Most lead lists are half-finished. Names, emails — and nothing else. Here is what scraping and AI enrichment can do with them, and why complete profiles directly produce better results.
You have a CSV: 500 rows, name, company, email. That is it. No context, no hook, no idea whether the contact is even relevant. To turn that into a personalised message, you would need to manually research every single lead — open their website, scroll LinkedIn, take notes.
Nobody does that for 500 contacts. So generic templates get used — and generic templates produce generic results.
Scraping in getProspects means automated analysis of publicly available data sources to extract real context about a contact. No database queries, no list purchases — structured reading of information that is public anyway.
The system analyses for each contact:
The raw data points from scraping are turned by AI into structured context. The result is not a data dump but a clear profile: what does this company do? What is the likely challenge? Which hook works best for a first message?
This profile feeds directly into email generation. That is why a getProspects email does not sound like a template — because it is based on real data points, not fill-in-the-blank text.
getProspects only scrapes publicly available information. All processed data stays on EU servers. The scraping module logs the origin of every data point — for full GDPR transparency.
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