Zoho CRM Integration Template

Integrate Zoho CRM into your Mid-call Actions and enable your AI assistant to automatically create qualified leads, categorize them, and initiate sales workflows during customer conversations.

Overview & Features

Intelligent Lead Creation

Automatic lead generation from conversations
BANT qualification and lead scoring
Industry-specific categorization
Multi-channel lead source tracking

Sales Process Automation

Automatic assignment rules and territory management
Lead nurturing workflow triggers
Sales team notifications
CRM analytics and performance tracking

Zoho CRM API Setup

1. Configure Zoho OAuth 2.0

Zoho API Console

Visit Zoho API Console
Create a “Server-based Application” client
Note the client ID and client secret

Configure OAuth Scopes

Required scopes:
  - ZohoCRM.modules.leads.CREATE
  - ZohoCRM.modules.leads.READ
  - ZohoCRM.modules.contacts.READ (for duplicate check)
  - ZohoCRM.users.READ (for assignment)

Generate Refresh Token

Initial authorization flow:
Visit the authorization URL  
Grant user consent  
Receive authorization code  
Exchange code for refresh token  
Use refresh token for API calls  

Configure Lead Creation Tool

Configuration in the Famulor Interface

Tool Details
Header Configuration
Request Body Template

Field	Value
Name*	`Zoho CRM Lead erstellen`
Description	”Automatically creates a new lead in Zoho CRM with complete conversation information”
Function Name*	`create_zoho_lead`
Function Description*	“Creates a lead in Zoho CRM. Use this when a potential customer shows interest or you identify new business opportunities.”
HTTP Method	`POST`
Timeout (ms)	`5000`
Endpoint*	`https://www.zohoapis.eu/crm/v2/Leads`

{
  "Authorization": "Zoho-oauthtoken {{ZOHO_TOKEN}}",
  "Content-Type": "application/json",
  "User-Agent": "Famulor-MidCall-Zoho/1.0"
}

{
  "data": [
    {
      "Company": "{company}",
      "Last_Name": "{last_name}",
      "First_Name": "{first_name}",
      "Email": "{email}",
      "Phone": "{phone}",
      "Lead_Source": "{lead_source}",
      "Lead_Status": "{lead_status}",
      "Description": "{description}",
      "Industry": "{industry}",
      "No_of_Employees": "{employees}",
      "Annual_Revenue": "{revenue}",
      "Street": "{street}",
      "City": "{city}",
      "Zip_Code": "{zip}",
      "Country": "{country}",
      "Rating": "{rating}",
      "Website": "{website}",
      "Lead_Score": "{lead_score}",
      "Budget": "{budget}",
      "Timeline": "{timeline}",
      "Pain_Points": "{pain_points}",
      "Competitor": "{competitor}",
      "Call_Source": "Famulor Mid-call Action"
    }
  ],
  "trigger": ["workflow"],
  "duplicate_check_fields": ["Email", "Phone"]
}

Parameter Schema

{
  "type": "object",
  "properties": {
    "company": {
      "type": "string",
      "description": "Company name of the lead"
    },
    "first_name": {
      "type": "string",
      "description": "First name of the contact person"
    },
    "last_name": {
      "type": "string",
      "description": "Last name of the contact person"
    },
    "email": {
      "type": "string",
      "format": "email",
      "description": "Email address"
    },
    "phone": {
      "type": "string",
      "description": "Phone number"
    },
    "lead_source": {
      "type": "string",
      "enum": ["Phone Call", "Website", "Trade Show", "Referral", "Advertisement"],
      "description": "Source of the lead",
      "default": "Phone Call"
    },
    "lead_status": {
      "type": "string",
      "enum": ["New", "Contacted", "Qualified", "Lost"],
      "description": "Current lead status",
      "default": "Contacted"
    },
    "description": {
      "type": "string",
      "description": "Detailed notes from the conversation"
    },
    "industry": {
      "type": "string",
      "description": "Industry of the company"
    },
    "employees": {
      "type": "string",
      "enum": ["1-10", "11-50", "51-200", "201-1000", "1000+"],
      "description": "Number of employees"
    },
    "revenue": {
      "type": "number",
      "description": "Annual revenue in Euros"
    },
    "rating": {
      "type": "string",
      "enum": ["Hot", "Warm", "Cold"],
      "description": "Lead rating based on conversation",
      "default": "Warm"
    },
    "lead_score": {
      "type": "integer",
      "description": "Calculated lead score (0-100)",
      "minimum": 0,
      "maximum": 100
    },
    "budget": {
      "type": "string",
      "description": "Available or stated budget"
    },
    "timeline": {
      "type": "string",
      "description": "Timeframe for purchase decision"
    },
    "pain_points": {
      "type": "string",
      "description": "Identified challenges and issues"
    },
    "competitor": {
      "type": "string",
      "description": "Mentioned competitors or alternative solutions"
    }
  },
  "required": ["last_name", "company"]
}

