.

3. Multi-location mapping This was the most detailed layer. Companies like Axalta Coating Systems had multiple sites (production facility on the east coast, offices on the west coast, distribution center near Stockholm). Each location got its own dedicated row with full data: address, phone, postal code, and establishment type (factory vs. HQ vs. office).

4. Contact data sourcing and verification For each location, I sourced and verified:

Office email addresses (updated where the client's existing data was outdated)

Direct phone numbers

Company websites

Postal codes

VAT numbers (best efforts, where publicly available)

NACE industry codes

Year of establishment

Workforce size (updated with current figures)

Used Apollo.io, ContactOut, Seamless.AI, and LinkedIn for sourcing. Cross-referenced everything against company websites and official registries to ensure accuracy.

5. Data structuring and delivery Organized all verified data into a structured Google Sheets spreadsheet. Each row represented a single location entry. Columns covered: company name, country, active status, classification, website, email, establishment type, address, phone, postal code, year founded, workforce size, volume indicators, company description, VAT number, and special notes.

15+ companies researched across 5 European countries (Norway, Sweden, Denmark, UK, Germany)

Each company classified by business type (manufacturer, wholesaler, retailer, distributor, service provider)

Multi-location mapping with dedicated entries for factories, offices, and headquarters

Verified and updated contact data: emails, phone numbers, websites, VAT numbers

Workforce size and company descriptions updated with current information

Clean, structured spreadsheet ready for client outreach

Delivered a fully verified, structured dataset that the client could immediately use for targeted outreach to helmet manufacturers across Europe. Companies that were inactive or non-manufacturers were clearly flagged, saving the client's sales team from wasting time on dead leads. The multi-location mapping gave them granular targeting capability they didn't have before.

Google Sheets, LinkedIn, Apollo.io, ContactOut, Seamless.AI, Chrome Extensions, Search Engines, Official Company Registries