Overview
This page contains a listing of all the fields contained in the Company Dataset. Fields are broken out into the following sections:- 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.
Base Company Fields
Formatting NotesThe dot notation indicates that the property is one level deep inside a hash. If a field is not present then we’ll return an empty list or null value for that field.
| Field Name | Field Type | Persistence Commitments and Format | Short Description | Example |
|---|---|---|---|---|
name | String | The company’s main common name | people data labs | |
size | Enum (String) | Canonical Company Sizes | A self-reported range representing the number of people working at the company. For the “true” number of employees, use the employee_count field. | 11-50 |
employee_count | Integer | Greater than 0 | The current integer number of employees working at the company based on number of PDL profiles. For the company’s self-reported size range, use the size field. | 78 |
id | String | PDL company ID. This is currently non-persistent and generated from the company’s primary linkedin username | peopledatalabs | |
founded | Integer | Greater than 0 | The founded year of the company | 2015 |
industry | Enum (String) | Canonical Industries | Self reported industry — the enum is from linkedin’s standard industries | computer software |
naics | Object | An object containing the NAICS industry information associated with a company | ||
naics.naics_code | String | The NAICS code associated with a company’s industry classification | “111110” | |
naics.sector | String | The NAICS sector associated with a company’s industry classification | “agriculture, forestry, fishing and hunting” | |
naics.sub_sector | String | The NAICS subsector associated with a company’s industry classification | “crop production” | |
naics.industry_group | String | The NAICS industry group associated with a company’s industry classification | “oilseed and grain farming” | |
naics.naics_industry | String | The NAICS industry associated with a company’s industry classification | “soybean farming” | |
naics.national_industry | String | The NAICS national industry associated with a company’s industry classification | “soybean farming” | |
sic | Object | An object containing the SIC industry information associated with a company | ||
sic.sic_code | String | The SIC industry code associated with a company’s industry classification | “5731” | |
sic.major_group | String | The SIC major group associated with a company’s industry classification | “agricultural production - crops” | |
sic.industry_group | String | The SIC industry group associated with a company’s industry classification | “cash grains” | |
sic.industry_sector | String | The SIC industry sector associated with a company’s industry classification | “soybeans” | |
location.address_line_2 | String | The company’s current HQ address line 2 | suite 1670 | |
location.continent | Enum (String) | Canonical Countries | The company’s current HQ continent | north america |
location.country | Enum (String) | Canonical Continents | The company’s current HQ country | united states |
location.geo | String | The company’s current HQ city-level Geo | 37.77,-122.41 | |
location.locality | String | The company’s current HQ locality | san francisco | |
location.metro | Enum (String) | Canonical Metros | The company’s current HQ metro (US only) | san francisco, california |
location.name | String | The company’s current HQ location name, generated from our canonical location data with the format locality, region, country | san francisco, california, united states | |
location.postal_code | String | The company’s current HQ postal code | 94105 | |
location.region | String | The company’s current HQ region | california | |
location.street_address | String | The company’s current HQ street address | 455 market st | |
linkedin_id | String | Primary company linkedin ID | 18170482 | |
linkedin_url | String | Primary company linkedin url | linkedin.com/company/peopledatalabs | |
facebook_url | String | Primary company facebook | facebook.com/peopledatalabs | |
twitter_url | String | Primary company twitter url | twitter.com/peopledatalabs | |
profiles | Array (String) | A list of all profiles associated with the company | [“linkedin.com/company/peopledatalabs”,“linkedin.com/company/18170482”,“facebook.com/peopledatalabs”,“crunchbase.com/organization/talentiq”] | |
website | String | Primary company website | peopledatalabs.com | |
ticker | String | Free Text Field, capitalized | Company Ticker, (only for public companies) | MOO |
type | Enum (String) | Canonical Company Types | The type of the company | private |
summary | String | Free text field | Company description | people data labs builds people data. use 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. we 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 | Array (String) | Tags associated with the company | [“data”, “daas”, “enrichment api”] | |
headline | String | Free text field | The company’s “headline” summary | your single source of truth |
alternative_names | Array (String) | The list of names associated with this company filtered to ensure data quality | [“people data labs”, “people data labs inc”, “talentiq”] | |
affiliated_profiles | Array (String) | A list of company IDs that PDL has flagged as being affiliated and having an association to this company (either parent or child) | [“engagio”, “demandbase”] |
Company Insights Fields
Formatting NotesThe dot notation indicates that the property is one level deep inside a hash. If a field is not present then we’ll return an empty list or null value for that field.
