I'm at a critical decision point and would love feedback from anyone who's built lead qualification systems before. CONTEXT: I'm building an AI automation system for med spa lead generation. Before I start selling anything, I want to validate my assumptions by doing ICP (Ideal Customer Profile) discovery calls with 5-7 med spa owners. But here's the thing: I don't want to waste time calling the wrong businesses. So I'm building a multi-layer qualification workflow to identify which med spas are worth talking to for ICP research. THE WORKFLOW I'M PLANNING: Layer 1: Google Maps Data Scraping • Scrape 200-500 med spas from Austin (using Google Maps API) • Collect: Business name, website, review count, rating, primary category, phone • Use GPT to score leads 0-100 based on these signals • Goal: Identify businesses that are "serious but inconsistent" (my target ICP) Layer 2: Website Analysis • For businesses with websites: Scrape content using Firecrawl • Use GPT to score website quality, service clarity, and alignment with GBP • Combine Google Maps score + Website score → Final ICP tier (A / B+ / B / C) • Goal: Understand which businesses need help vs. already optimized Layer 3: Email Extraction & Outreach • Use Hunter.io to find business owner emails • Send non-sales outreach via Instantly.ai (just asking for 15-min research call) • Track opens, clicks, replies • Goal: Book 5-7 ICP discovery calls (not selling, just learning) Layer 4: AI Voice Follow-Up • If no email response after 5 days: Vapi AI calls them • Script: "I'm doing market research on med spa marketing, would you have 15 minutes to chat?" • Goal: Increase response rate with multi-touch approach Layer 5: ICP Discovery Calls • Conduct 5-7 manual calls with qualified leads • Ask: What's your biggest challenge? What are you spending on marketing? What would you pay to solve X? • Goal: Validate assumptions, understand real pain points, build offer based on

Open any AI tool. It doesn't matter which one! Type this prompt: “Ask me one question at a time to understand what I do, and when you have enough information, clearly explain how you can help me.”

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The biggest difference between emails that get ignored and emails that get replies isn’t the subject line… it’s research + relevance. I just put together a system using n8n that: - Research prospects automatically - Pulls real, meaningful context - Turns that research into truly personalized cold emails Not templates.Not generic “we help companies like yours” nonsense. When your email proves you actually understand the person you’re reaching out to, replies stop being random, they become predictable. Most people don’t need better copy. They need better inputs. And automation done right makes that easy.