Corporate Directory Web Scraping and Structured Excel Data Extraction
Pain Points (Public)
Small businesses and procurement teams need structured product catalog data (manufacturer, model number, origin country) extracted from corporate supplier websites and organized into spreadsheets, but lack the technical means or time to do it at scale — even for moderately sized lists of a few hundred to a few thousand SKUs.
Suggested Approach (Public)
Build a targeted scraper using Python (BeautifulSoup or Playwright for JS-heavy pages) that crawls a specified corporate site, extracts product fields into a normalized schema, and writes results directly to Google Sheets via the Sheets API — with a simple config file so the client can swap target URLs or column mappings without touching code.
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Posted budgets are not confirmed payments. Task counts do not establish independent buyers or willingness to subscribe. Small samples are preliminary signals.
Opportunity assessment PRO
Development brief PRO
- Position as a specialized web scraping service specifically tailored for market research and corporate directory extraction into clean Excel files.
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- Build core web scraper parsing corporate directories for company names, executive emails, phone numbers, and physical addresses.
Competitor evidence PRO
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Public Demand Evidence · 2 task(s)
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