Person Schema

A breakdown of the person-related fields we offer

Overview

This page details the Person Data that we provide through our Person APIs, such as Person Enrichment and Person Search.

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

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Formatting Notes

The dot notation indicates that the field is a key within an object.

For more information about data formatting, see Data Types.


Base Person Fields

These fields are available to all customers by default.

Identifiers

id

Description A unique persistent identifier for the person.
Data Type String

Field Details

The ID is a unique, persistent, and hashed value that represents a specific person. See https://docs.peopledatalabs.com/docs/persistent-ids for more information.

Example

  "id": "qEnOZ5Oh0poWnQ1luFBfVw_0000"

full_name

Description The person's full name.
Data Type String

Field Details

The first and the last name fields appended with a space.

Example

  "full_name": "sean thorne"

first_name

Description The person's first name.
Data Type String

Field Details

The person's first name.

Example

  "first_name": "sean"

middle_initial

Description The first letter of the person's middle name.
Data Type String (1 character)

Field Details

The first letter of the person's middle name.

Example

  "middle_initial": "f"

middle_name

Description The person's middle name.
Data Type String

Field Details

The person's middle name.

Example

  "middle_name": "fong"

last_initial

Description The first letter of the person's last name.
Data Type String (1 character)

Field Details

The first letter of the person's last name.

Example

  "last_initial": "t"

last_name

Description The person's last name.
Data Type String

Field Details

The person's last name.

Example

  "last_name": "thorne"

Demographics

gender

Description The person's gender.
Data Type Enum (String)

Field Details

The value will always be one of our Canonical Genders.

Example

  "gender": "male"

birth_date

Description The day the person was born.
Data Type String (Date)

Field Details

If this field exists, birth_year will agree with it.

Example

  "birth_date": "1990-12-02"

birth_year

Description The year the person was born.
Data Type Integer

Field Details

The approximated birth year associated with this person profile. If a profile has a birth_date, the birth_year field will match it.

Example

  "birth_year": 1990

Contact Information

mobile_phone

Description The person's mobile phone number.
Data Type String (Phone)

Field Details

The mobile_phone field is generated from a highly confident source of mobile phones. We've hand-validated a sample of these and seen over 90% accuracy.

Example

  "mobile_phone": "+15558675309"

phone_numbers

Description All phone numbers associated with the person.
Data Type Array [String (Phone)]

Field Details

For more detailed metadata on individual phone numbers, see the phones field in our Person Risk Attributes dataset.

Example

  "phone_numbers": [
    "+15558675309"
  ]

emails

Description Email addresses associated with the person.
Data Type Array [Object]

Field Details

Each email associated with the person will be added to this list as its own object. The Person Risk Attributes dataset will add more fields per email.

FieldData TypeDescription
addressStringThe fully parsed email address
typeEnum (String)The type of email, must be one of our Canonical Email Types

Example

  "emails": [
    {
      "address": "[email protected]",
      "type": "current_professional"
    },
    {
      "address": "[email protected]",
      "type": "personal"
    }
  ]

personal_emails

Description All personal emails associated with the person.
Data Type Array [String]

Field Details

The list of all emails tagged as type = personal.

Example

  "personal_emails": [
    "[email protected]"
  ]

work_email

Description The person's current work email.
Data Type String

Field Details

The value for this field must use valid email address formatting.

Example

  "work_email": "[email protected]"

Location

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

location_name

Description The location of the person's current address.
Data Type String

Example

  "location_name": "berkeley, california, united states"

location_locality

Description The locality of the person's current address.
Data Type String

Example

  "location_locality": "berkeley"

location_region

Description The region of the person's current address.
Data Type String

Example

  "location_region": "california"

location_metro

Description The metro of the person's current address. One of our Canonical Metros.
Data Type Enum (String)

Example

  "location_metro": "san francisco, california"

location_country

Description The country of the person's current address. One of our Canonical Countries.
Data Type Enum (String)

