Overview

This page details the company-related fields that we provide through the Company Enrichment and Company Search APIs.

• Base Company Fields: Common fields available to all customers by default
• Company Insights Fields: Premium fields targeted towards investment and market research use cases, built by aggregating data from our Person dataset
• Premium Company Fields: Premium company fields such as related companies, subsidiaries, acquisitions and more

📘

Field Availability

Please note: Not all fields are available in all bundles.

• For more information about data formatting, see Data Types.
• For a full example record, see Example Company Record.
• For a simplified overview of our company fields, check out the Company Data Overview.
• For more details about our company fields, including fill rates and which fields are included in the base vs premium field bundles, check out our Company Stats pages.
• For a full data ingestion JSON schema, check out this page.
• If you'd like access to premium fields or have questions about which fields are included in your specific field bundle(s), please speak to one of our data consultants.

Base Company Fields

These fields are available to all customers by default.

Identifiers

id

Field Details

🚧

Change to alphanumeric hash format in v26.0

With our April 2024 release, the format of the id field in our company records changed to an alphanumeric format and the previous id format was moved to the linkedin_slug field.

For more information see our April 2024 Release Announcement (v26.0).

The ID is a unique, hashed value that represents a specific company record.

Example

  "id": "tnHcNHbCv8MKeLh92946LAkX6PKg"

name

Field Details

The company name will be lowercase with any leading/trailing whitespace removed. It is not guaranteed to be unique.

For the correct capitalization of the company name, see display_name.

The name value returned here does not undergo much cleaning or standardization. However, we clean and tokenize company names behind the scenes so they can be found using the Company Search API. To see how company name cleaning works, check out the Company Cleaner API.

Example

  "name": "people data labs"

display_name

Field Details

The display_name field preserves the capitalization of the company name (unlike name which is always lowercase). display_name is set using the company’s self-reported name, so it should be accurate even for companies with non-standard capitalization (such as VMware, FedEx, or Dell EMC).

Use this field to display properly capitalized company names in a UI or other customer-facing project or product.

Example

  "display_name": "VMware"

Company Information

affiliated_profiles

Field Details

A list of Company IDs that we have flagged as having an association to this company (either a parent or a subsidiary.) See Parents and Subsidiaries for fields based on specific company associations.

Example

  "affiliated_profiles": [
    "a1cpOkL4SHp0wSAKjbCeuwtAlno0",
    "3WBa1kollMtBbib5DoiCwwhyD9ks"
  ]

alternative_domains

Field Details

If a company rebrands or otherwise changes its primary domain, old company websites will be kept in this list.

See website for how we handle domains.

Example

  "alternative_domains": [
    "peopledatalabs.com",
    "talentiq.co",
    "peopledatalabs.co"
  ]

alternative_names

Field Details

A list of names associated with the company filtered to ensure data quality.

Example

  "alternative_names": [
    "people data labs",
    "people data labs inc",
    "talentiq"
  ]

employee_count

Field Details

employee_count is an integer greater than or equal to zero. We calculate it by finding the number of profiles whose experience.company.id matches the company with a non-null job_start_date and no end date.

For the company's self-reported size range, use the size field instead. For more information about the different types of employee count data we provide, see Employee Count Fields.

This number may be higher or lower than a company's real employee count depending on how many false positives and false negatives we have in our data as well as missing or duplicate individuals.

Example

  "employee_count": 78

employee_count_by_country

Field Details

Each country will be one of our Canonical Countries. For more information about how each count is calculated, see Employee Count Breakdowns.

Beginning in v25.0, this field will also contain an other_uncategorized subfield. Profiles that we have associated with the company but do not have enough information to assign a location to will be included in this field. For more information, see Employee Count Fields.

Example

  "employee_count_by_country": {
    "united states": 67,
    "canada": 2,
    "india": 1,
    "bangladesh": 1,
    "other_uncategorized": 2
  }

founded

Field Details

The founding year will be an integer greater than zero. If no year is found, it will be null.

