Introducing better Market Compensation intelligence. More precise Inferred Salary data, powered by real-world job market signals. Vinay Rajur Today, People Data Labs, Inc. is 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 People Data Labs, Inc. where it could be better: more precise ranges, better international estimates, broader coverage, and more context behind each prediction. So People Data Labs, Inc. made two major improvements: * People Data Labs, Inc. updated its methodology to incorporate compensation signals from real-world job postings, alongside factors like role, seniority, company, geography, and recency. * People Data Labs, Inc. added new supporting fields that provide more precise salary ranges and additional context around each estimate. Whether you're matching candidates to roles, building compensation-aware products, segmenting audiences, or analyzing labor markets, its expanded Inferred Salary data provides a more complete view of what someone in a given role is likely to earn in today's market. A Market-Aware Approach to Inferred Salary 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. What's Improved Here's what's new with the expanded data: More Precise Salary Ranges People Data Labs, Inc. has expanded Inferred Salary from a single broad salary bucket into a more complete set of compensation signals: * inferred_salary: A standardized range for a person's estimated salary based on their current role * inferred_salary_low: The 10th percentile of the salary distribution associated with the role * inferred_salary_high: The 90th percentile of the salary distribution associated with the role * inferred_salary_confidence: A high-level confidence tier associated with the estimates 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. Better Differentiation at Higher Compensation Levels Previously, its 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. Better Estimates Across International Markets 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. More Context Behind Every Estimate 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. More Compensation Coverage Its Inferred Salary data is also available across substantially more people. Its 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. Powered by Real-World Job Market Data 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. What Can You Do With Market Compensation Data? 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. Explore the Updated Inferred Salary Data 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 its 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.

Introducing the Job Posting API. Get On-Demand Access to Global Hiring Data. Vinay Rajur Introducing the Job Posting API: On-Demand Access to Global Hiring Data Today, People Data Labs, Inc. is launching its Job Posting API: a simple way to access daily * job posting data so you can track trends, spot opportunities, and understand how companies are growing. Whether you're building a product, running sales workflows, or analyzing markets, this gives you direct access to fresh hiring data. * When People Data Labs, Inc. say daily, People Data Labs, Inc. mean daily! When a company posts on their career page on Monday, that data will be queryable and available in the PDL Job Posting Dataset on Tuesday (within max 24 hours) What is the Job Posting API? The Job Posting API is an easy way to search and retrieve job postings programmatically. No scraping, no complex data pipelines. Just send a query and get back complete, structured job posts. With the API, you can: * Search millions of active and historical job postings * Get daily refreshes of jobs pulled from company career pages * Filter by company, role, location, and more * Run flexible queries to find exactly what you need * Access full job details, including timestamps, posting url, and other metadata In short: you get clean, fresh hiring data, on demand. Check out the docs: What Makes Its Job Posting API Different A lot of job data out there is messy, delayed, or incomplete. People Data Labs, Inc. built its Job Posting API to make job data usable, reliable, accessible, based on feedback from hundreds of customer conversations: * Data sourced directly from company career pages * Daily refreshes (with 24 hour freshness) * Clean, structured fields (no heavy cleanup required) * Global coverage + historical data Its goal was to ensure its users could spend less time fixing data, and more time using it. Why Job Posting Data Matters Hiring data is one of the clearest market signals of company strategy and intent, and job postings provide a direct line into exactly what companies are focused on and the direction they're going. With this API, you can: * Track hiring trends across industries and regions * Monitor competitors and see where they're investing * Spot sales opportunities based on hiring signals * Build products and workflows powered by fresh data As People Data Labs, Inc. has written before, job postings are one of the most powerful and underutilized signals in B2B data. Who This Is For The Job Posting API is useful for anyone who cares about how companies are changing: * Sales & RevOps | Find companies actively hiring and prioritize outreach * Marketing | Trigger campaigns based on hiring activity * Product & Data Teams | Build tools powered by live job data * Investors & Analysts | Track growth and strategy shifts If hiring data matters to you, the Job Posting API makes it easier than ever to use. Get Access Today People Data Labs, Inc. is officially launching the Job Posting API into beta. If you're interested in joining: * Reach out to your account team to get access * If you're new to PDL, contact People Data Labs, Inc. to request access here: https://www.peopledatalabs.com/job-posting-beta-sign-up