Example

  "location_country": "united states"

location_continent

Description The continent of the person's current address. One of our Canonical Continents.
Data Type Enum (String)

Example

  "location_continent": "north america"

location_street_address

Description The person's current street address.
Data Type String

Example

  "location_street_address": "455 fake st"

location_address_line_2

Description The person's current street address line 2.
Data Type String

Example

  "location_address_line_2": "apartment 12"

location_postal_code

Description The postal code of the person's current address.
Data Type String

Example

  "location_postal_code": "94704"

location_geo

Description The geo code of the city center of the person's current address.
Data Type String

Example

  "location_geo": "37.87,-122.27"

location_last_updated

Description The timestamp that a new data source contributed to the record for the person's current address.
Data Type String (Date)

Field Details

An update is the time when either new information is added to the record or existing information is validated.

Example

  "location_last_updated": "2018-11-05"

location_names

Description All location names associated with the person.
Data Type Array [String]

Example

  "location_names": [
    "berkeley, california, united states",
    "san francisco, california, united states"
  ]

regions

Description All regions associated with the person.
Data Type Array [String]

Example

  "regions": [
    "california, united states"
  ]

countries

Description All countries associated with the person.
Data Type Array [Enum (String)]

Example

  "countries": [
    "united states"
  ]

street_addresses

Description All street addresses associated with the person.
Data Type Array [Object]

Field Details

Each address associated with the person will be added to this list as its own object. The Person Risk Attributes dataset will add more fields per address.

For more information about each field, see Common Location Fields

Example

  "street_addresses": [
    {
      "name": "berkeley, california, united states",
      "locality": "berkeley",
      "metro": "san francisco, california",
      "region": "california",
      "country": "united states",
      "continent": "north america",
      "street_address": "455 fake st",
      "address_line_2": "apartment 12",
      "postal_code": "94704",
      "geo": "37.87,-122.27"
    }
  ]

Social Presence

We currently cover person social profiles on our Canonical Profile Networks. All profiles we've found for a person 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 person stubs (for example, linkedin.com/company), 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_url

Description The person's LinkedIn profile URL based on source agreement.
Data Type String

Example

  "linkedin_url": "linkedin.com/in/seanthorne"

linkedin_username

Description The person's LinkedIn profile username based on source agreement.
Data Type String

Example

  "linkedin_username": "seanthorne"

linkedin_id

Description The person's LinkedIn profile ID based on source agreement.
Data Type String

Example

  "linkedin_id": "145991517"

facebook_url

Description The person's Facebook profile URL based on source agreement.
Data Type String

Example

  "facebook_url": "facebook.com/deseanthorne"

facebook_username

Description The person's Facebook profile username based on source agreement.
Data Type String

Example

  "facebook_username": "deseanthorne"

facebook_id

Description The person's Facebook profile ID based on source agreement.
Data Type String

Example

  "facebook_id": "1089351304"

twitter_url

Description The person's Twitter profile URL based on source agreement.
Data Type String

Example

  "twitter_url": "twitter.com/seanthorne5"

twitter_username

Description The person's Twitter profile username based on source agreement.
Data Type String

Example

  "twitter_username": "seanthorne5"

github_url

Description The person's GitHub profile URL based on source agreement.
Data Type String

Example

  "github_url": "github.com/deseanathan_thornolotheu"

github_username

Description The person's GitHub profile username based on source agreement.
Data Type String

Example

  "github_username": "deseanathan_thornolotheu"

profiles

Description Social profiles associated with the person.
Data Type Array [Object]

Field Details

Each profile associated with the person will be added to this list as its own object. The Person Risk Attributes dataset will add more fields per social profile.

FieldData TypeDescription
urlStringThe profile URL.
idStringThe profile ID (format varies based on social network).
networkEnum (String)The social network the profile is on. Must be one of our Canonical Profile Networks.
usernameStringThe profile username.

Example

  "profiles": [
    {
      "network": "linkedin",
      "id": "145991517",
      "url": "linkedin.com/in/seanthorne",
      "username": "seanthorne"
    }
  ]

Current Job

These fields describe the person's most recent work experience.

job_title

Description The person's current job title.
Data Type String

Field Details

The person's current job title.

