NEVER manually research prospects again... This AI system replaced a $60K/year SDR. While B2B founders waste 3 hours daily on prospect research... I built an automation that booked me 21 qualified meetings in 10 days. ↳ 3 already closed. $17,490 in new revenue. The capabilities are insane: - Scrapes entire websites in 30 seconds - Analyzes service pages, case studies, blog posts - Generates hyper personalized icebreakers - Does 20 minutes of research per prospect automatically I've used this for SaaS companies, marketing agencies, consultants, and B2B service providers. And it costs $0 compared to hiring research assistants or buying expensive data tools. The system handles everything: → Deep prospect research across all website pages → Personalized email openers that get replies → Context that makes cold outreach feel warm → Scales to 100+ prospects per day ↳ My reply rate jumped from 1.2% to 8.3% using this. Want the system? 1. Follow me 2. Like this post 3. Click "SYSTEM" and get the free template from our website.

This is what happens when you stop manually researching prospects. Most people are still doing cold email like it's 2015: Buy a lead list. Plug into a tool. Send "Hey, we help businesses grow..." Hope for mercy. That's not outreach. That's spam with your name on it. Here's what actually works in 2026: Campaign 1 (Mar 11-13): - 298 emails sent - 10.07% reply rate - 40% positive replies - 12 opportunities worth $12,000 Campaign 2 (Mar 9-13): - 2,352 emails sent - 2.59% reply rate - 31.15% positive replies - 19 opportunities worth $19,000 Same inbox. Same market. Different system. The difference? AI does the research I used to spend 20 hours per week doing. Here's what the system does automatically: → Scrapes prospect websites (every page, not just homepage) → Analyzes their business model, services, recent activity → Identifies specific gaps (SEO issues, broken links, slow site speed) → Writes personalized emails based on what it found → Sends follow-ups intelligently → Logs everything to CRM It doesn't pitch randomly. It diagnoses problems, then shows how to solve them. Last week, one prospect replied: "Your email won because you actually studied our site. If this works, I'll hire your team permanently." That's the power of relevance over volume. The system works while I'm doing other things. Research. Writing. Sending. Following up. Booking calls. All automated. If your cold email feels dead, it's not the channel. It's the way you're doing it. No more "Hey there..." openers. No more generic "we help" templates. Just real context. Real personalization. Real replies. Here's the exact AI workflow I'm using to book 19+ calls per week. P.S. This isn't a tool. It's a weapon. Use it responsibly.

Looking for someone experienced with web scraping, data enrichment and AI automation (preferably n8n). Project overview: Building a prospect intelligence workflow for B2B outreach. The automation should: * Start by building a top-of-funnel list of UK companies (£1M+ revenue is a MUST). * From that list, scrape public website content (homepage, FAQ, support/help, returns, etc.). * Using that data, identify predefined behavioural signals (e.g. complex products, product confusion, subscription models, large FAQs, slow support evidence, returns friction). * Based on those signals, analyse public reviews for recurring customer themes. * From the refined set, find key decision-makers (Founder, CEO, Head of CX, Customer Support, Operations, etc.). * Finally, export everything into a clean CSV for outreach. The focus is on **publicly available information only**. No scraping behind logins or private data. Please send: * Relevant experience. * Examples of similar scraping/enrichment projects. * Preferred stack (n8n, Apify, Firecrawl, Claude/OpenAI, etc.). * Estimated timeline and cost. And most importantly THAT YOU UNDERSTAND WHAT I AM LOOKING FOR RATHER THAN SENDING ME A PDF WITH IRRELEVANT AUTOMATION. This is likely to become an ongoing rather than a one-off build.

One thing I've realised after 6 months in this space. The people making money stay quiet about how they do it. The people making zero dollars will tell you how to make money. That's where things get weird. Most of group 2 loves sharing how you should make money. Most of them fall into one of these buckets. - The person who makes things up about how to make money. - The person who repeats advice from other people. - The person trying to be helpful but not making any money. So what do all three have in common? In every case, the person giving advice isn't making money. But they give it anyway. That's the problem. When you're new, you want advice. You ask for help. But if the advice isn't based on real experience, listen to Alex Hormozi instead. You'll get better advice on how to make money. But what about when you start making money? I'm on that side now. Clients pay me. And I understand why you don't want to share how you make money without charging for it. Have you received advice on how to make money in the AI space and failed?

I'm 21 and started my own AI automation agency 2 months ago. My first client came through my network, and the next ones came from posting LinkedIn videos about what I was building. But I wanted something that scales without waiting for inbound. So I built a cold email automation pipeline from scratch. It handles the full flow: - Lead discovery using web scraping (Firecrawl + Google Maps data) - Email verification before any email goes out - AI-powered research per lead: website scrape, competitor analysis, needs analysis - Personalized 3-email sequences generated by AI with A/B testing on - subject lines, approaches and styles - Automated follow-up timing (day 1, day 3, day 7) - Reply detection via IMAP with AI classification into 6 categories - Human approval dashboard so nothing sends without review - Lead recycling for non-responders after 60 days The key insight: cold email is not about volume. It is about deep research per lead so the AI has enough context to write emails that actually feel personal. Every lead goes through a 7-step research process before a single word gets written. I put together a complete guide of 26 pages (PDF attached) that covers the full architecture, the actual AI prompts I use, SMTP setup, warmup strategy, deliverability tips, and the 10 mistakes I made building this. Hope it helps someone here!