Your cold emails aren’t landing? they’re too cold. generic intros. zero context. you’re just another name in their inbox. Want replies? Start with relevance! Here’s how i do it: → pull insights from their website, linkedin, or job description → turn it into a natural opener (not robotic nonsense) → add 2–3 unique personalization fields in your sheet → run it through n8n or zapier → now every email feels handcrafted—without the manual work example? “Saw your team helps B2B startups cut churn, that’s exactly why I’m reaching out.” see the difference? real, relevant, and about them—not you. Bonus: run a 4-email sequence, each with a new angle. same offer, different hook. watch replies go up. Stop being lazy with personalization. Tools make it easy. What wins is effort. 👇 what’s your biggest block with cold email right now?

Made $5k in 30 days with cold email and AI. Solo. No team. no fluff. no pretending. just systems that work. I built a AI b2b lead gen agency from scratch. Spent $377. Closed 2 high-ticket clients. Collected $5,000. Here’s the breakdown: → 7,300 emails sent → 97 replies → 30 positive replies → 10 meetings booked → 2 closed deals How? → 50+ warm inboxes via zapmail → apollo + apify to scrape and enrich leads → ai for research, personalization, and follow-ups → instantly to push 1,000+ cold emails/day no team. no fancy brand. no paid ads. just a clear offer and real execution. Here’s what matters: • your infrastructure is everything • $377 is enough to get going • AIsaves you hours (if you know how to prompt) • most people overthink, i just hit send • high-ticket b2b buyers want value—not fluff Cold email still works. if your list is good and your message is sharp. 👇 What’s really stopping you from doing this?

You're throwing away half your leads. here's how to fix it. You verify 10k emails. Only 5k come back valid. The rest? Catch-alls. Unusable. Trashed. But here’s what no one tells you: 50-60% of catch-alls are actually deliverable. You just need a better tool. I tested BounceBin. Recovered 2.5k extra leads from a 10k list. Bounce rate? Still under 2%. That’s thousands of leads you’d never reach otherwise. How? → BounceBin doesn’t just “verify” It tests inbox behavior using AI. Goes beyond basic SMTP checks. → Works great alongside MillionVerifier Validate first, recover catch-alls second. → Real numbers, real ROI More leads → more replies → more meetings booked. Stop wasting half your list. Start turning catch-alls into conversions. How are you handling catch-all emails right now? Let’s compare strategies 👇

no budget. no tools. no excuses. I built a lead list with 1000+ emails in 27 minutes using google + Chatgpt for FREE Here’s the process: → Open Google Search this: site:instagram.com "real estate" gmail.com → Grab unstructured results emails, names, phone numbers whatever shows up → Drop it into Chatgpt prompt: “organize this into clean columns: name, email, phone, url” → Download as .csv Start outreach Book meetings Why this works: no tools to learn no forms to fill just pure, raw data turned into pipeline Want to scale it? → Vary your search terms → Go beyond gmail: yahoo, outlook, etc → Target different platforms → Pair email with instagram dms → Keep outreach volume low (20/day max per inbox) This method books 10+ calls/month if you actually do it and do it consistently Will you test it out, let's discuss in the comments?

8,000 cold emails. 27 new opps. 0 hours spent replying. i tested AI reply agents on a B2B SaaS campaign. not AI hype. real results. The setup → instantly. ai → trained it with my past replies → integrated Slack + Calendly → gave it tone, rules, and edge The numbers (30 days) → 8,000 emails sent → 27 opps booked → 74% of replies handled without me → 4.4 hours saved → not one awkward message sent What surprised me most → it turned “i’m too busy” into “circle back in 2 weeks” → handled objections like a pro → sounded human every time How to get this right → train with your real replies → give it strict rules + clear tone → start with human-in-the-loop → scale to full autopilot later this isn’t about saving time it’s about scaling smart without killing personalization