Example

  "job_title": "co-founder and chief executive officer"

job_title_role

Description The derived role of the person's current job title.
Data Type Enum (String)

Field Details

The value will be one of our Canonical Job Roles.

Example

  "job_title_role": "operations"

job_title_sub_role

Description The derived subrole of the person's current job title.
Data Type Enum (String)

Field Details

The value will be one of our Canonical Job Sub Roles. Each subrole maps to a role. See https://docs.peopledatalabs.com/docs/title-subroles-to-roles for a complete mapping list.

Example

  "job_title_sub_role": "logistics"

job_title_levels

Description The derived level(s) of the person's current job title.
Data Type Array [Enum (String)]

Field Details

Each level in the list will be one of our Canonical Job Title Levels.

Note: The cxo level is a catch-all for "Chief __ Officer" roles, so a CEO, CIO, CTO, etc. will all have job_title_levels: ["cxo"].

Example

  "job_title_levels": ["cxo", "owner"]

job_last_updated

Description The timestamp that a new data source contributed to the record for the person's current job.
Data Type String (Date)

Field Details

An update is the time when either new information is added to the record or existing information is validated.

Example

  "job_last_updated": "2018-11-05"

job_start_date

Description The date the person started their current job.
Data Type String (Date)

Example

  "job_start_date": "2015-03"

Current Company

These fields describe the company the person currently works at. These fields will match the corresponding values in our Company Schema and will use the same formatting and parsing logic.

job_company_id

Description The person's current company's PDL ID.
Data Type String

Example

  "job_company_id": "peopledatalabs"

job_company_name

Description The person's current company's name.
Data Type String

Example

  "job_company_name": "people data labs"

job_company_website

Description The person's current company's website.
Data Type String

Example

  "job_company_website": "peopledatalabs.com"

job_company_size

Description The person's current company's size range.
Data Type Enum (String)

Example

  "job_company_size": "51-200"

job_company_founded

Description The person's current company's founding year.
Data Type Integer (> 0)

Example

  "job_company_founded": 2015

job_company_industry

Description The person's current company's industry.
Data Type Enum (String)

Example

  "job_company_industry": "computer software"

job_company_linkedin_url

Description The person's current company's LinkedIn URL.
Data Type String

Example

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

job_company_linkedin_id

Description The person's current company's LinkedIn ID.
Data Type String

Example

  "job_company_linkedin_id": "18170482"

job_company_facebook_url

Description The person's current company's Facebook URL.
Data Type String

Example

  "job_company_facebook_url": "facebook.com/peopledatalabs"

job_company_twitter_url

Description The person's current company's Twitter URL.
Data Type String

Example

  "job_company_twitter_url": "twitter.com/peopledatalabs"

job_company_location_name

Description The person's current company's headquarters' location name.
Data Type String

Example

  "job_company_location_name": "san francisco, california, united states"

job_company_location_locality

Description The person's current company's headquarters' locality.
Data Type String

Example

  "job_company_location_locality": "san francisco"

job_company_location_region

Description The person's current company's headquarters' region.
Data Type String

Example

  "job_company_location_region": "california"

job_company_location_metro

Description The person's current company's headquarters' metro area.
Data Type Enum (String)

Example

  "job_company_location_metro": "san francisco, california"

job_company_location_country

Description The person's current company's headquarters' country.
Data Type Enum (String)

Example

  "job_company_location_country": "united states"

job_company_location_continent

Description The person's current company's headquarters' continent.
Data Type Enum (String)

Example

  "job_company_location_continent": "north america"

job_company_location_street_address

Description The person's current company's headquarters' street address.
Data Type String

Example

  "job_company_location_street_address": "455 market st"

job_company_location_address_line_2

Description The person's current company's headquarters' street address line 2.
Data Type String

Example

  "job_company_location_address_line_2": "suite 1670"

job_company_location_postal_code

Description The person's current company's headquarters' postal code.
Data Type String

Example

  "job_company_location_postal_code": "94105"

job_company_location_geo

Description The person's current company's headquarters' city-center geographic coordinates.
Data Type String

Example

  "job_company_location_geo": "37.77,-122.41"

Work History

industry

Description The most relevant industry for this person based on their work history.
Data Type Enum (String)

Field Details

A person's industry is determined based on their tagged personal industries and the industries of the companies that they have worked for.

