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Qualify Website Leads with OpenAI, HubSpot and Gmail

Curated n8n workflow that uses OpenAI to assess inbound leads, create or reuse HubSpot records and notify a team through Gmail.

Works with Gmail, HubSpot, OpenAI, Webhook

Illustration of AI Lead Qualification n8n workflow

Workflow overview

Curated external workflow. This template is listed on the official n8n workflow directory and credited to its original creator. TemplateFlows has reviewed the source listing, but has not independently imported, executed or security-tested the JSON. Use the original source link for access; no JSON is redistributed here.

What the template does

This externally authored n8n workflow accepts lead submissions, asks OpenAI for structured qualification details, checks HubSpot for an existing contact, and supports lead or deal handling and internal Gmail notifications. The source listing describes fields such as lead score, urgency and recommended follow-up.

Source review only: TemplateFlows has not independently assessed the AI model’s accuracy or tested CRM writes. Use the original n8n.io workflow and review every automated decision before production use.

Requirements

Prerequisites

  • n8n instance with an authorized webhook.
  • OpenAI API access and an understood usage budget.
  • HubSpot account with suitable contact/deal permissions.
  • Gmail credential for internal notifications.
  • A documented ideal-customer profile and review policy.

Required tools and services

  • n8n
  • Gmail

Setup steps

  1. Inspect AI scoring prompts

    Check which lead fields are shared with the model and whether the scoring criteria fit your business.

  2. Connect external services

    Set up OpenAI, HubSpot and Gmail credentials with least-privilege access.

  3. Map HubSpot fields

    Verify existing-contact lookup and avoid overwriting manual CRM decisions.

  4. Test qualification and errors

    Evaluate representative test leads, duplicates, invalid data and API failures; require human review for consequential actions.

Possible implementation problems

AI scoring can be inconsistent or biased. Treat scores as suggestions, not facts. Avoid sending sensitive data to a model without a valid basis and authorization. API usage may incur charges. Check CRM deduplication and idempotency.

Source and attribution

Creator
Mohamad Sasa
Original source
n8n.io
License
Check original author and n8n source terms before reuse or redistribution

Guides for this workflow

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