Skip to content
Visit the Platform
  • There are no suggestions because the search field is empty.

Compensation by Occupation API Guide

Compare compensation insights across occupations to support salary benchmarking, organizational planning, and equitable talent strategies.

What this API does

The Compensation by Occupation API delivers detailed salary information for any occupation in Pearson’s Ontology, allowing teams to view compensation distributions by year and country. This includes percentile-based data (10th to 90th), standard deviation, and confidence level — giving a statistically grounded view of earnings across roles.

You can use this API to:

  • Benchmark salaries to support compensation planning and pay structure design

  • Validate if your role titles align with market-level compensation data

  • Analyze how compensation has changed over time across multiple percentile levels

Who it's for

This API is most relevant for:

  • People Strategists – who need reliable market benchmarks to inform workforce planning, budgeting, and pay equity efforts.

  • Tech Strategists – who analyze job and salary data as part of automation impact assessments or workforce technology initiatives.

Supported customer goals

This API helps customers:

  • Explore workforce market trends — through historical and current salary data across roles

  • Standardize roles and salaries — by mapping job titles to Pearson’s ontology and aligning with percentile ranges

  • Understand the impact of tech — by combining compensation insights with automation risk or role change potential

API Bundles

This API is included in the following bundle:

Foundational APIs — available to all paying API customers by default

Input & Output

Input

  • Required: An Occupation ID from Pearson’s ontology

  • Optional: A Country Code (default is US)

Output

  • Year-over-year salary percentiles (10th, 25th, 50th, 75th, 90th)

  • Standard deviation and confidence level for each year

  • Multiple views available: Chart, Table, and downloadable JSON

Practical Examples

  • A People Strategist in Australia enters “Digital Marketing Manager” to view salary trends from 2020–2025 and compare 50th and 90th percentiles when designing a new pay band.

  • A Tech Strategist exploring the impact of automation on clerical roles looks up compensation ranges to identify which jobs may become overvalued or under-compensated over time.

  • A compensation consultant supporting workforce transformation for a client maps legacy job titles to Pearson Ontology and runs this API to create salary benchmark dashboards.