Webchat Deep Link APIs

The Webchat Deep Link API allows you to generate personalized webchat URLs with pre-populated user attributes. This enables seamless user experiences by creating direct links to conversations with context already established, perfect for personalized marketing campaigns, support tickets, or authenticated user flows.

Generate Webchat Deep Link

Create personalized webchat URLs for one or more users with pre-populated attributes.

Endpoint: POST /public/api/generate-webchat-deep-link

Headers:

Authorization: Bearer YOUR_API_TOKEN
Content-Type: application/json

Request Body:

{
  "scenario_id": "customer_support",
  "dataset": [
    {
      "user_id": "user_12345",
      "attributes": {
        "name": "John Doe",
        "email": "john.doe@example.com",
        "account_type": "premium",
        "support_tier": "gold"
      }
    },
    {
      "user_id": "user_67890",
      "attributes": {
        "name": "Jane Smith",
        "email": "jane.smith@example.com",
        "account_type": "standard",
        "support_tier": "silver"
      }
    }
  ]
}

Request Parameters:

• scenario_id (required, string) - The scenario ID for the webchat conversation
• dataset (required, array) - Array of user configurations (max limit configurable)
  • user_id (optional, string) - Unique identifier for the user. If not provided, a UUID will be generated automatically
  • attributes (required, object) - Key-value pairs of user attributes to pre-populate in the conversation context

Response:

[
  {
    "user_id": "user_12345",
    "url": "https://short.url/abc123"
  },
  {
    "user_id": "user_67890",
    "url": "https://short.url/def456"
  }
]

Response Fields:

• user_id (string) - The user identifier (provided or auto-generated)
• url (string) - The shortened deep link URL for this user

How It Works

When you generate a webchat deep link:

1. User Context Creation: The system creates a persistent user context with the provided user ID (or generates a new UUID)
2. Attribute Population: All provided attributes are added to the user’s context
   • Scalar attributes (strings, numbers) are stored directly
   • Collection attributes (arrays) are processed appropriately
   • Composite collection attributes are not currently supported
3. Deep Link Generation: A fullpage webchat URL is created with:
   • The specified scenario ID
   • The user ID
   • The appropriate app key/access token for the scenario
4. URL Shortening: The deep link is shortened to create a user-friendly URL
5. Persistent Context: When a user clicks the link, their context is loaded with all pre-populated attributes, enabling personalized conversations from the first message

Supported Attribute Types

Scalar Attributes

Simple key-value pairs stored as strings or numbers:

{
  "name": "John Doe",
  "email": "john.doe@example.com",
  "account_id": "12345",
  "vip_status": "true"
}

Collection Attributes (Arrays)

Attributes that accept multiple values:

{
  "interests": ["sports", "technology", "travel"],
  "preferred_languages": ["en", "es"],
  "product_ids": ["PROD-001", "PROD-002", "PROD-003"]
}

Arrays can also be provided as comma-separated strings:

{
  "interests": "sports,technology,travel"
}

Unsupported Types

• Composite collection attributes are currently not supported
• Complex nested objects beyond simple arrays

Use Cases

Personalized Marketing Campaigns

Generate unique links for email campaigns with customer context:

{
  "scenario_id": "sales_campaign",
  "dataset": [
    {
      "user_id": "customer_001",
      "attributes": {
        "name": "Alice Johnson",
        "email": "alice@example.com",
        "campaign_id": "SPRING2024",
        "discount_code": "SAVE20",
        "customer_segment": "high_value"
      }
    }
  ]
}

Support Ticket Integration

Create pre-contextualized support conversations:

{
  "scenario_id": "customer_support",
  "dataset": [
    {
      "user_id": "ticket_12345",
      "attributes": {
        "name": "Bob Williams",
        "email": "bob@example.com",
        "ticket_id": "TKT-12345",
        "issue_type": "billing",
        "priority": "high",
        "account_number": "ACC-98765"
      }
    }
  ]
}

Authenticated User Sessions

Seamlessly transition authenticated users to chat:

{
  "scenario_id": "member_portal",
  "dataset": [
    {
      "user_id": "auth_user_789",
      "attributes": {
        "name": "Carol Davis",
        "email": "carol@example.com",
        "member_id": "MEM-789",
        "subscription_tier": "platinum",
        "preferences": ["email_notifications", "sms_alerts"]
      }
    }
  ]
}

Bulk Link Generation

Generate links for multiple users in a single request:

{
  "scenario_id": "onboarding",
  "dataset": [
    {
      "attributes": {
        "name": "User One",
        "email": "user1@example.com",
        "cohort": "january_2024"
      }
    },
    {
      "attributes": {
        "name": "User Two",
        "email": "user2@example.com",
        "cohort": "january_2024"
      }
    },
    {
      "attributes": {
        "name": "User Three",
        "email": "user3@example.com",
        "cohort": "january_2024"
      }
    }
  ]
}

Error Responses

404 Not Found - Fullpage Disabled

{
  "message": "Fullpage webchat routes are not enabled."
}

422 Unprocessable Entity - Validation Errors

{
  "message": "The given data was invalid.",
  "errors": {
    "scenario_id": ["The scenario_id field is required."],
    "dataset": ["The dataset field is required."],
    "dataset.0.attributes": ["The attributes field is required."],
    "dataset.1.user_id": ["User id must be a string"]
  }
}

