#cold-email

Build a systematic cold email testing program. Setup: 1. Define hypothesis (subject line, CTA, length). 2. Split list into equal segments (minimum 100 contacts each). 3. Send variant A to segment 1, variant B to segment 2. 4. Wait 3-5 days for statistical significance. 5. Measure open rate, reply rate, meeting booked rate. 6. Calculate winner (minimum 95% confidence). 7. Roll out winner to remaining list. Variables to test: personalization depth, value proposition clarity, email length (50 vs 150 words), CTA placement. Use Lemlist or Woodpecker for tracking. Document learnings in playbook.

Design a high-converting cold email sequence. 7-email cadence: Email 1: Problem-focused (no pitch). Email 2: Case study/social proof. Email 3: Value proposition. Email 4: Breakup email (last chance). Email 5: Different angle/resource. Email 6: Direct ask for meeting. Email 7: Final touchpoint. Best practices: personalize first line, keep under 100 words, single CTA, A/B test subject lines. Send over 2 weeks. Track open and reply rates. Optimize based on data. Aim for 5-10% reply rate.

Personalize outbound emails efficiently. Research (2-3 mins per prospect): 1. Recent LinkedIn post or company news. 2. Mutual connections. 3. Technology they use (BuiltWith, SimilarWeb). 4. Recent job postings (indicates growth/pain). Personalization tiers: High-value accounts (custom per person): '[Name], saw your post about hiring 3 SDRs. Are you also scaling your sales tech stack?' Medium-value (templated with custom first line): 'Noticed [company] is using [tool]. How is that working for [specific pain point]?' Low-value (segment-based): '[Industry] companies typically face [challenge]. Curious if you're experiencing this?' Tools: Phantombuster for data enrichment, ChatGPT for variation generation, Instantly/Lemlist for sending. Batching: research 50 prospects, write custom lines, plug into sequence. Track: personalized emails get 3-5x reply rate vs generic. Test different personalization levels to find ROI sweet spot.