Quickstart

Overview

This quickstart is a brief introduction to our data and APIs. Don’t worry if you’ve never used an API before, with a little copy-paste magic we’ll get you up and running in no time. In fact, in just a few minutes, you will be pulling down and accessing real person and company data directly from our datasets!

Here’s what we’ll cover:

  1. Creating an account (and getting your free API key)
  2. Lookup a Person Profile using our Person Enrichment API
  3. Lookup a Company Profile using our Company Enrichment API

Now let’s get started!


Create an Account

In order to access our data, you will need an API key. You can get your API key by creating a free account at www.peopledatalabs.com/signup.

Note that this is your secret API key so take care to keep it private. You can always regenerate a new API key from the dashboard in case you need to.

For more information on signing up for an API key and setting up package access, see our Self-Signup API Quickstart guide.


Lookup a Person Profile using the Person Enrichment API

Once you have your API key, let's start by looking up a person profile from our Person Dataset using the Person Enrichment API.

Here’s a cURL command that you can copy and paste into your terminal:

📘

Before Running the Command:

Replace the XXXX with your API key (between the double-quotes) and hit enter to run your command.

API_KEY=”XXXX”
curl "https://api.peopledatalabs.com/v5/person/enrich?api_key=${API_KEY}&pretty=True&profile=linkedin.com/in/seanthorne"

Here’s what happens when we run this command:

  • We send a request via cURL command for the profile associated with the following linkedin account: linkedin.com/in/seanthorne
  • The Person Enrichment API finds the best matching profile record in our Person Dataset
  • The profile record is returned to us in the API response (with a 200 status since a record was successfully found)

The result of the command should be the following profile record:

{
  "status": 200,
  "likelihood": 10,
  "data": {
    "id": "qEnOZ5Oh0poWnQ1luFBfVw_0000",
    "full_name": "sean thorne",
    "first_name": "sean",
    "middle_initial": "f",
    "middle_name": "fong",
    "last_name": "thorne",
    "gender": "male",
    "birth_year": "1990",
    "birth_date": null,
    "linkedin_url": "linkedin.com/in/seanthorne",
    "linkedin_username": "seanthorne",
    "linkedin_id": "145991517",
    "facebook_url": "facebook.com/deseanthorne",
    "facebook_username": "deseanthorne",
    "facebook_id": "1089351304",
    "twitter_url": "twitter.com/seanthorne5",
    "twitter_username": "seanthorne5",
    "github_url": null,
    "github_username": null,
    "work_email": "[email protected]",
    "personal_emails": [
      "[email protected]"
    ],
    "mobile_phone": "+14155688415",
    "industry": "computer software",
    "job_title": "co-founder and chief executive officer",
    "job_title_role": null,
    "job_title_sub_role": null,
    "job_title_levels": [
      "owner",
      "cxo"
    ],
    "job_company_id": "peopledatalabs",
    "job_company_name": "people data labs",
    "job_company_website": "peopledatalabs.com",
    "job_company_size": "11-50",
    "job_company_founded": "2015",
    "job_company_industry": "computer software",
    "job_company_linkedin_url": "linkedin.com/company/peopledatalabs",
    "job_company_linkedin_id": "18170482",
    "job_company_facebook_url": "facebook.com/peopledatalabs",
    "job_company_twitter_url": "twitter.com/peopledatalabs",
    "job_company_type": "private",
    "job_company_ticker": null,
    "job_company_location_name": "san francisco, california, united states",
    "job_company_location_locality": "san francisco",
    "job_company_location_metro": "san francisco, california",
    "job_company_location_region": "california",
    "job_company_location_geo": "37.77,-122.41",
    "job_company_location_street_address": "455 market street",
    "job_company_location_address_line_2": "suite 1670",
    "job_company_location_postal_code": "94105",
    "job_company_location_country": "united states",
    "job_company_location_continent": "north america",
    "job_last_updated": "2021-06-01",
    "job_start_date": "2015-03",
    "job_summary": "People Data Labs builds people data. Leverage our dataset of 1.5 billion unique person profiles as your data foundation to build products, enrich person profiles, power predictive modeling/AI, analysis, and more. We build and maintain our data from our powerful Data Union. 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. Backed by Founders Fund. I consult with our engineering customers to solve people data building challenges - [email protected]",
    "location_name": "san francisco, california, united states",
    "location_locality": "san francisco",
    "location_metro": "san francisco, california",
    "location_region": "california",
    "location_country": "united states",
    "location_continent": "north america",
    "location_street_address": null,
    "location_address_line_2": null,
    "location_postal_code": null,
    "location_geo": "37.77,-122.41",
    "location_last_updated": "2021-06-01",
    "linkedin_connections": 9684,
    "inferred_salary": ">250,000",
    "inferred_years_experience": 9,
    "summary": "Interested in solving the hardest problems the enterprise is facing.",
    "phone_numbers": [
      "+14155688415",
      "+18603784097",
      "+15038301033"
    ],
    "emails": [
      {
        "address": "[email protected]",
        "type": null
      },
      {
        "address": "[email protected]",
        "type": "professional"
      },
      {
        "address": "[email protected]",
        "type": "professional"
      },
      {
        "address": "[email protected]",
        "type": "professional"
      },
      {
        "address": "[email protected]",
        "type": "personal"
      },
      {
        "address": "[email protected]",
        "type": null
      },
      {
        "address": "[email protected]",
        "type": "current_professional"
      },
      {
        "address": "[email protected]",
        "type": "current_professional"
      },
      {
        "address": "[email protected]",
        "type": "current_professional"
      }
    ],
    "possible_emails": [
      {
        "address": "[email protected]",
        "type": "professional"
      }
    ],
    "interests": [
      "location based services",
      "mobile",
      "social media",
      "colleges",
      "university students",
      "consumer internet",
      "college campuses"
    ],
    "skills": [
      "entrepreneurship",
      "start ups",
      "management",
      "public speaking",
      "strategic partnerships",
      "strategy",
      "fundraising",
      "saas",
      "enterprise technology sales",
      "social networking"
    ],
    "location_names": [
      "san francisco, california, united states",
      "albany, california, united states",
      "portland, oregon, united states"
    ],
    "regions": [
      "california, united states",
      "oregon, united states"
    ],
    "countries": [
      "united states"
    ],
    "street_addresses": [],
    "experience": [
      {
        "company": {
          "name": "hallspot",
          "size": "1-10",
          "id": "hallspot",
          "founded": "2013",
          "industry": "computer software",
          "location": {
            "name": "portland, oregon, united states",
            "locality": "portland",
            "region": "oregon",
