People Data Labs sits at the center of a lot of B2B data workflows, powering enrichment for companies like eBay, Adidas, and thousands of growing startups. But most teams considering PDL don't fully understand what makes it different from other data providers, or how to actually use it effectively.

This guide breaks down how People Data Labs works: where the data comes from, what the APIs do, how pricing operates, and where PDL fits in the landscape of B2B data tools. Whether you're evaluating PDL for the first time or trying to get more value from an existing implementation, this covers everything you need to know.

What Is People Data Labs?

People Data Labs (PDL) is a B2B data-as-a-service company that provides person and company data through APIs and licensed datasets. Founded in 2015, PDL has built one of the largest people databases in the industry, with nearly 3 billion person profiles and over 70 million company profiles.

The core value proposition is straightforward: you send PDL whatever information you have about a person or company, and they return a complete profile with all the additional data points they can match. An email address becomes a full professional profile. A company domain becomes firmographic details, employee counts, funding information, and more.

PDL positions itself as infrastructure for data teams rather than an end-user sales tool. Their customers are typically building products that need people data, including HR tech platforms, sales intelligence tools, marketing automation systems, and analytics products. This developer-first orientation shows up in their documentation, API design, and pricing model.

Where Does PDL Get Its Data?

Understanding PDL's data sources helps explain both its strengths and limitations.

The Data Union model

PDL operates what they call a "Data Union," which is essentially a data-sharing cooperative. Companies opt into sharing their data with PDL, and in return they get access to the aggregated dataset. Participants span HR tech, real estate tech, identity verification, marketing technology, and other verticals.

This model means PDL's data comes from companies that have direct relationships with the people in their database, not from scraping public sources. The trade-off is that coverage depends on which companies participate in the union.

Public data sources

Beyond the Data Union, PDL aggregates publicly available data including government records, business filings, and other open sources. They combine these with their proprietary sources to build more complete profiles.

Data processing and standardization

Raw data from these sources goes through PDL's data pipeline, which handles:

Deduplication to combine records that represent the same person or company across different sources. A single professional might appear in multiple source systems under slightly different names or with different contact information.

Standardization to normalize job titles, company names, locations, and other fields into consistent formats. "VP of Sales" and "Vice President, Sales" become the same standardized title.

Validation to check that data points make logical sense together. Employment dates should be sequential. Locations should match companies. Email domains should correspond to employers.

The result is a unified dataset that's cleaner and more consistent than any individual source, though still imperfect given the inherent challenges of B2B data.

PDL's Core APIs Explained

PDL offers several APIs, each designed for different use cases. Understanding when to use which one matters for both cost management and result quality.

Person Enrichment API

This is the most commonly used endpoint. You provide identifying information about a person, and PDL returns their complete profile.

Input options:

You can look up people using their email address, phone number, LinkedIn URL, name plus company, name plus location, or various combinations of these identifiers. More specific inputs generally produce more accurate matches.

Output data:

A successful match returns the full person profile, which can include names and aliases, current and past employment history with job titles and dates, education history, locations including current and inferred, email addresses (personal and professional), phone numbers, social media profiles, and skills and interests.

How matching works:

PDL uses proprietary matching logic to find the person in their database. You can control match strictness through parameters, trading off between match rate (finding more people) and accuracy (higher confidence in the matches you find).

When you set stricter matching thresholds, PDL requires more input fields to match or higher confidence scores. This reduces false positives but also means some legitimate matches might not return.

Company Enrichment API

Similar to person enrichment, but for organizations. Provide a company identifier and receive the full company profile.

Input options:

Look up companies by domain, name, LinkedIn URL, stock ticker, or combinations of these. Domain tends to be the most reliable identifier for digital-first companies.

Output data:

Company profiles include firmographic basics like industry, employee count, and founding year. They also include location details for headquarters and other offices, social media presence, funding information when available, technology stack data, and related entities like subsidiaries or parent companies.

Person Search API

While enrichment works when you have a specific person in mind, search lets you find people matching certain criteria. This enables prospecting use cases.

How it works:

You build a query specifying the attributes you want to filter on: job title contains "VP of Marketing," company employee count between 100 and 500, location in the United States, and so on. PDL returns people matching those criteria.

Use cases:

Building targeted prospect lists for outbound campaigns. Finding decision-makers at specific accounts. Identifying candidates matching certain professional criteria. Market research on workforce composition in specific industries.

Company Search API

The company equivalent of person search. Build queries to find companies matching specific criteria and receive matching company profiles.

Person Identify API

This endpoint handles fuzzier matching scenarios where you have incomplete or potentially inaccurate information. Rather than returning a single best match, it can return multiple potential matches ranked by likelihood.

When to use it:

When your input data quality is low and you want to see multiple possibilities rather than relying on PDL's single best guess. When you're doing entity resolution across messy datasets. When you need the matching logic to be more permissive than standard enrichment.

