Real results from real founders. See how we turn social profiles into pipeline.
The 3-part system that turned profile visits into pipeline
We generated 200 sales calls in 30 days for a B2B DevTools founder using a 3-part LinkedIn + X strategy: profile optimization (2% → 31% conversion), strategic engagement (poke system), and daily posting cadence (5-minute approval workflow). No viral tweets, no paid ads, no influencer partnerships—just strategic execution.
The 5 metrics that actually matter for B2B pipeline
Track 5 metrics for B2B content ROI: (1) Profile conversion rate, (2) CTA click-through, (3) Email capture rate, (4) Call booking rate, (5) Close rate. Most founders track likes and impressions (vanity) instead of pipeline and revenue (what matters). Formula: Profile visits × Conversion rate × Call booking rate × Close rate = Clients acquired.
How to market to engineers without sounding like every other agency
Generic ghostwriters fail for DevTools because they lack technical depth. Effective developer marketing requires: (1) Understanding technical concepts (vector databases, CI/CD, Kubernetes), (2) Using Capability Bridge framework (sell verbs not nouns), (3) Speaking engineer-to-engineer (peer tone, no hype). Most marketing copy says "easy to integrate" (meaningless gap). Good DevTools copy says "Deploy to 50 regions in parallel without touching your Jenkins config" (specific capability).
For technical founders who hate posting
Social selling for B2B founders: (1) Fix your profile (2% → 10%+ conversion), (2) Daily posting (5 min/day), (3) Strategic engagement (not random scrolling), (4) Track calls booked (not likes). Time investment: 35 min/week. Expected results: 20-50 calls/month by Month 1. You don't need to become an influencer or go viral. You need a system.
Positioning guide for ML products and data infrastructure
Market your AI startup by selling capabilities (what users can DO) not features (what you built). Focus on: (1) Specific accuracy metrics with benchmarks, (2) Latency at scale, (3) Cost comparisons, (4) Integration effort. Avoid: "AI-powered", "proprietary algorithms", "state-of-the-art" without data. Engineers don't buy "we use GPT-4." They buy "96.3% F1 on GLUE vs 94.1% GPT-4 baseline."
We'll audit your profile live and show you the exact gaps costing you pipeline.
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