If different sources list different founding years, we will choose the year that appears in the most sources. If multiple years appear in the same number of sources, we will use the latest year.

Example

  "founded": 2015

headline

Field Details

headline is a short description of the company, limited to 300 characters.

Example

  "headline": "Your Single Source of Truth"

size

Field Details

The value of this field will be one of our canonical Company Sizes. We derive it from the company's self-reported size on their social media profile.

For the true number of employees, use the employee_count field.

Example

  "size": "11-50"

summary

Field Details

The company summary is a lowercase string and can contain escape characters such as \n. The string is limited to a maximum of 1000 characters.

Example

  "summary": "people data labs builds people data. \n\nuse our dataset
              of 1.5 billion unique person profiles to build products,
              enrich person profiles, power predictive modeling/ai,
              analysis, and more. we work with technical teams as their
              engineering focused people data partner. \n\nwe work with
              thousands of data science teams as their engineering focused
              people data partner. these include enterprises like adidas,
              ebay, and acxiom, as well as startups like madison logic,
              zoho, and workable. we are a deeply technical company, and
              are backed by two leading engineering venture capital firms
              - founders fund and 8vc.",

tags

Field Details

Each tag is a lowercase string.

There may be tags that seem to overlap (for example: "data", "analytics" and "data and analytics"). This is intentional so that it is easier to search for companies matching a tag.

Example

  "tags": [
    "data",
    "people data",
    "data science",
    "artificial intelligence",
    "data and analytics",
    "machine learning",
    "analytics",
    "database",
    "software",
    "developer apis"
   ]

website

Field Details

This field contains the address of the primary company website. It should not be an address of a social profile.

We standardize websites by removing https://www. and any additional subdomains (with certain exceptions). Popular hosting platforms (like Facebook, Blogspot, Wix, etc.) will retain their subdomains. For example, samspizza.blogspot.com or etsy.com/sams-pizza.

Websites using link shortening services (like Bit.ly, TinyURL, ShortURL, etc.) will appear in full.

We have a list of invalid URL items (domains, subdomains and TLDs) that we check against. We also check if an iteration of the company name appears in the website address as a simple validation.

Ideally, this is the website address that people commonly use when accessing a company's site (such as facebook.com) and not an alias (such as fb.com).

As with Social Presence, we do not verify that the website is valid, so that we don’t DDoS them.

Example

  "website": "peopledatalabs.com"

Funding Data

funding_stages

Field Details

An unordered list of all funding stages for funding events announced by the company.

This is generated from the separate events in funding_details.funding_type.

All values in the list must be Canonical Funding Rounds. If there are multiple events tied to the same round (ex: Series A), that label will only appear once in the list.

Example

  "funding_stages": [
    "series_b",
    "series_a",
    "seed"
  ]

last_funding_date

Field Details

The date of the company’s most recent funding event. This represents the publicly disclosed date of the closing of the financing, and will be independent of any prior dates associated with that same funding round.

Example

  "last_funding_date": "2021-11-16"

latest_funding_stage

Field Details

Must be one of the Canonical Funding Rounds.

Example

  "latest_funding_stage": "series_b"

number_funding_rounds

Field Details

The number of separate funding events for the company. This is the total number of events in funding_details.

If multiple events are tied to the same funding round, they will each be counted toward the total (ex: 3 Series A events will add 3 to the total count).

Example

  "number_funding_rounds": 7

total_funding_raised

Field Details

The cumulative amount raised by the company during all publicly disclosed funding rounds.

The value for this field is represented in USD. It is the sum of all known values from individual funding rounds (each of which is represented in $ USD using “then-current” currency exchange rates).

Example

  "total_funding_raised": 55250000.0

Industry Types

industry

Field Details

Industry is self-reported and will be one of our Canonical Industries. If no industry is found, the field will be null.

Example

  "industry": "animation"

naics

Field Details

Each NAICS code associated with the company will be included in the list. For each NAICS code, we provide the actual six-digit code as well as the official description for each level of the NAICS code.

PDL uses NAICS 2017 industry categorization.

