Voice AI Lead Qualification System - Better Than Human SDRs (Full Tutorial)

Video Description

I built a voice AI that qualifies leads automatically, calculates a score 1-10, and routes them to hot/warm/cold paths. This is the most complex voice AI project I've built yet. 🎯 What This System Does: Calls leads from Google Sheets automatically Asks qualifying questions (budget, timeline, authority, pain) Calculates qualification score using N8N Routes to appropriate path based on score Books meetings for hot leads Schedules follow-ups for warm leads Adds cold leads to newsletter Updates Google Sheets with all data Sends automated emails 💰 Business Impact: Traditional SDR: Salary: $40,000-60,000/year Calls/day: 50-80 Consistency: Variable Sick days: 10-15/year Training time: 2-3 months Voice AI SDR: Cost: $100-300/month Calls/day: 480 (20 concurrent) Consistency: Perfect Sick days: 0 Training time: Setup once 98% cost reduction. 🧮 Dynamic Scoring System: After collecting all qualification data, AI calls N8N function: Input: Budget range (user's answer) Timeline (immediate vs 6 months) Authority level (decision maker vs researcher) Pain level (urgency of need) N8N Processing: AI agent analyzes inputs Scores on 10-point scale Returns: score, category, next action, priority Output back to Retell: Qualification score: 8 Lead category: Hot Next action: Book meeting Priority: High Routing: Score 7.5+ → Hot lead path → "Do you have 30 min now?" Score 5-7.4 → Warm lead path → "I'll follow up in 2 weeks" Score 5 → Cold lead path → "Want our newsletter?" ⚙️ Technical Setup: Retell AI Configuration: Agent type: Conversation Flow Model: GPT-4o-mini ($0.08/min) Voice: Customizable Global prompt: Identity + context Dynamic variables: Name, company, source Test cases: Hot/warm/cold scenarios N8N Workflows: Main caller - Reads Google Sheets, calls leads, waits between calls Score calculator - Receives data, scores lead, returns result Post-call processor - Webhook receives call data, updates sheets MCP server - Handles Google Sheets/Gmail/Calendar actions Google Sheets Structure: Lead ID (formula-generated) Full name, phone, email Lead source (form, ads, LinkedIn) Company, industry Status (pending/contacted/qualified) Qualification score (AI-filled) Budget range (AI-filled) Timeline (AI-filled) Authority level (AI-filled) Next action (AI-filled) Last called timestamp Call recording URL Transcript 🔧 Building Tips: 1. Flowchart First Don't start in Retell. Map the entire conversation in a tool like Miro, Figma, or even paper. 2. Script Sample Responses Give AI example phrases, not just prompts. "Tell them something like: [script]" 3. Extract Variables Immediately When user mentions budget, extract it that second. Don't wait. 4. Use Equation Transitions Route based on variables, not just user responses. If score ≥7.5, go here. 5. Function Call Handling Check "speak during execution" Set timeout to 20,000ms+ Give AI something to say while waiting 6. Test Each Path Use test cases for hot/warm/cold leads. Run 10+ times per path. 7. Global Nodes for Edge Cases User can get angry or lose interest anywhere. Handle it globally. 8. MCP for Actions Don't hardcode API calls. Use MCP for flexibility. ⚠️ Common Issues Fixed: Issue: AI says "$5K" as "dollar five K" Fix: Write out "5,000 dollars" fully Issue: Long silence during score calculation Fix: Enable "speak during execution" + add prompt "Hold on while I note this" Issue: Wrong email captured Fix: Extract variable + confirm back to user + update via MCP Issue: Can't transfer based on score Fix: Use equation transition, not prompt transition Issue: Function timeout errors Fix: Increase timeout in function settings to 20,000ms 🕐 Timestamps: 00:00 Live Demo - Full Lead Qualification Call 02:30 Google Sheets Setup & Lead Database 03:30 Conversation Flow Chart Overview 06:30 Why Conversation Flow is better than Single Prompt 08:00 Retell AI Interface Walkthrough 11:00 Node Types Explained (15+ node types) 13:00 Google Sheets Structure 14:00 N8N Workflow Overview 15:00 Dynamic Scoring System Deep Dive 16:30 Conversation Flow Build (Step by Step) 24:00 Score-Based Routing Setup 26:00 MCP Integration 27:00 Testing & Best Practices 29:00 Cost Analysis vs Call Centers 💡 Key Learnings: Flowchart before building (saves hours) Conversation Flow for complex agents Extract variables at every stage Function calls enable dynamic logic MCP adds powerful integrations Test cases prevent surprises 20 concurrent calls = 480/day possible 💰 Cost Breakdown: GPT-4o-mini: $0.08/minute Average call: 3-4 minutes Cost per lead: $0.24-0.32 1,000 leads: $240-320 Traditional SDR for same work: $2,000-5,000 85-95% savings. 📚 Resources: Comment "LEAD" for complete template Retell AI: retellai.com N8N: n8n.io Perfect For: B2B SaaS companies with inbound leads Agencies qualifying prospects Service businesses with inquiries Consultants with form submissions Anyone spending $2K+/month on SDRs