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

For access to fields beyond the Base Company Fields, please speak to one of our data consultants.

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Formatting Notes

For more information about data formatting, see Data Types.

Base Company Fields

These fields are available to all customers by default.

Identifiers

id

Field Details

The ID value is currently non-persistent and generated from the company's primary LinkedIn username.

Example

  "id": "peopledatalabs"

name

Field Details

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

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"

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": [
    "engagio",
    "demandbase"
  ]

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 zero. We calculate it by finding the number of our profiles whose job_company_id matches the company. For the company's self-reported size range, use the size field.

Because this insight relies on job_company_id, it only counts employees who list their current primary job as the company. Companies which tend to hire more part-time workers may have a lower employee_count than their actual headcount.

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 on missing and duplicate individuals.

Example

  "employee_count": 78

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. 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"

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"
  }

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.

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"
    },
    ...
   ]

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 is a numeric code that corresponds to the stock exchange and makes it possible to join data when companies on two or more exchanges share the same ticker symbol.

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

Example

  "mic_exchange": "xnms"

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.

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_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"
  ]

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. Note: this differs from employee_count, which only uses job_company_id and therefore does not care about start and end dates.

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

employee_count_by_country

Field Details

Each country will be one of our Canonical Countries.

Example

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

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.

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.

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.

If a person changes roles with a company during the same month, they will be counted in the same month towards both roles.

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,
    },
    ...
    "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,
    }
  }

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. Note: this differs from employee_count which only uses job_company_id and therefore does not care about start and end dates.

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 employees_departed / current_employees. 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
  }

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.

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": "10,000,000-25,000,000"

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": "2021-04",
      "pdl_id": "qYZGvMnVsvaCNJ5743pbbA_0000",
      "job_title": "vice president of engineering",
      "job_title_role": "engineering",
      "job_title_sub_role": null,
      "job_title_levels": ["vp"],
      "new_company_id": "google",
      "new_company_job_title": "chief technology officer",
      "new_company_job_title_role": "engineering",
      "new_company_job_title_sub_role": null,
      "new_company_job_title_levels": ["cxo"]
    },
    ...
  ]

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": "2021-09",
      "pdl_id": "iL40x4vUwYd313hRm8DgOQ_0000",
      "job_title": "vice president, sales",
      "job_title_role": "sales",
      "job_title_sub_role": null,
      "job_title_levels": ["vp"],
      "previous_company_id": "spotify",
      "previous_company_job_title": "sales manager",
      "previous_company_job_title_role": "sales",
      "previous_company_job_title_sub_role": 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": {
      "google" : 573,
      "facebook" : 498,
      ...
    },
    "finance": {
      "microsoft" : 294,
      "bain-and-company" : 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": {
      "google" : 573,
      "facebook" : 498,
      ...
    },
    "finance": {
      "microsoft" : 294,
      "bain-and-company" : 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.

Alternative Domains

alternative_domains

Field Details

See website for how we handle domains.

Example

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

Parents and Subsidiaries

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

all_subsidiaries

🚧

Warning

This field is in beta and is subject to change.

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" : [
    "blue-sky-studios",
    "skywalker-sound",
    "industrial-light-&-magic",
    "walt-disney-animation-studios",
    "twentieth-century-fox",
    "fox-searchlight-pictures",
    "marvel-studios",
    "lucasfilm"
  ]

direct_subsidiaries

🚧

Warning

This field is in beta and is subject to change.

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" : [
    "blue-sky-studios",
    "walt-disney-animation-studios",
    "twentieth-century-fox",
    "fox-searchlight-pictures",
    "marvel-studios",
    "lucasfilm"
  ]

immediate_parent

🚧

Warning

This field is in beta and is subject to change.

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": "lucasfilm"

ultimate_parent

🚧

Warning

This field is in beta and is subject to change.

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": "the-walt-disney-studios"