PDL offers self-reported NAICS industry categorizations within the company data, where this data serves as an alternative to Industry and SIC for users to categorize or segment companies. Because the data PDL publishes represents self-reported data where the industry values were selected by employees of those companies prior to the 2022 revision, we have not bulk converted to, or inferred, NAICS 2022 categories for our existing NAICS values.

A NAICS code doesn’t have to use all six digits. Any unspecified field(s) in our data will have a null value.

Example

  "naics": [
    {
      "naics_code": "423920",
      "sector": "wholesale trade",
      "sub_sector": "merchant wholesalers, durable goods",
      "industry_group": "miscellaneous durable goods merchant wholesalers",
      "naics_industry": "toy and hobby goods and supplies merchant wholesalers",
      "national_industry": "toy and hobby goods and supplies merchant wholesalers"
    },
    ...
  ]

sic

Field Details

Each SIC code associated with the company will be included in the list. For each SIC code, we provide the actual four-digit code as well as the official description for each level of the SIC code.

A SIC code doesn’t have to use all four digits. Any unspecified field(s) in our data will have a null value.

Example

  "sic": [
    {
      "sic_code": "7372",
      "major_group": "business services",
      "industry_group": "computer programming, data processing, and other computer related services",
      "industry_sector": "prepackaged software"
    },
    ...
   ]

Primary Location

location

Field Details

A company's location is the location of its Headquarters (HQ). We determine a company’s current Headquarters/primary office based on the location that we see most often in our sources.

For more information on our standard location fields, see https://docs.peopledatalabs.com/docs/data-types#locations.

Example

  "location": {
    "name": "san francisco, california, united states",
    "locality": "san francisco",
    "region": "california",
    "metro": "san francisco, california",
    "country": "united states",
    "continent": "north america",
    "street_address": "455 market street",
    "address_line_2": "suite 1670",
    "postal_code": "94105",
    "geo": "37.77,-122.41"
  }

Stock Information

gics_sector

Field Details

gics_sector is how a stock exchange classifies the industry of a given company.

The value of gics_sector will always be one of our Canonical GICS Sectors or null if the company's type is not public.

Example

  "gics_sector": "technology"

mic_exchange

Field Details

mic_exchange represents the Market Identified Code (MIC) standard exchange code corresponding to the stock exchange of the company.

The value of mic_exchange will always be one of our Canonical MIC Codes or null if there is no ticker.

Example

  "mic_exchange": "xnams"

ticker

Field Details

ticker is the uppercase string of the company’s stock symbol.

If a company is not public (as listed in its type), its ticker will be null.

Example

  "ticker": "MOO"

type

Field Details

type will be one of the Canonical Company Types. If a company has a known ticker, then its type is public. If a company does not have a ticker and its ultimate parent company does, then its type is public_subsidiary.

Example

  "type": "private"

Social Presence

We currently include company social profiles for LinkedIn, Yellow Pages, Xing, Twitter, Facebook and Crunchbase. Any profiles that we find for the company from these sources will be added to the profiles list.

Each social profile URL has one or more standard formats that we parse and turn into a standard PDL format for that social URL. We invalidate profiles that have non-valid company stubs (for example, linkedin.com/in), and we also have a blacklist of usernames that we know are invalid.

We do not validate if a URL is valid (that is, whether you can access it) because doing this at scale is considered a Direct Denial of Service (DDoS) attack and/or a form of crawling. This is highly discouraged! We try to mitigate invalid URLs as much as possible by using Entity Resolution (Merging) to link URLs together and then tagging the primary URL at the top level for key networks.

linkedin_id

Example

  "linkedin_id": "18170482"

linkedin_slug

Field Details

To support our upcoming change to PDL Company IDs, we are adding the new linkedin_slug field. This field is generated in the same way as our current company id field.

For new company records that do not have associated LinkedIn pages, this field will be null.