The value will be one of our Canonical Industries.

Example

  "industry": "computer software"

interests

Description The person's self-reported interests.
Data Type Array [String]

Field Details

Each interest is cleaned (lowercased, stripped of whitespace, etc.). We don't have a finite lists of interests but we remove profanity, etc.

Example

  "interests": [
    "data"
  ]

skills

Description The person's self-reported skills.
Data Type Array [String]

Field Details

Each skill is cleaned (lowercased, stripped of whitespace, etc.). We do not always strip punctuation because it can be relevant for some skills (ex: "c++" vs "c").

We do not do any canonicalization, so "java" and "java 8.0" are considered separate skills. For this reason, we encourage our customers to use fuzzy text matching with the skills field.

The Skill Enrichment API can help find similar skills.

Example

  "skills": [
    "entrepreneurship"
  ]

experience

Description The person's work experience.
Data Type Array [Object]

Field Details

The order of work experience in the list is determined by recency and associativity. The experience object that is tagged as experience.is_primary = True is copied over to the flattened job_ fields (see Current Job and Current Company).

The Person Risk Attributes dataset will add more fields per work experience.

Each work experience object contains the following fields:

FieldData TypeDescription
companyObjectThe company where the person worked.
location_namesArray [String]Locations where the person has worked while with this company (if different from the company HQ).
end_dateString (Date)The date the person left the company. If the person is still working for the company, will be null.
start_dateString (Date)The date the person started at the company.
titleObjectThe person's job title while at the company.
is_primaryBooleanWhether this is the person's current job or not. If true, this experience will be used to populate the job_ fields.
experience.company

The fields in experience.company map to the corresponding fields in our Company Schema. The same parsing and formatting logic apply.

FieldSub FieldData TypeDescription
nameStringThe company name, cleaned and standardized.
sizeEnum (String)The self-reported company size range. Must be one of our Canonical Company Sizes.
idStringThe company's PDL ID
foundedInteger (> 0)The founding year of the company.
industryEnum (String)The self-identified industry of the company. Must be one of the Canonical Industries.
locationObjectThe location of the company's headquarters. See Common Location Fields for detailed field descriptions.
nameString
localityString
regionString
metroEnum (String)
countryEnum (String)
continentEnum (String)
street_addressString
address_line_2String
postal_codeString
geoString
linkedin_urlStringThe company's LinkedIn URL
linkedin_idStringThe company's LinkedIn ID
facebook_urlStringThe company's Facebook URL
twitter_urlStringThe company's Twitter URL
websiteStringThe company's primary website, cleaned and standardized.
experience.title

See Current Job for more details on the specific fields.

FieldData TypeDescription
nameStringThe cleaned job title.
roleEnum (String)One of the Canonical Job Roles.
sub_roleEnum (String)One of the Canonical Job Sub Roles.
levelsArray [Enum (String)]Canonical Job Title Levels.

Example

  "experience": [
    {
      "company": {
        "name": "people data labs",
        "size": "11-50",
        "id": "peopledatalabs",
        "founded": 2015,
        "industry": "computer software",
        "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"
        },
        "linkedin_url": "linkedin.com/company/peopledatalabs",
        "linkedin_id": "18170482",
        "facebook_url": "facebook.com/peopledatalabs",
        "twitter_url": "twitter.com/peopledatalabs",
        "website": "peopledatalabs.com"
      },
      "location_names": ["san francisco, california, united states"],
      "end_date": null,
      "start_date": "2015-03",
      "title": {
        "name": "chief executive officer and co-founder",
        "role": "operations",
        "sub_role": "logistics",
        "levels": ["cxo", "owner"]
      },
      "is_primary": true
    },
  ]

Education

education

Description The person's education information.
Data Type Array [Object]

Field Details

The education objects associated with this person profile, which, when output in CSV format, have indexing based on recency and associativity.

