n8n 12-Line Lead Qualifier: Full Breakdown (2026)

An r/n8n post with 95 upvotes: "Built a lead qualifier in n8n. The scoring prompt is 12 lines and that's the whole product." The post demonstrates that lead qualification does not need a complex ML pipeline — a search enrichment step plus a structured LLM prompt handles 80% of the use case.

The 4-node architecture

Node 1: Webhook trigger (new CRM contact). Node 2: Scavio HTTP Request (search company name for context). Node 3: LLM node (score the lead 1-10 using SERP context). Node 4: IF node (route hot/warm/cold to different CRM pipelines). That is the entire workflow.

The 12-line scoring prompt

You are a B2B lead scorer. Given a company name and search results about them,
score the lead 1-10 on fit for [YOUR ICP DESCRIPTION].

Scoring criteria:
- Hiring for roles that use our product category: +3
- Recent funding or growth news: +2
- Tech stack overlap with our product: +2
- Company size 50-500 employees: +1
- Active in relevant communities: +1
- No signals found: base score 3

Return JSON only: {"score": N, "reason": "one sentence"}

Company: {{company_name}}
Search results: {{search_snippets}}

The search enrichment step

{
  "method": "POST",
  "url": "https://api.scavio.dev/api/v1/search",
  "headers": { "x-api-key": "{{ $env.SCAVIO_API_KEY }}" },
  "body": { "query": "{{ $json.company_name }}", "platform": "google", "limit": 3 }
}

Three search results provide enough context for the LLM to detect hiring signals, funding news, and tech stack. More results add noise without improving accuracy.

Why this beats traditional lead scoring

• No training data required: the LLM generalizes from the prompt
• ICP changes are a prompt edit, not a model retrain
• Search enrichment catches signals that static CRM data misses
• Cost: $0.005 (search) + ~$0.002 (LLM) = $0.007/lead
• Setup time: 15 minutes in n8n

Limitations

• LLM scoring is probabilistic — expect ~10-15% disagreement with human scoring
• Small or stealth companies have thin SERP presence, reducing signal quality
• The prompt needs tuning for your specific ICP; the 12 lines are a starting point