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Enhanced Employees Matching Based on Varied Company Names
The Employee Listing Endpoint now matches employees based on a few company identification conventions

/ changelog

Changelog: Enhanced Employee Listing Match Rates by Company Name Matching

We are now able to match on average 107% more employees of companies via the newly revamped Employee Listing Endpoint.

The endpoint now matches employees based on LinkedIn company numerical ID and company name, not just the LinkedIn company profile URL.

Match type Previously Revamped Example
LinkedIn company profile URL https://www.linkedin.com/company/walmart/
LinkedIn company numerical ID https://www.linkedin.com/company/2646/
Company name Walmart, Walmart USA

Take for example, this is Walmart's employee count based on the previous vs newly-revamped matching algorithm:

  • Previously: 378,164
  • Revamped: 456,819

The results?

A nice improvement of 78,655 count, or 20.8%.

The previous matching algorithm

Previously we only matched company employees by checking if a person listed a company in their work experiences, specifically we only considered them a match if the company profile URL was the same as the target company profile, i.e.:

This approach resulted in more qualified profiles, but fewer results, in most cases about 50% less. However, this is not always what our users need. Some of users prefer more results returned.

New coy_name_match parameter

Introducing the new coy_name_match parameter! With this parameter, you can specify the matching criteria, to return profiles that match the name of your target company instead of just matching the company profile URL.

The coy_name_match parameter also matches company name without case sensitivity, e.g. a user profile with apple in his work experience would match for the same company of https://www.linkedin.com/company/apple. Previously that user won't be matched as an Apple employee.

We also improved the general employee listing matching algorithms with the following:

  • Company Profile URL (vanity ID)
  • Company Profile URL (numerical ID)

Let's see Amazon's improvements

Taking another beloved company as example - Amazon, this is their main LinkedIn company profile URL https://www.linkedin.com/company/amazon/

Based on the old matching algorithm, the Employee Listing Endpoint would only match:

  • 553,560 employees

With the newly-revamped algorithm and coy_name_match parameter, Amazon's other LinkedIn profiles based on vanity ID https://www.linkedin.com/company/amazon-bestt-offers/ and numerical ID https://www.linkedin.com/company/88390279/, and users who input Amazon/amazon without the company's LinkedIn URL would be considered in the same company. This brings the employee count to:

  • 579,472 employees

An 25,912 increase in Amazon employees matched that would otherwise not be.

More data for you!

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