Example

  "linkedin_slug": "peopledatalabs"

linkedin_url

Example

  "linkedin_url": "linkedin.com/company/peopledatalabs"

facebook_url

Example

  "facebook_url": "facebook.com/peopledatalabs"

twitter_url

Example

  "twitter_url": "twitter.com/peopledatalabs"

profiles

Example

  "profiles": [
    "linkedin.com/company/peopledatalabs",
    "linkedin.com/company/18170482",
    "facebook.com/peopledatalabs",
    "twitter.com/peopledatalabs",
    "crunchbase.com/organization/talentiq"
  ]

PDL Record Information & Metadata

dataset_version

Field Details

Note: This number corresponds to the data release number, not the API release number.

Example

  "dataset_version": "19.2"

Company Insights Fields

These fields are targeted towards investment and market research use cases and are built by aggregating data from our Person Dataset.

Average Employee Tenure

Average employee tenure is the average number of years employees work for the company. It is represented by a floating number greater than zero and rounded to the nearest thousandth. It could skew lower if there have been a lot of recent hires.

The average is calculated using experience.start_date and experience.end_date for each employee found in our Person records.

If no start date is given or if a date only contains a year but no month, then the experience is not counted toward the average.

average_employee_tenure

Field Details

This insight shows the average number of years that employees at the company have worked based on experience.start_date and experience.end_date.

Example

  "average_employee_tenure": 2.75

average_tenure_by_level

Field Details

This insight shows the average number of years that employees at the company have worked broken out by their level at the company. The average for each level is calculated using the same logic as average_employee_tenure.

The level names come from experience.title.levels, meaning they will always be one of the Canonical Job Levels.

Example

  "average_tenure_by_level": {
    "entry": 0.3,
    "unpaid": 2.0,
    "senior": 6.0,
    "director": 3.0,
    "vp": 2.4,
    "training": 0.2,
    "manager": 4.0,
    "owner": 3.2,
    "partner": 2.4,
    "cxo": 8.1
  }

average_tenure_by_role

Field Details

This insight shows the average number of years that employees at the company have worked broken out by their role at the company. The average for each role is calculated using the same logic as average_employee_tenure.

The role names come from experience.title.role, meaning they will always be one of the Canonical Job Roles.

Example

  "average_tenure_by_role": {
    "real_estate": 4.5,
    "design": 2.0,
    "trades": 3.2,
    "marketing": 0.1,
    "education": 6.5,
    "legal": 8.0,
    "customer_service": 4.0,
    "finance": 5.0,
    "public_relations": 8.1,
    "engineering": 2.1,
    "human_resources": 0.5,
    "media": 0.4,
    "sales": 0.6,
    "operations": 0.1,
    "health": 2.0
  }

Employee Count Breakdowns

The count for each category will always be an integer value greater than or equal to zero.

This number may be higher or lower than a company's real employee count depending on how many false positives and false negatives we have in our data, missing and duplicate individuals, and missing information on start dates and job roles.

If no start date is given, then the experience is not counted.

For the overall employee count, see employee_count. For the company's self-reported size, see size.

Note that discrepancies between the employee_count, the most recent employee_count_by_month, and aggregatedemployee_count_by_month_by_role and employee_count_by_month_by_level counts are expected. For more information about the logic used to calculate these values, see this page.

employee_count_by_month

Field Details

The total number of profiles associated with this company at the end of each month in the format YYYY-MM. The date range begins at the start date of the first associated employee or January 1, 2010, whichever is most recent. The final month in the range will be the last full month before the last monthly Data Build. Most often this is the month before request was submitted. For example, if you make a request mid-March, the response will contain all data up to that February.

Example

  "employee_count_by_month": {
    "2021-07": 84,
    "2021-08": 86,
    "2021-09": 84
  }

employee_count_by_month_by_level

Field Details

The total number of profiles associated with this company at the end of each month in the format YYYY-MM broken down by experience.title.levels. The level names will always be one of the Canonical Job Levels.

The date range begins at the start date of the first associated employee or January 1, 2010, whichever is most recent. The final month in the range will be the last full month before the last monthly Data Build. Most often this is the month before request was submitted. For example, if you make a request mid-March, the response will contain all data up to that February.

