Quickstart

Overview

This quickstart is a brief introduction to our data and APIs. Don’t worry if you’ve never used an API before, as with a little copy-and-paste magic, we’ll get you up and running in no time. 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. Augmenting existing records with our Person Enrichment API
  3. Looking Up a Company Profile Using our Company Enrichment API

Now let’s get started!


Creating 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: 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 one.

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


Augmenting Existing Records with the Person Enrichment API

Once you have your API key, 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 XXXX with your API key, and hit enter to run the command.

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

This is what happens when we run this command:

  • We send a request through a 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 in the API response (with a 200 status, as 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"
}

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

A couple key points to note 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 relating to the more than 140 fields in our Person Schema, which can enable a wide range of different use cases.

Try looking up your own Person profile

For some variety, let’s look up someone besides our venerable CEO. Find your favorite person on LinkedIn (which could even be yourself), and then go to their profile page and copy the URL. Finally, try running the following command:

📘

Before Running the Command

  1. Replace XXXX with your API key.
  2. Replace YYYY with the Linkedin URL that 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 that 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. If this happens, try picking a different LinkedIn profile to enrich.

In the above example, we're 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 a basic understanding of the type of information contained within our Person Dataset.


Looking Up a Company Profile Using the Company Enrichment API

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

Just as we used the Person Enrichment API to retrieve the profile of a specific person, we'll use the Company Enrichment API to retrieve the profile of a specific company. Let’s pull the record for People Data Labs using the company’s Linkedin profile: linkedin.com/company/peopledatalabs/

Here's the cURL command for doing this:

📘

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
}

As with records in our Person Dataset, 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 trying to get a feel for the type of data contained in the PDL datasets, try a few different Linkedin URLs. Here are some examples:

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

Once you have chosen a Linkedin URL, run the following command:

📘

Before Running the Command

  1. Replace XXXX with your API key.
  2. Replace YYYY with the Linkedin URL that 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 the response, you should see either:

  • The full PDL company profile associated with the Linkedin URL that you submitted.
  • An error indicating that no matching record could be found, in which case you can try one of the example Linkedin URLs listed above.

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


Wrapping Up

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 look up person profiles in our PDL dataset by Linkedin URL (in the data world, we’d say that you “enriched” a profile using a Linkedin URL.)
  • You learned how to use the Person Enrichment API to look up person profile records.
  • You also learned how to use the Company Enrichment API to look up company profile records.
  • 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 😁.


What’s Next
Did this page help you?