Match Prospects

Introduction

The Match Prospects endpoint allows users to accurately match individual prospects to unique Prospect IDs using multiple fetchers, such as email, phone number, LinkedIn profile, or name and company combination. This ensures accurate lead identification and enhances sales and marketing workflows.

📌 Key Benefits:

Match and validate lead data across multiple fetchers.
Enhance B2B prospecting by linking leads to business profiles.
Improve lead scoring and segmentation with high-quality matches.
Reduce data duplication and inconsistencies.

Endpoint: `POST /prospects/match`

How It Works

Input: Provide a list of prospects with at least one fetcher (e.g., email, phone number, LinkedIn URL, or name & company).
Processing: The system cross-references internal datasets and returns the best possible matches.
Output: A structured response with matched Prospect IDs, maintaining the same order as the input list.

Request Schema

Field	Type	Description
prospects_to_match:	Array	A list of prospect fetchers to match
`email`	String	The prospect’s email address
`phone_number`	String	The prospect’s phone number
`full_name`	String	The prospect’s full name (must be accompanied by `company_name`)
`company_name`	String	The prospect’s company name (must be accompanied by `full_name`)
`linkedin`	String	LinkedIn profile URL
`business_id` (optional)	String	Filters the match to a specific company

full_name must be accompanied with company_name

Example Request (cURL)

curl -X POST "https://api.explorium.ai/v1/prospects/match" \
  -H "API_KEY: your_api_key_here" \
  -H "Content-Type: application/json" \
  -d '{
  "request_context": {
  
  "prospects_to_match": [
    {
      "business_id": "19fbe842a2e51db95d4f92333f2cc63a",
      "linkedin": "https://www.linkedin.com/in/russell-lumpkin-07585b128"
    },
    {
      "full_name": "tim cook",
      "company_name": "Apple"
    },
    {
      "email": "[email protected]"
    }
  ]
}
'

Example Response

{
  "response_context": {
    "correlation_id": "a30a507872c64b428f067115aaf64cad",
    "request_status": "success",
    "time_took_in_seconds": 1.627
  },
  "total_results": 3,
  "total_matches": 3,
  "matched_prospects": [
    {
      "input": {
        "business_id": "19fbe842a2e51db95d4f92333f2cc63a",
        "full_name": null,
        "company_name": null,
        "email": null,
        "phone_number": null,
        "linkedin": "https://www.linkedin.com/in/russell-lumpkin-07585b128"
      },
      "prospect_id": "6ffd52c681452e2da8aac7ec3efb174f4604734c"
    },
    {
      "input": {
        "business_id": null,
        "full_name": "tim cook",
        "company_name": "Apple",
        "email": null,
        "phone_number": null,
        "linkedin": null
      },
      "prospect_id": "07352d784dc9e77b06b2517dec224b53e4f482dd"
    },
    {
      "input": {
        "business_id": null,
        "full_name": null,
        "company_name": null,
        "email": "[email protected]",
        "phone_number": null,
        "linkedin": null
      },
      "prospect_id": "ee936e451b50c70e068e1b54e106cb89173198c4"
    }
  ]
}

Best Practices

Use multiple fetchers whenever possible to increase match accuracy.
Combine with business_id to refine matches to a specific company.
Ensure accurate and up-to-date data for improved results.
Handle null values in responses where no match is found.

📌 For more details on request formats and usage, refer to the API documentation.

Body Params - Try Me Example

try : linkedin: https: https://www.linkedin.com/in/russell-lumpkin-07585b128
   		business_id: 19fbe842a2e51db95d4f92333f2cc63a
 or:  full_name: satya nadella, 
    	company_name: Microsoft
 or:  email: [email protected]

Introduction

Endpoint: POST /prospects/match

Request Schema

full_name must be accompanied with company_name

Endpoint: `POST /prospects/match`