In a data-driven market, understanding job classifications and salary benchmarks is crucial for advertisers and HR professionals alike.
The Occupational Information Network (O*NET) and the Bureau of Labor Statistics (BLS) provide some of the most comprehensive data sources available on U.S. occupations, offering insights into job roles, required skills, industry trends, and salary expectations.
O*NET is a dynamic, detailed database developed by the U.S. Department of Labor that classifies and describes occupations across various industries. Each O*NET title corresponds to a specific occupation and includes key information such as required skills, competencies, education, and training requirements. This classification system helps standardize job roles across different industries and regions - down to the metro level.
The Bureau of Labor Statistics (BLS) compiles detailed salary and employment data for each occupation through surveys such as the Occupational Employment and Wage Statistics (OEWS) program. BLS salary data includes median and mean wages for specific occupations, industry-specific salary variations, and regional differences in pay.
At RampedUp, we provide an assumed salary based on the blended data points of O*NET occupational titles and BLS salary data on most contacts within the United States. We also assign the below Salary Bands for ease of use and segmentation:
- under $25,000
- $25,000 - $50,000
- $50,000 - $75,000
- $75,000 - $100,000
- $100,000 - $150,000
- $150,000 - $250,000
- $250,000+
By connecting O*NET job classifications with BLS salary data, we gain insight into salaries based on the employee's title and location. Ad Tech platforms, Consumer Marketing tools, and AI-driven job matching tools can use the fusion of O*NET and BLS data to associate a salary or salary band with a person based on their location and job title. The can also create custom audiences based on a person's salary, title, and location or use an assumed salary band as a datapoint for list building.