Practical Use Cases

Scenario 1: Lead Qualification During Cold Call

Lead Opportunity Detection

Cold Call Context:
  Prospect: "Yes, we are actually looking for a CRM solution..."
  
AI: "Great! Let me document this as a lead..."

create_zoho_lead:
  company: "Example AG"
  first_name: "Max"
  last_name: "Mustermann" 
  phone: "+49123456789"
  lead_source: "Phone Call"
  lead_status: "Contacted"
  description: "Looking for a CRM solution for 50 employees. Current system is too slow."
  employees: "51-200"
  rating: "Warm"
  pain_points: "Performance issues with current CRM"

BANT Qualification Integration

Automatic Lead Scoring Logic:
  
Budget Assessment:
  "Under 10k" → lead_score: 40
  "10-50k" → lead_score: 70
  "Over 50k" → lead_score: 90
  
Authority Level:
  "CEO/Managing Director" → +20 points
  "IT Manager" → +15 points  
  "Employee" → +5 points
  
Need Urgency:
  "Immediate" → rating: "Hot"
  "This year" → rating: "Warm"
  "Sometime" → rating: "Cold"

Response Handling

{
  "data": [
    {
      "code": "SUCCESS",
      "details": {
        "Modified_Time": "2024-01-15T10:30:00+01:00",
        "Modified_By": {
          "name": "Famulor Integration",
          "id": "123456789"
        },
        "Created_Time": "2024-01-15T10:30:00+01:00",
        "id": "987654321098765432",
        "Created_By": {
          "name": "Famulor Integration",
          "id": "123456789"
        }
      },
      "message": "record added",
      "status": "success"
    }
  ]
}

Natural Language Integration

Agent Message: "I am creating the lead for {{company}}..." Success Template: "Lead created for {{first_name}} {{last_name}} from {{company}}. Lead ID: {{leadId}}" Enhanced Customer Communication:

With follow-up information:
  "The lead has been created. Our sales team will contact you within 24 hours with further information."

With lead score context:
  "Based on our conversation, you have a high lead score. You will be prioritized by our senior account manager."

Related pages: Introduction and Building Flows, and Debugging Runs.

Need a whole toolset instead of building HTTP actions one by one? Connect an external MCP server — tools are discovered automatically. See MCP Servers.

Mid-Call Tools

Mid-Call Tool Integrations

Zoho CRM Integration

Zoho CRM Integration Template

Overview & Features

Intelligent Lead Creation

Sales Process Automation

Zoho CRM API Setup

1. Configure Zoho OAuth 2.0

Configure Lead Creation Tool

Configuration in the Famulor Interface

Parameter Schema

Practical Use Cases

Scenario 1: Lead Qualification During Cold Call

Response Handling

Natural Language Integration

​Zoho CRM Integration Template

​Overview & Features

Intelligent Lead Creation

Sales Process Automation

​Zoho CRM API Setup

​1. Configure Zoho OAuth 2.0

​Configure Lead Creation Tool

​Configuration in the Famulor Interface

​Parameter Schema

​Practical Use Cases

​Scenario 1: Lead Qualification During Cold Call

​Response Handling

​Natural Language Integration

Zoho CRM Integration Template

Overview & Features

Zoho CRM API Setup

1. Configure Zoho OAuth 2.0

Configure Lead Creation Tool

Configuration in the Famulor Interface

Parameter Schema

Practical Use Cases

Scenario 1: Lead Qualification During Cold Call

Response Handling

Natural Language Integration