Each education object in the list will include the following data:

FieldData TypeDescription
schoolObjectThe school the person attended.
end_dateString (Date)The date the person left the school. If the person is still at the school, will be null.
start_dateString (Date)The date the person started at the school.
gpaFloatThe GPA the person earned at the school.
degreesArray [Enum (String)]The degrees the person earned at the school. All values will be Canonical Education Degrees
majorsArray [Enum (String)]All majors earned at the school. All values will be Canonical Education Majors.
minorsArray [Enum (String)]All minors earned at the school. All values will be Canonical Education Majors.
education.school

To tap into our school matching logic, use our School Cleaner API to retrieve possible school values.

FieldSub FieldData TypeDescription
nameStringThe name of the school.
typeEnum (String)The school type. Will be one of our Canonical School Types.
idStringThe NON-PERSISTENT ID for the school in our records.
locationObjectThe location of the school. See Common Location Fields for detailed field descriptions.
nameString
localityString
regionString
countryEnum (String)
continentEnum (String)
linkedin_urlStringThe school's LinkedIn URL
linkedin_idStringThe school's LinkedIn ID
facebook_urlStringThe school's Facebook URL
twitter_urlStringThe school's Twitter URL
websiteStringThe website URL associated with the school, which could include subdomains.
domainStringThe primary website domain associated with the school.

Example

  "education": [
    {
      "school": {
        "name": "university of oregon",
        "type": "post-secondary institution",
        "id": "64LkgfdwWYkCC2TjbldMDQ_0",
        "location": {
          "name": "eugene, oregon, united states",
          "locality": "eugene",
          "region": "oregon",
          "country": "united states",
          "continent": "north america"
        },
        "linkedin_url": "linkedin.com/school/university-of-oregon",
        "linkedin_id": "19207",
        "facebook_url": "facebook.com/universityoforegon",
        "twitter_url": "twitter.com/uoregon",
        "website": "uoregon.edu",
        "domain": "uoregon.edu"
      },
      "end_date": "2014",
      "start_date": "2010",
      "gpa": null,
      "degrees": [],
      "majors": [
        "entrepreneurship"
      ],
      "minors": []
    },
  ]

Metadata

operation_id

Description An identifier for an operation in a Data Licsense delivery, used for troubleshooting.
Data Type String

Field Details

A value that exists only in Data License deliveries, which allows PDL employees to identify the timestamp and operations performed on the internal data in order to return a record in a delivery.

Example

  "operation_id": "acee3bde2e1a2cb7e75c57b80d5b7bc2d5de5b02e7ea51f91304c28df77251dc"

dataset_version

Description The major or minor release number.
Data Type String

Field Details

This field currently exists in Person Enrichment API responses only.

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

Example

  "dataset_version": "19.2"

version_status

❗️

DEPRECATION NOTICE

This object has been deprecated in API responses.

Description Metadata about the version of the dataset used to retrieve this record.
Data Type Object

Field Details

This object tracks the pervious and current dataset version, and any other persistent IDs that were merged into this record using improved entity resolution and the status of the record.

FieldData TypeDescription
containsArray [String]The list of IDs that have been merged into this record since the last release.
current_versionStringThe current data version.
previous_versionStringThe previous data version.
statusEnum (String)The changes made to this record between the previous release and the current one. One of our Canonical Version Statuses.

Example

  "version_status": {
    "contains": [
      "qEnOZ5Oh0poWnQ1luFBfVw_0000"
    ],
    "current_version": "15",
    "previous_version": "14",
    "status": "updated"
  }


Person Risk Attributes

These are premium identity-risk-related fields with enhanced tracking and sourcing information.

Additional Subfields

FieldData TypeDescription
first_seenString (Date)The date that this entity was first associated with the Person record.
last_seenString (Date)The date that this entity was last associated with the Person record.
num_sourcesInteger (> 0)The number of sources that have contributed to the association of this entity with the Person record.

The subfields are available for every record in the following fields:

Example

  "profiles // emails // experience // street_addresses": [
    {
      ...
      "first_seen": "2017-06-02",
      "last_seen": "2019-07-18",
      "num_sources": 17
    }
  ]

Contact Information

phones

Description The list of phone numbers associated with this record.
Data Type Array [Object]

Field Details

Each phone number object in this list will contain the following information.

FieldData TypeDescription
numberString (Phone)The phone number.
first_seenString (Date)The date that this number was first associated with this record.
last_seenString (Date)The date that this number was last associated with this record.
num_sourcesInteger (> 0)The number of sources that have contributed to the association of this profile with this record.

Example

  "phones": [
    {
      "number": "+15558675309",
      "first_seen": "2017-06-02",
      "last_seen": "2019-07-18",
      "num_sources": 17   
    }
  ]

linkedin_connections

Description The number of LinkedIn connections the person has.
Data Type Integer (>= 0)

Field Details

Typically between 0-500.

Example

  "linkedin_connections": 432

facebook_friends

Description The number of Facebook friends the person has.
Data Type Integer (>= 0)

Example

  "facebook_friends": 3912

name_aliases

Description Any other names the person goes by.
Data Type Array [String]

Field Details

Any associated names or aliases besides the primary one used in the full_name field.

Example

  "name_aliases": [
    "andrew nichol",
    "r andrew nichol",
    "robert nichol"
  ]

Lower Confidence Data

PDL values high confidence data that is very likely to be associated with a person. The data in these fields have lower confidence than the data used in other fields.

possible_emails

Description Email addresses associated with this person that have a lower level of confidence.
Data Type Array [Object]

Field Details

This field uses the same format as the emails field, including first_seen, last_seen, and num_sources.

Example

  "possible_emails": [
    {
      "address": "[email protected]",
      "type": null,
      "first_seen": "2021-06-13",
      "last_seen": "2021-06-13",
      "num_sources": 2
    }
  ]

possible_phones

Description Phone numbers associated with this person that have a lower level of confidence.
Data Type Array [Object]

Field Details

This field uses the same format as the phones field, including first_seen, last_seen, and num_sources.

Example

  "possible_phones": [
    {
      "number": "+15558675309",
      "first_seen": "2021-06-13",
      "last_seen": "2021-06-13",
      "num_sources": 2
    }
  ]    

possible_profiles

Description Social profiles associated with this person that have a lower level of confidence.
Data Type Array [Object]

Field Details

This field uses the same format as the profiles field, including first_seen, last_seen, and num_sources.

Example

  "possible_profiles": [
    {
      "network": "linkedin",
      "id": "145991517",
      "url": "linkedin.com/in/seanthorne",
      "username": "seanthorne",
      "first_seen": "2021-06-13",
      "last_seen": "2021-06-13",
      "num_sources": 2
    }
  ]

possible_street_addresses

Description Addresses associated with this person that have a lower level of confidence.
Data Type Array [Object]

Field Details

This field uses the same format as the street_addresses field, including first_seen, last_seen, and num_sources.

Example

  "possible_street_addresses": [
    {
      "name": "berkeley, california, united states",
      "locality": "berkeley",
      "metro": "san francisco, california",
      "region": "california",
      "country": "united states",
      "continent": "north america",
      "street_address": "455 fake st",
      "address_line_2": "apartment 12",
      "postal_code": "94704",
      "geo": "37.87,-122.27",
      "first_seen": "2021-06-13",
      "last_seen": "2021-06-13",
      "num_sources": 2
    }
  ]

possible_birth_dates

Description Birthdays associated with this person that have a lower level of confidence.
Data Type Array [String (Date)]

Field Details

The dates in this field use the same format as the birth_date field.

