Company Lookalikes can be used to retrieve a ranked list of companies that are similar to a given reference company. The similar companies are identified using a machine learning model that analyzes industry, revenue range, employee count, and other firmographic signals. These lookalike companies can be used to power prospecting, territory planning, or market expansion workflows where one wants to quickly find companies that "look like" a successful or high-priority account.

To find Company Lookalikes, select the companyId, which identifies the company you want to use as the basis for finding lookalikes. If you are not able to provide the companyId, you can provide only the companyName instead, the service will attempt to resolve the best matching company and then return lookalike companies based on that company. The more precise the company name is (for example, use the full company name with correct spelling and full legal name), the more likely the service is able to track down the company ID and use it to find lookalikes.

Optionally, you can narrow the results using the following boolean filters. When set to true, each filter restricts lookalikes to companies that share the corresponding attribute with the reference company:

• filter[sameRevenueRange]: same revenue range
• filter[sameCountry]: same country
• filter[sameIndustry]: same industry
• filter[sameEmployeeRange]: same employee count range

Behind the scenes, the model uses a semantic vector representation of the reference company's data to efficiently find similar companies in the ZoomInfo database.

The endpoint returns up to 100 lookalike companies, ordered from the most similar company to the least similar company (descending order by similarity score attributes.score). To control the number of results returned, use the page[size] parameter with any integer value between 1 and 100. Each result includes the company name, similarity score, rank, and key firmographic attributes such as industry, revenue range, employee range, and country.