Jay Feldman | Lead Gen Jay @leadgenjay

Results after applying this system: ✅ Consistent doctor clients month over month ✅ Higher reply rates with mechanism-led emails ✅ Built referral proof from scratch using the 3-tier name-drop method This system runs 24/7 and compounds with every new case study. Which step would help your agency most? Follow @LeadGenJay for more B2B client acquisition systems. ▶️ Full Medical Marketing Playbook: youtu.be/YnoKk8_vVjQ

My solution: 1️⃣ Source verified doctor emails via BookYourData — filter by specialty + owner (<50 employees). Skip Apollo. 2️⃣ Segment by specialty (target: plastic surgery, med spas, cosmetic dentistry, concierge medicine — avoid radiology/anesthesia). 3️⃣ Use the 4-sentence cold email: → Personalized opener → Mechanism-led pain question → Referral name-drop → Soft CTA only 4️⃣ Send via Instantly AI + warmed domains from InboxInsiders for deliverability. No case studies yet? Offer a free front-end service first. Deliver in 24hrs. Then pitch a discounted case study deal for a testimonial.

I landed doctor clients consistently for 6 years using one simple framework. Most agencies think this niche is too saturated. It's not. It's just noisy. My exact process below: 🧵

Results after full team rollout: ✅ Entire 82-person team has AI access in Slack ✅ Marketing auto-monitors Meta Ads vs Hyros discrepancies ✅ Sales gets bi-weekly automated reports — zero manual work ✅ Total cost: ~$100/month vs thousands in individual subscriptions This system runs 24/7 and keeps surfacing new automation use cases on its own. Which step would help your business most? Follow @LeadGenJay for more AI automation systems 🚀 ▶️ Full breakdown: youtu.be/Oo1nNwY6wPo Free credits: viktor.com/?via=jay-leadg…

My solution with Viktor: 1️⃣ Connected Viktor to Slack in under 5 mins — no dev work needed 2️⃣ One-click integrations: Google Ads, Stripe, Hyros, Notion & 15+ more 3️⃣ Switched default model from 'Smartest' → 'Balanced' mode (50% fewer credits, same quality) 4️⃣ Lowered heartbeat & workflow discovery frequency to kill background credit burn 5️⃣ Set role-based permissions per integration to protect sensitive data ⚠️ Gotcha: I burned $600 my first week by skipping steps 3 & 4. Don't be me.

I replaced Claude Code for my 82-person team using a $100/month Slack AI agent. Setup took less than 5 minutes from my phone. My exact process below 👇🧵

Results after 30 days: ✅ Reply rates: 2% → 5% (Reverse Lead Magnets as CTA) ✅ Entire campaign pipeline runs 24/7 autonomously ✅ Replaced Clay, Apollo & n8n — saving $000s/month This system runs while you sleep. Which step would help your business most? Follow @LeadGenJay for more AI automation systems. 🎥 Full breakdown: youtu.be/MGDlG4JyjVk

My solution inside Claude Code: 1️⃣ Scrape + verify leads via Consulti AI API (deduped automatically) 2️⃣ Run List Optimize skill — qualifies, researches & personalizes leads using Perplexity API 3️⃣ Auto-Improve loop rewrites copy until it hits your quality bar 4️⃣ Deploy campaigns to Instantly or Email Bison via API — zero manual logins Screenshot attached 👇

I rebuilt my entire cold email system inside Claude Code. No Apollo. No Clay. No n8n. One AI chat window now handles scraping, verifying, writing, and deploying full campaigns. Reply rates jumped from 2% → 5%. My exact process below: 🧵

Results from 38,647 emails sent 13,279 senior finance leaders reached 12,689 contacts completed the full sequence 57 qualified opportunities generated 25% of all positive replies converted into qualified pipeline The product never changed. The offer never changed. Fixing the list and focusing the message changed everything. The message only lands when the list is right.

So we rebuilt everything from scratch 1. Audited the full lead list and cut every contact outside the real ICP 2. Rebuilt targeting in Apollo and Clay around U.S. manufacturers and e-commerce companies at $20M to $500M revenue, CFO, Controller, and VP of Finance titles only 3. Killed the two angles that produced almost no replies across 40,000+ emails and committed 100% of sending to the one framing that worked: direct rate negotiation 4. Anchored the sequence on a real savings reference ($325,000 saved on $1.6M in parcel spend) with a free contract analysis as the next step 5. Deployed warmed sender infrastructure across multiple domains to protect inbox placement throughout the run

How we got 57 qualified opportunities for Source1 Parcel with cold email thread:

Results from the single relaunch campaign: 38,647 total emails sent 13,279 senior finance leaders reached 12,689 contacts completed the full sequence 57 qualified opportunities generated 25% of all replies converted into a qualified opportunity Same product. Same offer. Just a list that finally matched the buyer. The system runs continuously. The pipeline keeps filling. Cold email copy does not fix a broken list. But the right list with one proven message can change everything.

Here is what we rebuilt: 1. Audited the full contact list and removed every shipping-adjacent company that would never buy 2. Rebuilt targeting in Apollo and Clay around U.S. manufacturers and e-commerce companies doing $20M to $500M in revenue with hard exclusions locked in from day one 3. Targeted only CFOs, Controllers, and VPs of Finance, the people who actually feel the pain of overpaying on carrier contracts 4. Killed two underperforming messaging angles and went all in on one direct rate-negotiation framing that had already proven it converted 5. Anchored the sequence on a specific proof point ($325,000 saved on $1.6M in parcel spend) and offered a free analysis as the next step

How we got 57 qualified opportunities for Source1 Parcel with cold email The offer was not the problem. The list was. Details below: