Auto-qualify and route dental leads with GPT-4 into GoHighLevel

Unify website forms, Twilio SMS, and Meta Lead Ads leads; AI-score, classify, sync to CRM, send follow-ups, and generate weekly reports

Who

Small clinics or agencies automating local service (dental/aesthetic) lead follow-up

You get

Automated lead scoring and classification, instant high-priority response, scheduled re-engagement, weekly performance reports

You need

n8n · twilio · meta-ads · pinecone · gohighlevel · slack · google-calendar · postgres

Steps

1. Configure lead sources

   Set up three triggers in n8n: copy the Webhook node URL into your form or landing page; connect the Twilio trigger for SMS replies; connect the Meta Lead Ads trigger and select your Facebook Page and lead form. All sources feed into the Merge Leads from All Sources node.

2. Connect credentials and set defaults

   In the Set Workflow Defaults node, enter your practice name, GoHighLevel API base/token/Location ID, Twilio from-number, Slack channel, Google Calendar ID, Pinecone index name, dashboard email, high-priority score threshold (default 70), and unresponsive follow-up days (default 3). Add real credentials in n8n's credential manager for OpenAI, Twilio, SMTP, Slack, Google Calendar, Postgres, Facebook, and Pinecone.

3. AI lead scoring and classification

   The Prepare Lead Data node normalizes all three intake shapes into a common record. The Lead Qualifier Agent uses a GPT-4 model with the Calculate Lead Score tool (deterministic scoring), Check Calendar Openings tool, Sync with GoHighLevel tool, and Access Knowledge Base (Pinecone RAG) tool to output a structured result: treatment category, 0-100 score, summary, and recommended next step.

   Execution prompt · Source text。Lead Qualifier Agent node text field (user prompt)

   Copy prompt

   =A new lead has come in for {{ $json.practice_name }}. Qualify this lead and recommend the right treatment pathway.
   
   Lead source: {{ $json.source }}
   Name: {{ $json.lead_name }}
   Phone: {{ $json.lead_phone }}
   Email: {{ $json.lead_email }}
   Stated interest: {{ $json.treatment_interest }}
   Message/notes: {{ $json.lead_message }}

   Execution prompt · Source text。Lead Qualifier Agent node options.systemMessage field (system prompt)

   Copy prompt

   You are a lead qualification assistant for a local dental/aesthetic practice. Your job is to read an inbound lead's details and:
   
   1. Classify the lead into exactly one treatment category: Implants, All-on-X, Cosmetic, Orthodontics, or General (use General if nothing else clearly fits).
   2. Score the lead 0-100 on likelihood to book a consultation, based on urgency signals, budget signals, and clarity of interest in the message. Use the Calculate Lead Score tool to compute this score consistently rather than guessing.
   3. Check calendar availability with the Check Calendar Openings tool if the lead expresses interest in booking.
   4. Look up any existing contact history in GoHighLevel with the Sync with GoHighLevel tool before treating this as a brand-new lead.
   5. Use the Access Knowledge Base tool to answer any specific treatment questions the lead raised, grounding your summary in real practice information rather than guessing.
   
   Always return your final answer in the structured format required. Be concise and factual — do not make medical claims or promises about outcomes, pricing, or timelines beyond what the knowledge base confirms.

4. Route by treatment and enrich from GHL

   Route by Lead Treatment branches on the AI's treatment_category output into Implants, All-on-X, Cosmetic, Orthodontics, General, or fallback. Then HTTP requests look up the GHL contact by phone, fetch pipeline stage, and read custom fields to provide full customer context for downstream actions.

5. Trigger follow-up actions

   Every lead receives an acknowledgement SMS via Twilio; leads with email receive an SMTP confirmation. Check Lead Priority compares lead_score against HIGH_PRIORITY_SCORE_THRESHOLD. High-priority leads trigger: a Twilio voice call (currently static TwiML, replaceable with AI voice), a Slack alert, and a provisional Google Calendar hold. Log to Database writes to Postgres; Reply to Facebook DMs responds to Meta-sourced leads.

   Execution prompt · Source text。Post Alert to Slack node text field

   Copy prompt

   =🔥 High-priority lead: {{ $('Prepare Lead Data').first().json.lead_name }} ({{ $('Prepare Lead Data').first().json.lead_phone }}) — {{ $('Lead Qualifier Agent').first().json.output?.treatment_category }}, score {{ $('Lead Qualifier Agent').first().json.output?.lead_score }}/100. {{ $('Lead Qualifier Agent').first().json.output?.summary }}

6. Scheduled re-engagement of unresponsive leads

   A Schedule Trigger runs every 6 hours to fetch GHL contacts tagged new-lead-no-response older than FOLLOW_UP_DAYS_UNRESPONSIVE. The Follow-Up Agent uses GPT-4 to decide the re-engagement type: Re-engage (direct SMS/call), Nurture (gentle email), Voice Call (high-value callback), or Default. Parse Follow-Up Results structures the output; Route by Follow-Up Type dispatches to the corresponding action.

   Execution prompt · Source text。Follow-Up Agent node text field (user prompt)

   Copy prompt

   =This lead has not responded since initial contact. Decide the best follow-up action.
   
   Contact: {{ $json.contact?.firstName || $json.firstName }} {{ $json.contact?.lastName || $json.lastName }}
   Phone: {{ $json.contact?.phone || $json.phone }}
   Days since last contact: {{ $json.daysSinceLastContact || 'unknown' }}
   Previous treatment interest: {{ $json.customField?.treatment_interest || 'unknown' }}

   Execution prompt · Source text。Follow-Up Agent node options.systemMessage field (system prompt)

   Copy prompt

   You are a follow-up strategist for a local dental/aesthetic practice. For each unresponsive lead, decide exactly one follow-up type:
   
   - Re-engage: the lead showed real interest but went quiet — worth a direct, personalized SMS/call attempt
   - Nurture: the lead is early-stage or low-urgency — worth a gentle informational email instead of a hard sell
   - Voice Call: the lead is high-value or previously expressed urgency — worth a live callback attempt
   - Default: use this only if none of the above clearly fits
   
   Base your decision on how much time has passed, the treatment interest, and any conversation history in memory. Do not fabricate details not present in the record.

7. Generate and send weekly report

   On a weekly schedule, fetch the last 7 days of lead records from Postgres. Aggregate Metrics for Dashboard computes totals, high-priority counts, average score, and category breakdown. Build Dashboard Report formats the results, then Post Report to GHL Dashboard writes it as a GHL note and Email Report to Team sends it via SMTP.

You are an n8n workflow setup assistant. The user wants to replicate a dental/local-service lead qualification and routing system. First confirm they have ready: an n8n instance, OpenAI API key, GoHighLevel API token, and credentials for Twilio/SMTP/Slack/Google Calendar/Postgres/Pinecone/Meta Ads. Then guide them to import the template, replace all YOUR_* placeholders, build two sub-workflows (calendar lookup, GHL contact sync), and test a single lead end-to-end. Do not perform any API calls that may incur charges on the user's behalf.