Introducing Better Market Compensation Intelligence

Today, we’re introducing a major upgrade to PDL Inferred Salary, giving customers a more complete view of market compensation for the people and roles they care about.

Inferred Salary helps customers estimate a person’s likely compensation based on their current role, powering workflows like lead segmentation, candidate matching, and labor market analysis.

But customers consistently told us where it could be better: more precise ranges, better international estimates, broader coverage, and more context behind each prediction.

So we made two major improvements:

Whether you’re matching candidates to roles, building compensation-aware products, segmenting audiences, or analyzing labor markets, our expanded Inferred Salary data provides a more complete view of what someone in a given role is likely to earn in today’s market.

Compensation is shaped by more than a job title. Job function, seniority, company, geography, and current hiring-market conditions can all influence what a role is likely to pay.

PDL Inferred Salary combines Person Data with signals from Job Posting Data to estimate compensation at scale.

Rather than treating salary as a fixed attribute or relying only on broad salary buckets, the updated methodology provides richer compensation context based on a person’s role and the market around it.

Here’s what’s new with the expanded data:

We’ve expanded Inferred Salary from a single broad salary bucket into a more complete set of compensation signals:

For example:

{
  "inferred_salary": "150,000-250,000",
  "inferred_salary_low": 150000,
  "inferred_salary_high": 210000,
  "inferred_salary_confidence": "high"
}

This additional precision makes Inferred Salary easier to use in workflows like candidate matching, lead scoring, audience segmentation, and market analysis.

Previously, our salary buckets capped out at $250k+, limiting differentiation at the upper end of the market.

The new low and high estimates are uncapped and adjusted based on the market distribution of salaries for a given role. As a result, these fields provide greater granularity for highly compensated roles, making it easier to distinguish profiles that previously fell into the same broad bucket.

This can be especially useful for executive recruiting and high-compensation audience segmentation.

Compensation can vary dramatically across markets, even for similar roles.

By incorporating geography alongside real-world job-posting compensation signals, Inferred Salary estimates can better reflect differences across roles, companies, and locations.

For teams working across countries or regions, that provides more relevant market context.

A salary estimate is more useful when you also understand the strength of the signal behind it.

That’s the purpose of inferred_salary_confidence, which provides a high-level confidence tier alongside each estimate.

For automated workflows and market research, this gives teams more flexibility to prioritize higher-confidence estimates or treat lower-confidence values as a softer signal.

Our Inferred Salary data is also available across substantially more people.

Our inferred_salary coverage now spans more than 346 million Resume records, a 26% increase from the previous production release.

That means compensation can become a useful signal across more of the people data you already work with.

Job Posting Data is a key foundation of the improved Inferred Salary methodology.

Companies change hiring budgets. Pay varies by location. Similar roles can represent very different levels of seniority. And the market value of a role can shift over time.

By grounding salary estimates in observed job-market compensation, Inferred Salary can provide a more contextual view of what similar work is paying today.

The richer compensation context available through Inferred Salary can add useful signals anywhere you already use people data.

HR Tech & Recruiting

Estimate whether candidates align with a role’s compensation range, improve recommendations, or add salary context to search and ranking.

Sales & Marketing

Build compensation-based audience segments or add estimated earning level to scoring and targeting models.

Analytics & Research

Compare compensation across roles and geographies, study labor-market trends, or enrich large-scale person datasets.

Product & Data Teams

Build compensation intelligence into products, models, and internal workflows without needing verified salary data for every individual.

If compensation influences how you match candidates, segment audiences, rank profiles, or analyze markets, now is a great time to explore what the improved Inferred Salary data can add to your workflow.

Already a PDL customer? Reach out to your account team to explore the new fields and test the expanded Inferred Salary data against your existing workflows.

New to PDL? Talk to our team to see how market compensation intelligence can strengthen your recruiting, product, analytics, or go-to-market strategy.

Ready to start building? Explore the Inferred Salary documentation and September release notes for field definitions, coverage, and implementation details.