AI Lead Qualifier & Enrichment

1. Create a new workflow in n8n triggered by a HubSpot "New Contact" webhook. Configure the HubSpot trigger to fire whenever a new contact is created. 2. Add an HTTP Request node to fetch additional company data from HubSpot's Company API using the contact's associated company ID. 3. Add an HTTP Request node to call the Claude API (POST https://api.anthropic.com/v1/messages). Set the headers: x-api-key to your Anthropic API key, anthropic-version to 2023-06-01, and content-type to application/json. 4. In the Claude API request body, set the model to "claude-sonnet-4-20250514" and max_tokens to 1024. Craft a prompt that passes the lead's name, email domain, job title, and company info, asking Claude to return a JSON object with a fit_score (0-100), reasoning, and enrichment fields (industry, company_size_estimate, key_talking_points). 5. Add a Function node to parse Claude's JSON response. Extract the fit_score and enrichment data. Route high-scoring leads (score >= 70) to the enrichment path and low-scoring leads to the nurture path using an IF node. 6. On the high-score path, add a HubSpot node to update the contact record with the enrichment fields and lead score. Follow it with a Slack node that posts a summary to your #sales channel. 7. On the low-score path, add a HubSpot node to tag the contact for nurture sequences. 8. Test with a sample contact. Verify Claude's response parses correctly, the CRM record is enriched, and the Slack notification fires. Adjust the prompt if the scoring is too generous or too strict.