Documentation Index Fetch the complete documentation index at: https://docs.langdock.com/llms.txt
Use this file to discover all available pages before exploring further.
Lead Qualification & Scoring
Automatically score and qualify incoming leads based on company data, role, and use case to focus sales efforts on high-potential prospects.
How It Works
Trigger : Form submission from website or landing page
Workflow:
HTTP Request : Enrich lead data from external APIs (company info, LinkedIn data)
Agent : Score lead quality based on multiple factors
Condition : Route based on lead score
Hot leads (80-100) → Notify sales rep immediately
Warm leads (50-79) → Add to nurture campaign
Cold leads (0-49) → Archive for later
Action : Create/update CRM record with score
Send Notification : Alert assigned sales rep for hot leads
Configuration Example
HTTP Request Node (Enrich Data):
Method: POST
URL: https://api.clearbit.com/v2/combined/find
Headers:
- Authorization: Bearer YOUR_CLEARBIT_TOKEN
Body:
{
"email": "{{trigger.output.email}}"
}
Agent Node (Score Lead):
Model: GPT-4
Instructions: Score this lead from 0-100 based on:
**Company Info:**
- Size: {{http_request.output.company.employees}} employees
- Industry: {{http_request.output.company.industry}}
- Revenue: {{http_request.output.company.estimated_revenue}}
**Lead Info:**
- Role: {{trigger.output.role}}
- Seniority: {{http_request.output.person.seniority}}
- Use Case: {{trigger.output.use_case}}
**Scoring Criteria:**
- Enterprise companies (1000+ employees): +30 points
- Director level or above: +20 points
- Strategic use case: +25 points
- Tech/SaaS industry: +15 points
- Clear pain point mentioned: +10 points
Structured Output:
{
"score": "number (0-100)",
"qualification": "hot|warm|cold",
"reasoning": "string",
"recommended_action": "string"
}
Condition Node:
If Hot Lead: {{ agent.output.structured.score >= 80 }}
Else if Warm Lead: {{ agent.output.structured.score >= 50 && agent.output.structured.score < 80 }}
Else if Cold Lead: {{ agent.output.structured.score < 50 }}
Send Notification (Hot Leads):
🔥 **Hot Lead Alert - Score: {{ agent.output.structured.score }} /100**
**Contact:**
{{ trigger.output.name }} - {{ trigger.output.role }}
{{ trigger.output.company }}
{{ trigger.output.email }}
**Company Details:**
- Size: {{ http_request.output.company.employees }} employees
- Industry: {{ http_request.output.company.industry }}
**Use Case:**
{{ trigger.output.use_case }}
**AI Assessment:**
{{ agent.output.structured.reasoning }}
**Recommended Action:**
{{ agent.output.structured.recommended_action }}
**CRM Link:** [View in CRM]( {{ action.crm_url }} )
Benefits
Sales team focuses only on qualified leads
Response time under 5 minutes for hot leads
Objective, data-driven scoring
60% increase in conversion rates
Sales Follow-Up Automation
Automatically send personalized follow-up emails to prospects based on their engagement and timeline.
How It Works
Trigger : Scheduled daily at 9 AM
Workflow:
HTTP Request : Fetch prospects needing follow-up from CRM
Loop : For each prospect
Agent : Generate personalized follow-up email based on history
Action : Send email via Gmail or Outlook
Action : Update CRM with activity
Delay : 5 seconds (rate limiting)
Send Notification : Summary of follow-ups sent
Configuration Example
HTTP Request Node:
Method: GET
URL: https://api.yourcrm.com/prospects
Query Parameters:
- status: follow_up_needed
- last_contact_before: {{code.three_days_ago}}
Headers:
- Authorization: Bearer YOUR_CRM_TOKEN
Code Node (Calculate dates):
const now = new Date ();
const threeDaysAgo = new Date ( now );
threeDaysAgo . setDate ( threeDaysAgo . getDate () - 3 );
return {
three_days_ago: threeDaysAgo . toISOString (),
today: now . toISOString ()
};
Loop Node:
Input Array: {{http_request.output.prospects}}
Loop Variable: prospect
Max Iterations: 100
Agent Node (Inside Loop):
Model: GPT-4
Instructions: Write a personalized follow-up email to {{prospect.name}} at {{prospect.company}}.
**Context:**
- Last contact: {{prospect.last_contact_date}}
- Last topic: {{prospect.last_discussion}}
- Their role: {{prospect.role}}
- Pain points: {{prospect.pain_points}}
Write a friendly, brief email (2-3 paragraphs) that:
1. References our last conversation about {{prospect.last_discussion}}
2. Provides value or insight related to their {{prospect.pain_points}}
3. Suggests a specific next step (demo, call, resource)
Use a conversational, helpful tone. Subject line should be compelling.
Structured Output:
{
"subject": "string",
"body": "string"
}
Action Node (Send Email):
Integration: Gmail
Action: Send Email
To: {{prospect.email}}
Subject (Manual): {{agent.output.structured.subject}}
Body (Manual): {{agent.output.structured.body}}
Action Node (Update CRM):
Integration: Your CRM
Action: Update Contact
Contact ID: {{prospect.id}}
Fields:
- last_contact_date: {{code.today}}
- last_contact_type: email
- status: awaiting_response
Send Notification (After Loop):
✉️ **Follow-up Automation Complete**
Sent {{ loop.total }} personalized follow-up emails.
Check CRM for responses.
Benefits
No prospect falls through the cracks
Personalized at scale (not generic templates)
Consistent follow-up timing
Sales reps focus on conversations, not admin
Next Steps
Marketing Workflows Content and campaign automation
Finance Workflows Invoice and expense automation
Loop Node Learn about processing multiple items
Agent Node Generate personalized content with AI