IP Enrichment API

A newer addition that maps IP addresses to companies. You provide an IP address and receive information about the company associated with that IP, including location metadata.

Use cases:

Website visitor identification, where you want to know which companies are viewing your site. Account-based marketing workflows where IP data helps personalize experiences. Fraud detection where IP to company mapping helps verify business identity.

Supporting APIs

PDL also offers several utility APIs that don't consume credits:

The Autocomplete API suggests completions for partial input, useful for building search interfaces.

Cleaner APIs standardize and validate input data before you send it to enrichment endpoints. Cleaner job titles, company names, schools, and locations can improve match rates.

How PDL Pricing Works

PDL uses a credit-based pricing model that can get complicated. Here's how it actually breaks down.

The basics

You purchase credits, and different API calls consume different numbers of credits. You only get charged when the API successfully returns a match. Failed lookups where PDL doesn't find the person or company don't consume credits.

Credit consumption by endpoint

Person Enrichment consumes 1 credit per successful match. Company Enrichment also uses 1 credit per match. Person Search uses 1 credit per profile returned, so a search returning 50 results uses 50 credits. The Identify API uses more credits per call since it does more complex matching.

Plans and pricing tiers

PDL offers three main tiers:

The Free plan includes 100 person or company lookups per month. This is enough to test the API and validate that it works for your use case, but the free tier doesn't include email or phone data, only basic profile fields.

The Pro plan starts at $98/month and includes more generous credits plus access to contact data fields. Additional credits can be purchased at per-match rates that vary by endpoint.

Enterprise plans offer custom pricing for high-volume users, negotiated based on your specific needs. These include dedicated support, custom integrations, SLAs, and volume discounts. Contact PDL's sales team for enterprise pricing.

Understanding your costs

A few factors affect your actual spend with PDL:

Match rates depend on your input data quality and the populations you're enriching. Better input data (verified emails, LinkedIn URLs) typically produces higher match rates. Testing with a sample of your actual data helps you estimate costs accurately.

The search APIs consume credits per returned profile, so broad searches use more credits than narrow ones. Using filters effectively helps manage search costs.

Different data points have different fill rates across the database. Understanding which fields you need helps you evaluate whether PDL's coverage meets your requirements for your specific use case.

What Data Does PDL Return?

PDL's schema includes dozens of fields across person and company profiles. Here's what you can expect in terms of data availability.

Person data with strong coverage:

Names and name variations are consistently available since every profile has identity information.

Current employment information, including company name, job title, and start date, is available on most profiles. Historical employment varies by profile.

Location at the city and country level is typically present, either explicitly provided or inferred from other data points.

LinkedIn profile URLs when available in PDL's data sources.

Person data with good coverage:

Email addresses (both personal and professional) are available on many profiles. Coverage varies by geography and the specific population you're enriching.

Education history is present when available from contributing sources.

Skills and interests are derived from job histories and other signals.

Person data that varies more:

Phone numbers, especially direct dials, have more variable coverage. This is common across the industry given the challenges of sourcing phone data compliantly.

Personal details like interests and social profiles beyond LinkedIn depend on what's available in PDL's sources.

Company data with strong coverage:

Basic firmographics like name, domain, industry, and employee count are well covered for established companies.

Location information for headquarters is reliable.

Social profiles and basic web presence data.

Company data with good coverage:

Funding information is available for venture-backed companies. Private companies without public funding may have less data.

Technology stack data varies depending on whether the company has been profiled by technographic sources.

Revenue estimates should be treated as directional indicators rather than precise figures, which is standard across B2B data providers.

Common Use Cases for PDL

Sales and marketing enrichment

The most straightforward use case is enriching CRM records with additional data points. You have a list of contacts with email addresses, and you want to add job titles, company information, and other details for segmentation and personalization.

PDL's coverage of professional profiles makes it well suited for B2B enrichment. The data points most useful for sales, including job title, company, seniority indicators, and company size, tend to have good coverage.

Product data infrastructure

Many PDL customers are building products that need people or company data as a feature. An applicant tracking system might use PDL to auto-fill candidate profiles. A sales intelligence platform might use PDL as one of its data sources. A marketing automation tool might use PDL for lead enrichment.

In these cases, PDL functions as infrastructure that gets built into the product rather than a tool that end users interact with directly.

Market research and analytics

PDL's search capabilities enable research use cases. You can analyze workforce composition across industries, track hiring trends by examining job title distributions over time, or map competitive landscapes by examining employee movements between companies.

The dataset's size makes it useful for macro-level analysis even though individual records may have gaps.

Identity verification and fraud detection

PDL helps verify that people are who they claim to be by matching provided information against their database. If someone claims to work at a specific company with a specific title, PDL can confirm or contradict that claim.

The company to IP mapping also supports fraud detection workflows where business identity verification matters.

