Competitive Mentions Campaign
Someone who comments on a competitor’s LinkedIn post is telling you they care about the problem you solve. Find those people, get their work emails, filter to your ICP, and reach out while the topic is fresh.The Play
Identify competitor content
Find LinkedIn posts from competitor company pages, executives, and industry influencers that discuss problems your product solves. Focus on posts with high engagement (50+ reactions).
Enrich contacts
Run the engager list through Deepline’s waterfall enrichment to get verified work emails, current job titles, company info, and LinkedIn profiles.
Score and filter
Filter to your ICP: target titles (VP Sales, Head of RevOps, GTM Engineer), company size, industry. Score by engagement depth — commenters > likers.
Tell Claude Code
“Scrape the last 10 LinkedIn posts from [competitor company page]. Extract everyone who liked or commented. Enrich them with waterfall email enrichment and filter to VP/Director titles at companies with 50-500 employees. Write results to competitor-leads.csv.”
How It Works Under the Hood
- Apify LinkedIn scraper extracts post engagers (likes, comments, shares)
- Crustdata or LinkedIn enrichment resolves full profiles from engagement data
- Email waterfall (Dropleads → Hunter → LeadMagic → others) finds verified work emails
- AI scoring filters to ICP and ranks by engagement signal strength
Scoring Framework
| Signal | Weight | Rationale |
|---|---|---|
| Commented on competitor post | High | Active evaluation, wrote something specific |
| Shared competitor content | High | Amplifying — deep interest in the topic |
| Liked competitor post | Medium | Passive interest, but still in-category |
| Engaged with multiple posts | Very High | Repeated behavior = active buying cycle |
| Title matches ICP | Required | Filter gate — skip non-decision-makers |
What to Expect
Results vary by competitor post engagement volume and your ICP filters. A high-engagement post (100+ reactions) yields more raw engagers; tight ICP filters reduce the final list but improve quality.Cost Estimate
- LinkedIn scraping: ~$1-10 per 1,000 profiles via Apify (varies by actor and data depth)
- Email waterfall: ~0.3 credits per contact (waterfall stops at first match)
- Total depends on post engagement volume and enrichment hit rate
Variations
- Influencer audience mining — Target posts from industry thought leaders, not just competitors
- Event attendee enrichment — Same pattern but with conference/webinar attendee lists
- Community member targeting — Extract active members from Slack communities or Discord servers
Email Waterfall → | Multi-Signal Outreach → | I Have X, I Want Y →