            "metro": "portland, oregon",
            "country": "united states",
            "continent": "north america",
            "street_address": "1231 northwest hoyt street",
            "address_line_2": "suite 202",
            "postal_code": "97209",
            "geo": "45.52,-122.67"
          },
          "linkedin_url": "linkedin.com/company/hallspot",
          "linkedin_id": "3019184",
          "facebook_url": null,
          "twitter_url": "twitter.com/hallspot",
          "website": "hallspot.com",
          "ticker": null,
          "type": "private",
          "raw": [
            "hallspot",
            "hallspot, inc"
          ],
          "fuzzy_match": false
        },
        "location_names": [],
        "end_date": "2015-02",
        "start_date": "2012-08",
        "title": {
          "name": "co-founder",
          "raw": [
            "co-founder"
          ],
          "role": null,
          "sub_role": null,
          "levels": [
            "owner"
          ]
        },
        "is_primary": false,
        "summary": "CRM for bars and restaurants. Expanded to select west coast college campuses. 800k seed. Angel Conference Presentation: https://www.youtube.com/watch?v=7gL7yIVXuzE"
      },
      {
        "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",
          "ticker": null,
          "type": "private",
          "raw": [
            "people data labs"
          ],
          "fuzzy_match": false
        },
        "location_names": [],
        "end_date": null,
        "start_date": "2015-03",
        "title": {
          "name": "co-founder and chief executive officer",
          "raw": [
            "co-founder & ceo",
            "co-founder & ceo"
          ],
          "role": null,
          "sub_role": null,
          "levels": [
            "owner",
            "cxo"
          ]
        },
        "is_primary": true,
        "summary": "People Data Labs builds people data. Leverage our dataset of 1.5 billion unique person profiles as your data foundation to build products, enrich person profiles, power predictive modeling/AI, analysis, and more. We build and maintain our data from our powerful Data Union. 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. Backed by Founders Fund. I consult with our engineering customers to solve people data building challenges - [email protected]"
      }
    ],
    "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",
          "facebook_url": "facebook.com/universityoforegon",
          "twitter_url": "twitter.com/uoregon",
          "linkedin_id": "19207",
          "website": "uoregon.edu",
          "domain": "uoregon.edu",
          "raw": [
            "university of oregon"
          ]
        },
        "end_date": "2014",
        "start_date": "2010",
        "gpa": null,
        "degrees": [],
        "majors": [
          "entrepreneurship"
        ],
        "minors": [],
        "raw": [
          "data analytics & entrepreneurship",
          ", entrepreneurship",
          "entrepreneurship"
        ],
        "summary": "Entrepreneurship at University of Oregon"
      }
    ],
    "profiles": [
      {
        "network": "linkedin",
        "id": "145991517",
        "url": "linkedin.com/in/seanthorne",
        "username": "seanthorne"
      },
      {
        "network": "facebook",
        "id": "1089351304",
        "url": "facebook.com/deseanthorne",
        "username": "deseanthorne"
      },
      {
        "network": "twitter",
        "id": null,
        "url": "twitter.com/seanthorne5",
        "username": "seanthorne5"
      },
      {
        "network": "linkedin",
        "id": null,
        "url": "linkedin.com/in/sean-thorne-9b9a8540",
        "username": "sean-thorne-9b9a8540"
      },
      {
        "network": "angellist",
        "id": null,
        "url": "angel.co/deseanthorne",
        "username": "deseanthorne"
      },
      {
        "network": "gravatar",
        "id": null,
        "url": "gravatar.com/seanthorne5",
        "username": "seanthorne5"
      },
      {
        "network": "klout",
        "id": null,
        "url": "klout.com/seanthorne5",
        "username": "seanthorne5"
      },
      {
        "network": "aboutme",
        "id": null,
        "url": "about.me/sean_thorne",
        "username": "sean_thorne"
      },
      {
        "network": "linkedin",
        "id": null,
        "url": "linkedin.com/in/acoaaaizp10baq08dng_c7v7ndeffmpgbo1oiqc",
        "username": "acoaaaizp10baq08dng_c7v7ndeffmpgbo1oiqc"
      }
    ],
    "possible_profiles": [
      {
        "network": "angellist",
        "id": null,
        "url": "angel.co/sean-thorne-1",
        "username": "sean-thorne-1"
      },
      {
        "network": "twitter",
        "id": null,
        "url": "twitter.com/talent_iq",
        "username": "talent_iq"
      },
      {
        "network": "klout",
        "id": null,
        "url": "klout.com/hallspot_dev",
        "username": "hallspot_dev"
      },
      {
        "network": "linkedin",
        "id": null,
        "url": "linkedin.com/in/sean-thorne-4b92813b",
        "username": "sean-thorne-4b92813b"
      },
      {
        "network": "twitter",
        "id": null,
        "url": "twitter.com/seanthorne1",
        "username": "seanthorne1"
      }
    ],
    "certifications": [],
    "languages": [],
    "version_status": {
      "status": "updated",
      "contains": [],
      "previous_version": "14.0",
      "current_version": "15.0"
    }
  },
  "dataset_version": "15.0"
}

