Recipe: Lead enrichment
Enrich CRM rows with web facts — company size, funding, tech stack, social profiles, and recent news — so your sales team never reaches out blind.
Input
CSV or CRM export with company names and domains. Minimum: one identifier column.
Process
Parallel web scraping with rotating proxies, NLP entity extraction, deduplication pass.
Output
Enriched CSV with 15+ new columns: employee count, industry, tech stack, LinkedIn, funding rounds, news sentiment.
How it works
Parse input
Read CSV, detect column types (company name, domain, URL). Validate domains via DNS resolution. Flag rows with missing or malformed identifiers.
Scrape & extract
Fetch homepage, LinkedIn company page, Crunchbase profile, and recent news articles. Extract structured facts using CSS selectors and regex patterns tuned per source.
Normalize & merge
Deduplicate facts across sources. Normalize employee ranges, funding amounts, and industry labels. Merge into a single enriched row per lead.
Export
Write enriched CSV. Optionally push back to CRM via API (Salesforce, HubSpot). Attach confidence scores per field so reps know what to trust.
Quick start
# With CRM push
$ nimbus recipe run lead-enrichment --input ./leads.csv --push-to hubspot
# Enriching 247 leads...
# 241 enriched, 6 failed (invalid domains)
# Pushed 241 records to HubSpot
✓ Done in 4.2s
Output schema
| Column | Source | Confidence |
|---|---|---|
| employee_count | high | |
| industry | Crunchbase | high |
| tech_stack | BuiltWith / Wappalyzer | medium |
| funding_total | Crunchbase | high |
| linkedin_url | Google / LinkedIn search | medium |
| news_sentiment | NewsAPI / GDELT | low |
Ready to enrich your pipeline?
Run this recipe on your first 100 leads free. No credit card required.