Example

  "possible_birth_dates": [
    "1991-05-26",
    "1992-05-26"
  ]

possible_location_names

Description Locations associated with this person that have a lower level of confidence.
Data Type Array [String]

Field Details

This field uses the same format as the location_names field.

Possible locations are inferred based on phone area codes, university location, and other associations.

Example

  "possible_location_names": [
    "berkeley, california, united states",
    "san francisco, california, united states"
  ]

Job History

job_history

Description Any additional professional positions associated with this person.
Data Type Array [Object]

Field Details

Any additional job history information PDL has that is not included in the experience field.

Usually these are positions that have been removed or changed on resumes.

FieldData TypeDescription
company_idStringPDL Company ID
company_nameStringCompany Name
titleStringJob Title
first_seenString (Date)The date that this experience was first associated with this record.
last_seenString (Date)The date that this experience was last associated with this record.
num_sourcesInteger (> 0)The number of sources that have contributed to the association of this profile with this record.

Example

  "job_history": [
    {
      "company_id": "auntie-annes",
      "company_name": "auntie annes",
      "title": "food service supervisor",
      "first_seen": "2016-05-17",
      "last_seen": "2020-05-30",
      "num_sources": 12
    }
  ]

PDL Record Information

num_records

Description The number of unique raw records contributing to this specific PDL profile.
Data Type Integer (> 0)

Example

  "num_records": 420

num_sources

Description The number of unique sources contributing to this specific PDL profile.
Data Type Integer (> 0)

Example

  "num_sources": 72

first_seen

Description The date when this record was first created in our data.
Data Type String (Date)

Example

  "first_seen": "2017-06-02"


Premium Resume Fields

These are premium resume-related fields.

Raw Input

These fields contain the raw input used in other fields.

education.raw

Description Raw education data.
Data Type String

Field Details

Raw education data that was parsed into the degrees, majors, and minors fields in the education object.

Example

  "education": [
    {
      ...
      "raw": "bachelors of arts in entrepreneurship, business minor"
    }
  ]

education.school.raw

Description Raw school name.
Data Type String

Field Details

Raw school name used to populate the education.school object.

Example

  "education": [
    {
      "school": {
        ...
        "raw": "university of oregon"  
      }
    }
  ]

experience.company.raw

Description Raw company name.
Data Type Array [String]

Field Details

Raw company name(s) used to populate the experience.company object.

Example

  "experience": [
    {
      "company": {
        ...
        "raw": [
          "hallspot",
          "hallspot, inc"
        ]
      }
    }
  ]

experience.title.raw

Description Raw job title input.
Data Type Array [String]

Field Details

The lower cased job title raw input from our data sources used to populate the experience.title object.

Example

  "experience": [
    {
      "title": {
        ...
        "raw": [
          "chief executive officer and co-founder"
        ]
      }
    }
  ]

Summaries

These fields contain the user-inputted summaries for their experiences.

education.summary

Description User-inputted summary of their education.
Data Type String

Field Details

The summary is lowercased, but otherwise kept as-is from the raw source.

Example

  "education": [
    {
      ...
      "summary": "when i was at oregon i volunteered at a local homeless shelter 3 days a week"
    }
  ]

experience.summary

Description User-inputted summary of their work experience.
Data Type String

Field Details

The summary is lowercased, but otherwise kept as-is from the raw source.

Example

  "experience": [
    {
      ...
      "summary": "worked on the \"search analytics\" team to understand our users better"
    }
  ]

job_summary

Description User-inputted summary of their current job.
Data Type String

Field Details

The summary is lowercased, but otherwise kept as-is from the raw source.

Example

  "job_summary": "worked on the \"search analytics\" team to understand our users better"

summary

Description User-inputted personal summary.
Data Type String

Field Details

The self-written summary tied to the person profile (often a LinkedIn summary.)

The summary is lowercased, but otherwise kept as-is from the raw source.