This is the full profile for Sean Thorne (the CEO of People Data Labs) from our Person Dataset.

A couple key points to note here on profiles in our datasets:

  • Every profile record in our datasets is stored as a JSON object
  • Profiles in our Person Dataset will contain information for all the fields listed in our Person Schema , over 140 different fields that can enable a range of different use cases

Try looking up your own Person profile

For some variety, let’s try looking up someone besides our venerable CEO, Sean.

Find your favorite person on LinkedIn (could be yourself) go to their profile page and copy the url.

Then try running the following command:

📘

Before Running the Command

  1. Replace XXXX with your API key
  2. Replace YYYY with the linkedin url you want to “enrich”
API_KEY=“XXXX”
LINKEDIN_URL=“YYYY”
curl "https://api.peopledatalabs.com/v5/person/enrich?api_key=${API_KEY}&pretty=True&profile=${LINKEDIN_URL}"

This time you should see one of 2 results:

  1. A profile from our Person Dataset containing all the information we have associated with that linkedin url (similar to what we got before)
  2. An error indicating that the profile could not be found in our dataset. In this case, for this example, you can just try picking a different LinkedIn profile to enrich.

In this example, we are simply looking up profiles by their LinkedIn url, but the Person Enrichment API supports lookups using a variety of different inputs (such as name, email, phone numbers, employer, locations, and more). Feel free to dive deeper into the Person Enrichment API, but at this point, you should have an understanding of the type of information contained in our Person Dataset.


Lookup a Company Profile using the Company Enrichment API

Next up, let’s take a look at some records in the Company Dataset!

Just like we did for the Person Dataset, we will use the Company Enrichment API to retrieve the profile for a specific company. Let’s pull the record for People Data Labs, using the company’s linkedin profile: linkedin.com/company/peopledatalabs/

Here comes another cURL command:

📘

Before Running the Command

Replace XXXX with your API key

API_KEY=“XXXX”
curl "https://api.peopledatalabs.com/v5/company/enrich?api_key=${API_KEY}&pretty=True&profile=linkedin.com/company/peopledatalabs"

This time you should get the following response:

{
  "status": 200,
  "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_id": "18170482",
  "linkedin_url": "linkedin.com/company/peopledatalabs",
  "facebook_url": "facebook.com/peopledatalabs",
  "twitter_url": "twitter.com/peopledatalabs",
  "profiles": [
    "linkedin.com/company/peopledatalabs",
    "linkedin.com/company/18170482",
    "facebook.com/peopledatalabs",
    "twitter.com/peopledatalabs",
    "crunchbase.com/organization/talentiq"
  ],
  "website": "peopledatalabs.com",
  "ticker": null,
  "type": "private",
  "summary": "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. our data comes from our powerful data union: https://www.peopledatalabs.com/data-union 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 data science investors, 8vc and susa ventures.",
  "tags": [
    "data",
    "people data",
    "data science",
    "artificial intelligence",
    "data and analytics",
    "machine learning",
    "analytics",
    "database",
    "software",
    "developer apis"
  ],
  "headline": "Your Single Source of Truth",
  "alternative_names": [],
  "alternative_domains": [],
  "affiliated_profiles": [],
  "likelihood": 6
}

Just like for records in our Person data, company profiles in our Company Dataset are stored as JSON objects and contain information for the fields in our Company Schema.

Try looking up your own Company profile

Let’s try looking up another company profile.

This time, find your favorite company on LinkedIn, for example Google. Go to the company’s profile page and copy the url.

Because we are just trying to get a feel for the type of data contained in the PDL datasets, feel free to try out a few different linkedin urls. Here are a few examples:

  • https://www.linkedin.com/company/google/
  • https://www.linkedin.com/company/amazon/
  • https://www.linkedin.com/company/apple/

Then, once you have selected a linkedin url, try running the following command:

📘

Before Running the Command

  1. Replace XXXX with your API key
  2. Replace YYYY with the linkedin url you want to “enrich”
API_KEY=“XXXX”
LINKEDIN_URL=“YYYY”
curl "https://api.peopledatalabs.com/v5/company/enrich?api_key=${API_KEY}&pretty=True&profile=${LINKEDIN_URL}"

In response, you should now see either:

  • The full PDL company profile associated with the linkedin url you submitted
  • An error indicating that no matching record could be found, in which case you can just try out one of the example linkedin urls

We encourage you to try looking up a few different company profiles to get a sense of the type of coverage and information our datasets have.


Wrapping Up

And that’s it! You may not realize it but we covered a lot with this quickstart. Here’s a quick recap:

  • You created a PDL account and got a free API key, which you can use to access a variety of API endpoints
  • You used a simple cURL command to lookup person profiles in our PDL dataset by linkedin url (in the data world, we’d say you “enriched” a profile using a linkedin url)
  • You learned one way to use the Person Enrichment API to lookup person profile records
  • At the same time, you learned one way to use the Company Enrichment API as well
  • You saw multiple examples of person and company profiles that you pulled straight out of our datasets

Not bad for a few minutes of copying and pasting 😁

Updated 7 days ago


What's Next

Introduction

Quickstart


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