If a person changes levels within a company during the same month, they will be counted in the same month towards both levels. An individual may have more than a single level for the same experience object, in which case they will contribute towards multiple levels.

Example

  "employee_count_by_month_by_level": {
    "2015-03": {
      "partner": 0,
      "vp": 0,
      "owner": 1,
      "entry": 0,
      "director": 0,
      "unpaid": 0,
      "senior": 0,
      "cxo": 1,
      "manager": 0,
      "training": 0
    },
    ...
    "2021-06": {
      "partner": 0,
      "vp": 3,
      "owner": 1,
      "entry": 10,
      "director": 2,
      "unpaid": 2,
      "senior": 5,
      "cxo": 1,
      "manager": 3,
      "training": 0
    }
  }

employee_count_by_month_by_role

Field Details

The total number of profiles associated with this company at the end of each month in the format YYYY-MM broken down by experience.title.role. The role names will always be one of the Canonical Job Roles.

The date range begins at the start date of the first associated employee or January 1, 2010, whichever is most recent. The final month in the range will be the last full month before the last monthly Data Build. Most often this is the month before request was submitted. For example, if you make a request mid-March, the response will contain all data up to that February.

If a person changes roles with a company during the same month, they will only be counted for a single role.

Beginning in v25.0, each month will also contain an other_uncategorized subfield. Profiles that we have associated with the company but do not have enough information to assign a role to will be included in this field. For more information, see Employee Count Fields.

Example

  "employee_count_by_month_by_role": {
    "2015-03": {
      "engineering": 0,
      "education": 0,
      "media": 0,
      "design": 0,
      "trades": 0,
      "health": 0,
      "real_estate": 0,
      "customer_service": 0,
      "legal": 0,
      "human_resources": 0,
      "finance": 0,
      "public_relations": 0,
      "marketing": 0,
      "sales": 0,
      "operations": 0,
      "other_uncategorized": 1
    },
    ...
    "2021-06": {
      "engineering": 1,
      "education": 0,
      "media": 0,
      "design": 0,
      "trades": 0,
      "health": 0,
      "real_estate": 0,
      "customer_service": 0,
      "legal": 0,
      "human_resources": 0,
      "finance": 0,
      "public_relations": 0,
      "marketing": 0,
      "sales": 0,
      "operations": 0,
      "other_uncategorized": 8
    }
  }

employee_count_by_role

Field Details

The total number of profiles associated with this company at the end of the most recent month in the format YYYY-MM broken down by experience.title.role. The role names will always be one of the Canonical Job Roles. This field will also contain an other_uncategorized subfield that contains profiles we have associated with the company but do not have enough information to assign a role to.

This field is equivalent to the final month in the employee_count_by_month_by_role field.

Example

  "employee_count_by_role": {
    "real_estate": 0,
    "design": 2,
    "trades": 0,
    "marketing": 4,
    "education": 4,
    "legal": 0,
    "customer_service": 10,
    "finance": 6,
    "public_relations": 1,
    "engineering": 24,
    "human_resources": 3,
    "media": 1,
    "sales": 12,
    "operations": 10,
    "health": 0,
    "other_uncategorized": 10
  }

Employee Growth and Churn Rates

All calculation time frames are based on the month that you make the request. If you make the request in April, the three-month rate will use data from January onward.

If no start date is given, then the experience is not counted.

Additionally, if a date only contains a year but no month, it is assumed to be to be January for start dates and December (or the current month if December is in the future) for end dates.

employee_churn_rate

Field Details

The churn rate is rounded to four decimal points and is always greater than or equal to 0. If the company had 0 employees or did not exist at the start time for a specific window, then the churn rate is null.

Churn rate is calculated as max(employee_count_n_months_ago - employee_count_current, 0)/employee_count_n_months_ago. For example, if a company has 200 employees at the beginning of the month, and at the end of the month 100 leave and 100 remain then its churn rate = 100 / 100 = 1.0.

