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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.

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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.

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How It Works

Trigger: Form submission from website or landing page Workflow:
  1. HTTP Request: Enrich lead data from external APIs (company info, LinkedIn data)
  2. Agent: Score lead quality based on multiple factors
  3. 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
  4. Action: Create/update CRM record with score
  5. Send Notification: Alert assigned sales rep for hot leads

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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}})

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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

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Sales Follow-Up Automation

Automatically send personalized follow-up emails to prospects based on their engagement and timeline.

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How It Works

Trigger: Scheduled daily at 9 AM Workflow:
  1. HTTP Request: Fetch prospects needing follow-up from CRM
  2. 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)
  3. Send Notification: Summary of follow-ups sent

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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.

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Benefits

  • No prospect falls through the cracks
  • Personalized at scale (not generic templates)
  • Consistent follow-up timing
  • Sales reps focus on conversations, not admin

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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