Step 2: Send an Intake Acknowledgment and Map Lead Attributes

Return a quick response to the requester and normalize lead fields for downstream processing.

1. Open Send Intake Acknowledgment and set Respond With to json.
2. Set Response Body to ={{ { "success": true, "message": "Lead received and processing", "leadId": $json.leadId } }}.
3. Open Map Lead Attributes and add the following assignments:
4. Set leadId to ={{ $now.format('yyyyMMddHHmmss') }}-{{ $json.email.split('@')[0] }}.
5. Set timestamp to ={{ $now.toISO() }}.
6. Set source to ={{ $json.source || 'website' }}.

Step 3: Set Up the AI Lead Scoring Chain

Configure the AI scoring chain that analyzes lead content, parses the result, and generates a structured score.

1. Open AI Lead Scoring and set Text to =Analyze this lead and provide a qualification score: Name: {{ $json.name }} Email: {{ $json.email }} Company: {{ $json.company }} Message: {{ $json.message }} Budget: {{ $json.budget }} Timeline: {{ $json.timeline }}.
2. Ensure Prompt Type is define and Has Output Parser is enabled.
3. Open Extract AI Score and set Schema Type to manual.
4. Set Input Schema to the provided JSON schema for score, category, reasoning, recommended_action, key_strengths, and concerns.
5. Open OpenAI Chat Model and keep the model selection (e.g., gpt-4o-mini) or change to your preferred model.
6. Credential Required: Connect your openAiApi credentials in OpenAI Chat Model.
7. Note: Extract AI Score is an AI sub-node; credentials must be added to the parent language model, OpenAI Chat Model.

Step 4: Configure Lead Quality Routing

Route leads into hot or nurture paths based on the AI score.

1. Open Evaluate Lead Quality and set the first condition to compare Left Value ={{ $json.output.score }} with Right Value 70 using Operator larger.
2. Review the second condition row, which currently has empty Left Value and Right Value, and remove or complete it based on your own rules.

Step 5: Configure Airtable and Notification Outputs

Store qualified and nurture leads in Airtable and notify your team and prospects via Slack and email.

1. Open Append Hot Leads Airtable and set Operation to append, Base to YOUR_AIRTABLE_BASE_ID, and Table to YOUR_AIRTABLE_TABLE_ID.
2. Open Append Nurture Airtable and set Operation to append, Base to YOUR_AIRTABLE_BASE_ID, and Table to YOUR_AIRTABLE_TABLE_ID.
3. Credential Required: Connect your Airtable credentials in both Append Hot Leads Airtable and Append Nurture Airtable.
4. Open Slack Team Alert and keep Operation set to send.
5. Credential Required: Connect your Slack credentials in Slack Team Alert.
6. Open Dispatch Hot Lead Email and set Subject to Thank you for your inquiry - We'll be in touch soon!, To Email to ={{ $('Incoming Lead Webhook').item.json.email }}, and From Email to [YOUR_EMAIL].
7. Open Dispatch Nurture Email and set Subject to Thank you for contacting us, To Email to ={{ $('Incoming Lead Webhook').item.json.email }}, and From Email to [YOUR_EMAIL].
8. Credential Required: Connect your SMTP/Email credentials in both Dispatch Hot Lead Email and Dispatch Nurture Email.
9. Confirm the parallel branch: Append Hot Leads Airtable outputs to both Slack Team Alert and Dispatch Hot Lead Email in parallel.

Step 6: Test and Activate Your Workflow

Validate the end-to-end flow and move the workflow into production.

1. Click Test Workflow and send a sample POST request to the Incoming Lead Webhook URL with lead fields like name, email, company, message, budget, and timeline.
2. Confirm that Send Intake Acknowledgment returns the JSON response containing success, message, and leadId.
3. Verify that AI Lead Scoring produces output parsed by Extract AI Score, and that Evaluate Lead Quality routes to the correct Airtable node.
4. Check Airtable records, Slack notifications, and the outbound email in the correct branch to confirm success.
5. Once validated, toggle the workflow to Active to enable production processing.