Example

  "employee_churn_rate": {
    "3_month": 0.015,
    "6_month": 0.02,
    "12_month": 0.035,
    "24_month": 0.155
  }

employee_growth_rate

Field Details

The growth rate is rounded to four decimal points and can be negative if the current number of employees is less than in the past. If the company had zero employees or did not exist at the start time for a specific window, then the growth rate is null.

Growth rate is calculated as (current_employee_count / previous_employee_count) - 1. For example, if a company has 100 employees at the beginning of the month, and at the end of the month has grown to 200 employees then its growth rate = (200 / 100) - 1 = 1.0.

Example

  "employee_growth_rate": {
    "3_month": 0.0595,
    "6_month": 0.0723,
    "12_month": 0.8542,
    "24_month": 1.4722
  }

employee_growth_rate_12_month_by_role

Field Details

The 12 month growth rate of the total number of profiles associated with this company at the end of the most recent month in the format YYYY-MM broken down by experience.title.role. The role names will always be one of the Canonical Job Roles. This field will also contain an other_uncategorized subfield that contains profiles we have associated with the company but do not have enough information to assign a role to.

The growth rate is rounded to four decimal points and can be negative if the current number of employees is less than in the past. If the company had zero employees or did not exist at the start time for a specific window, then the growth rate is null.

Growth rate is calculated as (current_employee_count / previous_employee_count) - 1. For example, if a company has 100 employees at the beginning of the month 12 months ago, and at the end of the most recent month has grown to 200 employees then its growth rate = (200 / 100) - 1 = 1.0.

The 12 month growth rate will be computed using the last full month before the last monthly Data Build. Most often this is the month before request was submitted. For example, if you make a request mid-March, the response will contain the 12 month growth rate from February.

Example

 "employee_count_12_month_growth_by_role": {
    "real_estate": null,
    "design": -0.2500,
    "trades": null,
    "marketing": -0.5000,
    "education": 0.0000,
    "legal": null,
    "customer_service": -0.4545,
    "finance": -0.2500,
    "public_relations": null,
    "engineering": -0.1220,
    "human_resources": -0.1667,
    "media": 0.0000,
    "sales": -0.1852,
    "operations": 0.000,
    "health": null,
    "other_uncategorized": 0.1471
  }

Gross Additions and Departures

This insight shows the total number of employees that joined or left the company each month.

The count for each month will always be an integer greater than or equal to zero. The month range begins at the start date of the first associated employee or January 1, 2010, whichever is most recent. The final month in the range will be the last full month before the last monthly Data Build. Most often this is the month before request was submitted. For example, if you make a request mid-March, the response will contain all data up to that February.

This number may be higher or lower than a company's real employee count depending on how many false positives and false negatives we have in our data, missing and duplicate individuals, and missing information on start/end dates.

If a start or end date is not given or only contains a year but no month, it is not counted. This differs from employee_count_by_month that assumes January if there is no month.

gross_additions_by_month

Field Details

The total number of profiles that joined the company each month in the format YYYY-MM based on experience.start_date.

Example

  "gross_additions_by_month": {
    "2015-03": 1,
    "2015-04": 1,
    ...
    "2021-05": 2,
    "2021-06": 2
  }

gross_departures_by_month

Field Details

The total number of profiles that left the company each month in the format YYYY-MM based on experience.end_date.

Example

  "gross_departures_by_month": {
    "2015-03": 1,
    "2015-04": 1,
    ...
    "2021-05": 2,
    "2021-06": 2
  }

Inferred Revenue

inferred_revenue

Field Details

A company's inferred revenue is an estimated range of its annual revenue in US dollars and can be used as a filter in Company Search queries.

The revenue estimate is calculated using a predictive model that factors in details generated for our Company Insights Fields (for example, employee_count_by_month_by_role) as well as for other inputs that have been shown to be highly correlative.

The range will be one of our Canonical Inferred Revenue Ranges.

Example

  "inferred_revenue": "$10M-$25M"

Recent Executive Changes

These insights provide details on executives that have joined or left the company in the past three months at the time you make the request.