What Makes PDL Stand Out

Great coverage breadth

With nearly 3 billion person profiles, PDL offers one of the largest professional databases available. This scale means you're likely to find matches for the people you're looking for, particularly in North America and Europe where coverage is strongest.

Developer-first experience

PDL's documentation, SDKs, and API design are built for technical teams. The APIs are well-structured, the documentation is thorough, and integration is straightforward compared to many alternatives. If you're building data products or custom integrations, PDL makes the technical work easier.

Strong compliance foundation

PDL's Data Union model and published acceptable use policies provide confidence that data is sourced appropriately. For companies with privacy and compliance requirements, this transparency matters.

Flexible matching controls

The ability to adjust match strictness lets you balance between coverage and precision based on your specific use case. Stricter matching for high-stakes decisions, looser matching when you want broader coverage.

Considerations for your use case

Like any data provider, PDL works better for some scenarios than others. Coverage is strongest for established professionals in major markets. Match rates vary based on your input data quality and the specific populations you're enriching. Understanding these patterns helps you set realistic expectations and build effective workflows.

For teams that need maximum coverage across contact data specifically, combining PDL with other providers through waterfall enrichment often produces the best results. This is a common pattern across the industry, not a PDL-specific limitation.

Using PDL Through Databar

While PDL offers direct API access, many teams prefer accessing it through data integration platforms that simplify workflows and enable multi-provider strategies.

Databar has People Data Labs as a native integration, which means you can:

Access PDL enrichment without managing API credentials and rate limits yourself. The integration handles the technical complexity.

Combine PDL with other data providers in waterfall enrichment workflows. When PDL doesn't have a match or lacks specific data points, Databar can automatically query other providers to fill gaps.

Build enrichment workflows without code using Databar's visual interface. If you don't have engineering resources to build custom API integrations, this dramatically lowers the barrier to using PDL.

Manage costs more effectively by routing queries strategically across providers based on expected coverage and pricing.

Get started with People Data Labs inside Databar today to access PDL alongside 100+ other data providers in a unified platform.

PDL vs. Other Data Providers: Finding the Right Fit

PDL occupies a specific position in the data provider landscape, and understanding where it fits helps you evaluate whether it's right for your needs.

Vs. live scraping tools (Proxycurl, Scrapin):

These tools scrape data in real time rather than querying a pre-built database. PDL's approach offers faster response times, more consistent data structure, and clearer compliance posture. Live scraping may provide more recent updates for specific profiles but with higher latency.

Vs. other data aggregators (Clearbit, FullContact):

These occupy similar market positions to PDL. Differences come down to specific data sources, coverage in particular geographies or industries, pricing models, and integration options. PDL's scale and developer experience make it particularly strong for product teams.

When PDL is an excellent fit:

You need broad coverage across the professional population. You're building a product that needs people data as infrastructure. You have technical resources to work with APIs. You value compliance and data sourcing transparency. You want flexible matching controls for different use cases.

Getting Started With PDL

If you're evaluating PDL for the first time, here's a practical path forward.

Test with the free tier

PDL's free plan lets you make 100 API calls per month. Use this to test match rates and data quality on a sample of your actual data. This gives you concrete results to inform your decision.

Start with enrichment, not search

Enrichment is simpler and more predictable than search. Begin by enriching contacts you already have before using search to build new lists. This helps you understand PDL's data quality with your specific use case.

Define your requirements clearly

Which data points do you need? What match rate would work for your use case? What's your expected volume? Clear requirements help you choose the right plan and set up effective workflows.

Consider multi-provider strategies for maximum coverage

Many teams achieve the best results by combining PDL with other providers through waterfall enrichment. When one provider doesn't have a match, another often does. This is a common pattern for maximizing coverage.

Access People Data Labs through Databar to simplify integration and combine PDL with other providers in unified CRM enrichment workflows.

FAQ

Is People Data Labs free?

PDL offers a free tier with 100 lookups per month, but it's limited to basic profile fields without email or phone data. The free tier is designed for testing and evaluation rather than production use. Paid plans start at $98/month.

Where does People Data Labs get its data?

PDL aggregates data from their "Data Union" (a cooperative of companies that share data), public sources like government records and business filings, and various partnerships. They don't scrape social profiles directly, which differentiates them from some competitors.

How accurate is People Data Labs data?

PDL processes data through rigorous deduplication, standardization, and validation. Core profile information like name, company, and job title is reliable. Contact data coverage varies by population and geography, which is standard across the B2B data industry. PDL's matching logic lets you control the trade-off between coverage and precision for your specific use case.

How often is PDL data updated?

PDL refreshes their dataset monthly, with API endpoints receiving regular updates. The Person Schema includes "job_last_updated" and other timestamp fields so you can see when specific data points were last verified. This update cadence supports most B2B enrichment use cases effectively.