| Field Name | Field Type | Persistence Commitments and Format | Short Description | Example |
|---|---|---|---|---|
employee_growth_rate.3_month | Float | The percentage increase in total headcount from 3 months prior. A value of 1.0 represents a 100% increase in headcount (i.e. doubling headcount). | 0.0595 | |
employee_growth_rate.6_month | Float | The percentage increase in total headcount from 6 months prior. A value of 1.0 represents a 100% increase in headcount (i.e. doubling headcount). | 0.0723 | |
employee_growth_rate.12_month | Float | The percentage increase in total headcount from 12 months prior. A value of 1.0 represents a 100% increase in headcount (i.e. doubling headcount). | 0.8542 | |
employee_growth_rate.24_month | Float | The percentage increase in total headcount from 24 months prior. A value of 1.0 represents a 100% increase in headcount (i.e. doubling headcount). | 1.4722 | |
employee_churn_rate.3_month | Float | The number of employees that departed the company over the last 3 month period divided by the current number of employees. A value of 1.0 means that as many people have left as remain (e.g. 200 employees joined and 100 departed, with a current headcount of 100). | 0.015 | |
employee_churn_rate.6_month | Float | The number of employees that departed the company over the last 6 month period divided by the current number of employees. A value of 1.0 means that as many people have left as remain (e.g. 200 employees joined and 100 departed, with a current headcount of 100). | 0.02 | |
employee_churn_rate.12_month | Float | The number of employees that departed the company over the last 12 month period divided by the current number of employees. A value of 1.0 means that as many people have left as remain (e.g. 200 employees joined and 100 departed, with a current headcount of 100). | 0.035 | |
employee_churn_rate.24_month | Float | The number of employees that departed the company over the last 24 month period divided by the current number of employees. A value of 1.0 means that as many people have left as remain (e.g. 200 employees joined and 100 departed, with a current headcount of 100). | 0.155 | |
avg_employee_tenure | Float | Average years of experience at the company, summarized for all employees | 1.476 | |
avg_tenure_by_role | Object | Average years of experience at the company, broken out by job role | {”real_estate”: 0.0, “design”: 0.583, “trades”: 0.0, “marketing”: 1.292, “education”: 4.083, “legal”: 0.0, “customer_service”: 0.906, “finance”: 2.312, “public_relations”: 0.0, “engineering”: 1.705, “human_resources”: 0.633, “media”: 0.875, “sales”: 0.631, “operations”: 0.676, “health”: 0.0 } | |
avg_tenure_by_level | Object | Average years of experience at the company, broken out by job level | {”entry”: 0.0, “unpaid”: 0.0, “senior”: 1.03, “director”: 1.62, “vp”: 2.319, “training”: 0.778, “manager”: 0.866, “owner”: 7.0, “partner”: 0.167, “cxo”: 2.75 } | |
employee_count_by_country | Object | The number of current employees broken out by country. See canonical countries for the enumerated list of possible countries in this object. | ”employee_count_by_country”: {<br />"united states": 67,<br />"canada": 2,<br />"india": 1,<br />"bangladesh": 1<br />} | |
top_us_employee_metros | Object | The top US locations where current employees are located | ||
employee_count_by_month | Object | The total number of profiles tied to this company at the end of each month. The date range begins at the start date of the first associated employee or January 1, 2010 - whichever is most recent. | {"2021-07": 84,"2021-08": 86,"2021-09": 84} | |
gross_additions_by_month | Object | The total number of profiles that joined the company each month. | {"2021-07": 4,"2021-08": 6,"2021-09": 2} | |
gross_departures_by_month | Object | The total number of profiles that left the company each month. | {"2021-07": 3,"2021-08": 4,"2021-09": 2} | |
employee_count_by_month_by_role | Object | The number of profiles tied to this company each month, broken down by job_role. | ”2021-09”: {"real_estate": 0,"design": 2,"trades": 0,"marketing": 3,"education": 1,"legal": 0,"customer_service": 9,"finance": 2,"public_relations": 0,"engineering": 23,"human_resources": 1,"media": 1,"sales": 11,"operations": 7,"health": 0} | |
employee_count_by_month_by_level | Object | The number of profiles tied to this company each month, broken down by job_level. | ”2021-09”: {"entry": 0,"unpaid": 0,"senior": 7,"director": 15,"vp": 7,"training": 0,"manager": 25,"owner": 2,"partner": 0,"cxo": 4} | |
recent_exec_hires | Object | The number of CXOs, owners and VPs that have joined the company in the previous 3 months. | ”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"]}] | |
recent_exec_departures | Object | The number of CXOs, owners, and VPs that have left the company in the previous 3 months. | ”recent_exec_departures”: [{"departed_date": "2021-08","pdl_id": "99abcY0KYvPsx11Detgtqw_0000","job_title": "senior software engineer","job_title_role": "engineering","job_title_sub_role": "software","job_title_levels": ["senior"],"new_company_id": peopledatalabs,"new_company_job_title": "vice president of engineering","new_company_job_role": "engineering","new_company_job_sub_role": null,"new_company_job_levels":["vp"]}] | |
top_previous_employers_by_role | Object | The top 10 previous employers broken down by job role and ranked by number of current employees previously employed there. | ”engineering”: {"us-army": 3,"urban-robotics-inc.": 2,"dark-horse-comics": 3,"intel-corporation": 2,"best-buy": 3,"university-of-houston": 2,"the-active-network": 2,"vervegroup": 2,"tourmaline-labs-inc-": 2,"creativedrive": 2} | |
top_next_employers_by_role | Object | The top 10 next employers broken down by job role and ranked by number of previous employees currently employed there. | ”finance”: {"morgan-stanley": 2,"coatue-management": 2,"vfaseattle": 1,"virgin-america": 1,"popsugar": 1,"conversica": 1,"amazon": 1,} |
Premium Company Fields
Formatting NotesThe dot notation indicates that the property is one level deep inside a hash. If a field is not present then we’ll return an empty list or null value for that field.
| Field Name | Field Type | Persistence Commitments and Format | Short Description | Example |
|---|---|---|---|---|
ultimate_parent | Object | Beta field, subject to change | The ultimate organizational entity that owns this company | |
immediate_parent | Object | Beta field, subject to change | The organizational entity that directly owns this company | |
direct_subsidiaries | Array (Object) | Beta field, subject to change | The organizational entities that this company directly owns | |
all_subsidiaries | Array (Object) | Beta field, subject to change | The full set of organizational entities owned by this company and every company owned by this company | |
alternative_domains | Array (String) | The list of alternate domains associated with this company. | [“peopledatalabs.com”, “talentiq.co”, “peopledatalabs.co”] |