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HDW LinkedIn

Integrate with Horizon Data Wave LinkedIn API

Overview

This node integrates with the Horizon Data Wave LinkedIn API to retrieve employee statistics for a specified LinkedIn company. It is useful for users who want to analyze workforce data such as demographics, roles, or other aggregated employee metrics of a company on LinkedIn.

Typical use cases include:

  • HR analytics teams wanting to understand employee distribution within a company.
  • Market researchers analyzing company workforce trends.
  • Recruiters assessing company size and employee characteristics.

For example, by providing a company's unique LinkedIn URN, you can fetch summarized employee statistics like counts by department, seniority, or location.

Properties

Name Meaning
Company URN The unique identifier of the company on LinkedIn, including prefix (e.g., "company:79111745").
Timeout Maximum time in seconds to wait for the API response before timing out (default is 300 sec).

Output

The output is a JSON object containing the employee statistics data returned from the LinkedIn API for the specified company. This typically includes aggregated metrics about the company's employees, such as counts by various categories (e.g., departments, job levels, locations).

The exact structure depends on the API response but generally provides statistical summaries rather than individual employee records.

No binary data output is produced by this operation.

Dependencies

  • Requires an API key credential for the Horizon Data Wave LinkedIn API.
  • The node makes authenticated HTTP POST requests to https://api.horizondatawave.ai/api/linkedin/company/employee_stats.
  • Proper configuration of the API authentication credential in n8n is necessary.

Troubleshooting

  • Timeouts: If the request takes longer than the specified timeout, it may fail. Increase the "Timeout" property if needed.
  • Invalid Company URN: Ensure the company URN is correctly formatted with the required prefix (e.g., "company:123456").
  • API Errors: The node surfaces detailed error messages from the API, including HTTP status codes and error headers. Common issues include invalid credentials, rate limiting, or malformed requests.
  • Rate Limits: Excessive requests may be throttled by the API. Monitor token points or execution time headers in error responses to adjust usage.
  • Continue On Fail: If enabled, errors will be returned as part of the output JSON instead of stopping execution.

Links and References


This summary is based on static analysis of the node's source code and input property definitions without runtime execution.

Discussion