422 Unprocessable Entity - Too Many Users

{
  "message": "The given data was invalid.",
  "errors": {
    "dataset": ["Maximum number of users is 100"]
  }
}

422 Unprocessable Entity - Invalid Scenario

{
  "message": "The given data was invalid.",
  "errors": {
    "scenario_id": ["The selected scenario does not exist."]
  }
}

401 Unauthorized

{
  "message": "Unauthenticated."
}

500 Internal Server Error

{
  "error": "An error occurred while generating the deep link."
}

Best Practices

Security Considerations

1. User ID Management:
   • Use unpredictable user IDs for security
   • Avoid exposing sensitive internal IDs
   • Consider using UUIDs (auto-generated if not provided)
2. Attribute Privacy:
   • Don’t include sensitive data that shouldn’t persist in user context
   • Be mindful of data retention and privacy regulations
   • Ensure attributes comply with your privacy policy
3. Rate Limiting:
   • Be aware of any rate limits on link generation
   • Cache generated links when possible
   • Batch user link generation when feasible

Performance Optimization

1. Bulk Generation:
   • Generate multiple user links in a single request
   • Respect the maximum users per request limit
   • Process large user sets in batches
2. Attribute Efficiency:
   • Only include necessary attributes
   • Keep attribute values concise
   • Avoid large array values when possible

Integration Tips

1. Link Expiration:
   • Consider implementing link expiration on your side
   • Track link usage for analytics
   • Regenerate links for expired campaigns
2. User Experience:
   • Test links before sending to users
   • Provide fallback URLs if links fail
   • Monitor link click-through rates
3. Attribute Naming:
   • Use consistent attribute naming conventions
   • Document required vs. optional attributes
   • Ensure attribute names match your scenario configuration

Example Usage

Python Example

import requests
import json

# Configuration
base_url = "https://your-workspace.cloud.opendialog.ai/public/api"
api_token = "YOUR_API_TOKEN"
headers = {
    "Authorization": f"Bearer {api_token}",
    "Content-Type": "application/json"
}

# Generate deep links
payload = {
    "scenario_id": "customer_support",
    "dataset": [
        {
            "user_id": "user_12345",
            "attributes": {
                "name": "John Doe",
                "email": "john.doe@example.com",
                "support_tier": "premium"
            }
        },
        {
            "attributes": {  # user_id will be auto-generated
                "name": "Jane Smith",
                "email": "jane.smith@example.com",
                "support_tier": "standard"
            }
        }
    ]
}

response = requests.post(
    f"{base_url}/generate-webchat-deep-link",
    headers=headers,
    json=payload
)

if response.status_code == 200:
    links = response.json()
    for link in links:
        print(f"User {link['user_id']}: {link['url']}")
else:
    print(f"Error: {response.status_code}")
    print(response.json())

cURL Example

curl -X POST \
  https://your-workspace.cloud.opendialog.ai/public/api/generate-webchat-deep-link \
  -H 'Authorization: Bearer YOUR_API_TOKEN' \
  -H 'Content-Type: application/json' \
  -d '{
    "scenario_id": "customer_support",
    "dataset": [
      {
        "user_id": "user_12345",
        "attributes": {
          "name": "John Doe",
          "email": "john.doe@example.com",
          "product_interest": "enterprise_plan"
        }
      }
    ]
  }'

JavaScript Example

const generateDeepLinks = async () => {
  const baseUrl = 'https://your-workspace.cloud.opendialog.ai/public/api';
  const apiToken = 'YOUR_API_TOKEN';

  const payload = {
    scenario_id: 'customer_support',
    dataset: [
      {
        user_id: 'user_12345',
        attributes: {
          name: 'John Doe',
          email: 'john.doe@example.com',
          account_type: 'premium'
        }
      }
    ]
  };

  try {
    const response = await fetch(`${baseUrl}/generate-webchat-deep-link`, {
      method: 'POST',
      headers: {
        'Authorization': `Bearer ${apiToken}`,
        'Content-Type': 'application/json'
      },
      body: JSON.stringify(payload)
    });

    if (response.ok) {
      const links = await response.json();
      links.forEach(link => {
        console.log(`User ${link.user_id}: ${link.url}`);
      });
    } else {
      console.error('Error:', response.status);
    }
  } catch (error) {
    console.error('Request failed:', error);
  }
};

generateDeepLinks();

Integration Workflow

A typical integration workflow might look like:

1. Prepare User Data: Gather user information from your CRM, database, or application
2. Build Request: Format the data according to the API specification
3. Generate Links: Call the API to generate personalized deep links
4. Store Links: Save the generated URLs with user records
5. Distribute Links: Send links via email, SMS, or display in your application
6. Monitor Usage: Track link clicks and conversation starts
7. Analyze Results: Review conversation outcomes and user engagement

This creates a seamless bridge between your existing systems and OpenDialog’s conversational capabilities, enabling personalized, context-aware user experiences at scale.