Step 2: Connect Google Sheets

Pull raw lead replies from your sheet and normalize them into a consistent payload.

1. Open Fetch Sheet Replies and set Sheet Name to GHL-Replies.
2. Set Document ID to YOUR_GOOGLE_SHEET_ID_HERE.
3. Credential Required: Connect your Google Sheets OAuth2 credentials (not configured yet).
4. Open Normalize Lead Payload and map fields using expressions:
   • leadId → {{ $json.id || $('Fetch Sheet Replies').item.json.leadId }}
   • leadName → {{ $json.name || $('Fetch Sheet Replies').item.json.name }}
   • replyMessage → {{ $json.lastMessage || $('Fetch Sheet Replies').item.json.reply }}
   • email → {{ $json.email || $('Fetch Sheet Replies').item.json.email }}
   • company → {{ $json.company }}

Step 3: Set Up AI Intent Classification

Classify each lead reply into an intent category using the AI agent and structured parsing.

1. Open Classify Lead Intent and keep the Text prompt as configured, including the dynamic fields like {{ $json.leadId }} and {{ $json.replyMessage }}.
2. Open Azure GPT Chat Engine and set Model to gpt-4o.
3. Credential Required: Connect your Azure OpenAI API credentials in Azure GPT Chat Engine.
4. Confirm Session Memory Buffer is connected to Classify Lead Intent with Session Key set to "lead_intent_classifier" and Context Window Length set to 7.
5. Confirm Structured Result Parser is connected to Classify Lead Intent and uses the provided JSON schema example.
6. Open Parse Intent Output and set:
   • intent → {{ $json.output.intent }}
   • originalData → {{ $('Normalize Lead Payload').item.json }}

Step 4: Configure Intent Routing and Follow-up Payloads

Route each classified reply to the correct follow-up branch and populate task details.

1. Open Route by Intent and verify the rules match:
   • {{ $json.intent }} equals DEMO_REQUEST
   • {{ $json.intent }} equals PRICING_INQUIRY
   • {{ $json.intent }} equals OBJECTION
   • {{ $json.intent }} equals NOT_INTERESTED
2. Configure the follow-up Set nodes (grouped by function):
   • Set Demo Follow-up: dueDate → {{ $now.plus(2, 'days').toFormat('yyyy-MM-dd') }}, taskDescription → Contact {{ $json.originalData.leadName }} to schedule product demo
   • Set Pricing Follow-up and Set Objection Follow-up: dueDate → {{ $now.plus(1, 'days').toFormat('yyyy-MM-dd') }}
   • Set General Follow-up: dueDate → {{ $now.plus(3, 'days').toFormat('yyyy-MM-dd') }}

Step 5: Configure ClickUp Task Creation and Checklists

Create ClickUp tasks for each follow-up and append a standardized checklist item.

1. Open Create ClickUp Task and set IDs for List, Team, Space, and Folder to your ClickUp IDs (replace [YOUR_ID]).
2. Set Name to {{ $json.nextStep }} - {{ $json.leadName }} and Due Date to {{ $json.dueDate }}.
3. Credential Required: Connect your ClickUp credentials in Create ClickUp Task (not configured yet).
4. Open Create Checklist and set:
   • URL → https://api.clickup.com/api/v2/task/{{$json.id}}/checklist
   • JSON Body → { "name": "{{ $json.name }}" }
5. Open Append Checklist Item and set:
   • URL → https://api.clickup.com/api/v2/checklist/{{ $json.checklist.id }}/checklist_item
   • JSON Body → { "name": "Follow-up" }
6. Credential Required: Connect your ClickUp API credentials in both Create Checklist and Append Checklist Item (not configured yet).

Step 6: Test and Activate Your Workflow

Run a manual test to confirm intent classification, routing, and task creation all work as expected.

1. Click Execute Workflow to run Scheduled Run Trigger manually and pull a sample row from Fetch Sheet Replies.
2. Verify Classify Lead Intent produces structured JSON that matches the schema in Structured Result Parser.
3. Confirm the correct branch fires in Route by Intent and a task is created in ClickUp with the right Name, Due Date, and checklist item.
4. When successful, toggle the workflow to Active so Scheduled Run Trigger runs every 15 minutes in production.