Example

  "summary": "growth-hacker and digital nomad"

Certifications & Languages

certifications

Description Any certifications the person has.
Data Type Array [Object]

Field Details

The certifications listed here are based on user input, we do not verify them.

FieldData TypeDescription
nameStringCertification name
organizationStringThe organization awarding the certification.
start_dateString (Date)The date the certification was awarded.
end_dateString (Date)The expiration date of the certification.

Example

  "certifications": [
    {
      "name": "machine learning certification",
      "organization": "coursera",
      "start_date": "2022-03",
      "end_date": "2023-04"
    }
  ]

languages

Description Languages the person knows.
Data Type Array [Object]

Field Details

The languages listed here are based on user input, we do not verify them.

FieldData TypeDescription
nameEnum (String)The language. Must be one of our Canonical Languages.
proficiencyEnum (Integer)Self-ranked language proficiency from 1 (limited) to 5 (fluent).

Example

  "languages": [
    {
      "name": "english",
      "proficiency": 5
    }
  ]

Company Stock Information

experience.company.ticker

Description The company ticker.
Data Type String

Field Details

Corresponds to the Company Data ticker field.

Example

  "experience": [
    {
      "company": {
        ...
        "ticker": "goog"
      }
    }
  ]

experience.company.type

Description The company type.
Data Type Enum (String)

Field Details

Must be one of our Canonical Company Types. Corresponds to the Company Data type field.

Example

  "experience": [
    {
      "company": {
        ...
        "type": "public"
      }
    }
  ]

job_company_ticker

Description The company ticker for the person's current job.
Data Type String

Field Details

Corresponds to the Company Data ticker field.

Example

  "job_company_ticker": "goog"

job_company_type

Description The company type for the person's current job.
Data Type Enum (String)

Field Details

Must be one of our Canonical Company Types. Corresponds to the Company Data type field.

Example

  "job_company_type": "public"

O*NET Code

job_onet_code

Description The 8-digit O*NET code for the person’s current job title.
Data Type String

Field Details

The 8-digit O*NET code for the person’s current job title, following the 2018 SOC guidelines.

Example

  "job_onet_code": "11-1011.00"

job_onet_major_group

Description The O*NET Major Group associated with the person’s current job title.
Data Type String

Example

  "job_onet_major_group": "Management Occupations"

job_onet_minor_group

Description The O*NET Minor Group associated with the person’s current job title.
Data Type String

Example

  "job_onet_minor_group": "Top Executives"

job_onet_broad_occupation

Description The O*NET Broad Occupation associated with the person’s current job title.
Data Type String

Example

  "job_onet_broad_occupation": "Chief Executives"

job_onet_specific_occupation

Description The O*NET Specific Occupation associated with the person’s current job title.
Data Type String

Example

  "job_onet_specific_occupation": "Chief Executives"

job_onet_specific_occupation_detail

Description A more detailed job title classification than O*NET Specific Occupation.
Data Type String

Field Details

A more detailed job title for records where the specific occupation within O*NET's standard hierarchy isn't granular enough to accurately describe the job title.

For example, the highest level of granularity in O*NET for C-suite positions is Chief Executives. With this field, we can specify the type of executive role.

Example

  "job_onet_specific_occupation_detail": "Chief Technology Officer"

Inferred & Calculated Values

inferred_salary

Description The inferred salary range (USD) for the person's current job.
Data Type Enum (String)

Field Details

Must be one of our Canonical Inferred Salary Ranges.

Example

  "inferred_salary": "70,000-85,000"

inferred_years_experience

Description The person's inferred years of total work experience.
Data Type Integer (0 - 100)

Field Details

The value will be between 0 and 100.

Example

  "inferred_years_experience": 7

recommended_personal_email

Description The best available email to reach a person.
Data Type String

Field Details

This field is generated by analyzing the all of a person's emails in the personal_emails list to identify the best available email.

Through testing, we’ve found that using the email identified in recommended_personal_email versus selecting a random email address from personal_emails resulted in ~33% higher deliverability.

Example

  "recommended_personal_email": "[email protected]"