There is no limit on the number of executives that can be in either list. To determine if someone is an executive, we check if their experience.title.levels in the company matches CXO, owner or VP. If no level is specified, then the experience is not counted.

If a start or end date is not given for an executive, then the experience is not counted. If the date only contains a year, the month is assumed to be January.

recent_exec_departures

Field Details

For each executive that has left the company in the past three months, we provide the following information:

Example

  "recent_exec_departures": [
    {
      "departed_date": "2024-06",
      "pdl_id": "sosPKkiBABHsppzWEYyqgg_0000",
      "job_title": "vice president of revenue operations",
      "job_title_role": "analyst",
      "job_title_sub_role": "revenue_operations",
      "job_title_class": "general_and_administrative",
      "job_title_levels": ["vp"],
      "new_company_id": "ZFOfaDnanwu1hrtXsyfFEw521uw0",
      "new_company_job_title": "senior vice president, revenue operations",
      "new_company_job_title_role": "analyst",
      "new_company_job_title_sub_role": "revenue_operations",
      "new_company_job_title_class": "general_and_administrative",
      "new_company_job_title_levels": ["senior", "vp"]
    },
    ...
  ]

recent_exec_hires

Field Details

For each executive that has joined the company in the past three months, we provide the following information:

Example

"recent_exec_hires": [
  {
    "joined_date": "2024-06",
    "pdl_id": "un-fsOccjHy1yElqJObW6g_0000",
    "job_title": "chief of staff to the chief executive officer and founder",
    "job_title_role": "operations",
    "job_title_sub_role": "aides",
    "job_title_class": "general_and_administrative",
    "job_title_levels": ["owner"],
    "previous_company_id": "RjhjJnYUCiAfXFyxCHLDQQ5opPrK",
    "previous_company_job_title": "business operations manager, reality labs",
    "previous_company_job_title_role": "professional_service",
    "previous_company_job_title_sub_role": "investment_banking",
    "previous_company_job_title_class": null,
    "previous_company_job_title_levels": ["manager"]
  },
    ...
  ]

Top Next and Previous Employers

The top ten next and previous companies employees are broken down by job role.

Companies are listed using their PDL Company ID.

The first list of companies will be under the "all" key. This represents the top 10 companies for any role.

The roles are based on the employee’s role at the company queried. Each role listed in the break down will come from the Canonical Job Roles.

If no start date is given or no role exists, then the experience is not counted.

If there are fewer than ten next/previous employers for a role, it will return as many as there are.

top_next_employers_by_role

Field Details

This insight uses experience.title.role and experience.start_date to find the top next employers. Companies are ranked by the number of previous employees currently employed there.

A company is considered to be a "next employer" if the employee has a start date after their start date for the company being queried.

Example

  "top_next_employers_by_role": {
    "all": {
      "aKCIYBNF9ey6o5CjHCCO4goHYKlf" : 573,
      "RjhjJnYUCiAfXFyxCHLDQQ5opPrK" : 498,
      ...
    },
    "finance": {
      "RZOFiRjw26VpLObnwmYXGgRyn3aW" : 294,
      "BWiTKOBgRTsSttn62R7EBQvww4gF" : 112,
      ...
    },
    ...
  }

top_previous_employers_by_role

Field Details

This insight uses experience.title.role and experience.start_date to find the top previous employers. Companies are ranked by the number of current employees previously employed there.

A company is considered to be a "previous employer" if the employee has a start date before their start date for the company being queried.

Example

  "top_previous_employers_by_role": {
    "all": {
      "aKCIYBNF9ey6o5CjHCCO4goHYKlf" : 573,
      "RjhjJnYUCiAfXFyxCHLDQQ5opPrK" : 498,
      ...
    },
    "finance": {
      "RZOFiRjw26VpLObnwmYXGgRyn3aW" : 294,
      "BWiTKOBgRTsSttn62R7EBQvww4gF" : 112,
      ...
    },
    ...
  }

Top US Metros

top_us_employee_metros

Field Details

This insight contains the top ten US metros for the company, ordered by the current headcount at each location. For each metro, we also provide the current headcount and the growth rate in that metro over the last twelve months.

Each metro listed is one of our Canonical Metros.

To determine the headcount at each location, we use our Person Data to find the location where each current employee works. If an employee does not have location data or they are not based in the US, they are not included in the count.

Example

  "top_us_employee_metros": {
    "san francisco, california, united states" : {
      "current_headcount" : 1207,
      "12_month_growth_rate" : .0040
    },
    "austin, texas, united states" : {
      "current_headcount" : 532,
      "12_month_growth_rate" : .0900
    },
    ...
  }

Premium Company Fields

These high-value fields are available through our premium offerings.

Premium Company Information

linkedin_follower_count

Field Details

The number of followers on a company’s LinkedIn profile.

Example

   "linkedin_follower_count": 5880

Funding Details

funding_details

Field Details

Each publicly disclosed funding event will be added to the funding_details list as an Object with the following fields:

Example

  "funding_details": [
    {
      "funding_round_date": "2021-11-16",
      "funding_raised": 45000000.0,
      "funding_currency": "usd",
      "funding_type": "series_b",
      "investing_companies": [
        "UHKkwjzET0f4c2FLBt5BOgB7eZH9",
        "s5O9wCcVnokBzzvX4TQwEwg07z1L"
      ],
      "investing_individuals": [
        "Guillaume \"G\" Cabane"
      ]
    },
    ...
  ]

Parents and Subsidiaries

These insights provide the company IDs of the queried company's parent and subsidiary companies.

all_subsidiaries

Field Details

The subsidiary company values will be the ID of the company. If no subsidiaries are found, the value will be null.

Example

  "all_subsidiaries" : [
    "HwrPqD6yDTnKmmPQFCgIeQ5hOn8j",
    "xhI4e4JvjGZF4SprW5hhCgmLfVjB",
    "niEc7rpuQ1GXwpuDPeeN2QWYggDC",
    "2BrnzFlEfHtRXJUakLCQYQuO0JnJ",
    "uBF8GihqobELnphsfR9ppwQbM9x7",
    "N7iFUv1vUYWF8t0JXHmL5gvFy4XE",
    "97JIBSIC059vdTevziAFJA7qSRNZ",
    "amtMwZGXmNDYoqBCSQBXQAxXVeWV"
  ]

direct_subsidiaries

Field Details

The subsidiary company values will be the ID of the company. If no subsidiaries are found, the value will be null.

Example

  "direct_subsidiaries" : [
    "HwrPqD6yDTnKmmPQFCgIeQ5hOn8j",
    "2BrnzFlEfHtRXJUakLCQYQuO0JnJ",
    "uBF8GihqobELnphsfR9ppwQbM9x7",
    "N7iFUv1vUYWF8t0JXHmL5gvFy4XE",
    "97JIBSIC059vdTevziAFJA7qSRNZ",
    "amtMwZGXmNDYoqBCSQBXQAxXVeWV"
  ]

immediate_parent

Field Details

The parent company value will be the ID of the company. If no parents are found, the value will be null.

Example

  "immediate_parent": "amtMwZGXmNDYoqBCSQBXQAxXVeWV"

ultimate_parent

Field Details

The parent company value will be the ID of the company. If no parents are found, the value will be null.

Example

  "ultimate_parent": "0XQ1XCKrHIFF3H6tBVRdzAIknJNS"

ultimate_parent_ticker

Field Details

The ultimate_parent_ticker field will be populated for records where the company is a subsidiary of a public company. These companies will also have a type value of public_subsidiary following the v28.0 release in October 2024.

Example

  "ultimate_parent_ticker": "CRM",

ultimate_parent_mic_exchange

Field Details

The ultimate_parent_mic_exchange field will be populated for records where the company is a subsidiary of a public company. These companies will also have a type value of public_subsidiary following the v28.0 release in October 2024.

Example

  "ultimate_parent_mic_exchange": "XNYS"