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Lesson Content

Why salary research requires source evaluation.

Salary data is everywhere – and it varies widely. This is not because some sources are wrong and others are right. Salary data varies because:

• Different methodologies: surveys vs. self-reported crowdsourcing vs. job posting analysis
• Different sample populations: geographic area, company size, industry subsector
• Different time periods: data may be from last year or earlier
• Different definitions: base salary vs. total compensation vs. OTE

Understanding these differences helps you use salary data intelligently, not just find a number and cite it.

Building a salary research search.

"What are current salary benchmarks for [specific job title] in [city or region] in [current year]? I have [X years of experience] and [relevant credentials/skills]. I am particularly interested in authoritative data sources. What are the key factors that drive salary variation at this experience level in this market?"

The salary source hierarchy.

Most authoritative (for base benchmarking):

• U.S. Bureau of Labor Statistics Occupational Employment and Wage Statistics (verify at bls.gov)
• State labor department statistics
• Major established compensation research firms (Mercer, Radford, Korn Ferry – note these often require purchase for full data)

High value:

• Major job boards with salary data (verify methodology published by each platform)
• LinkedIn Salary (based on member-reported data – see their methodology)
• Glassdoor (self-reported with volume – see their methodology)
• Industry professional association salary surveys

Use with context:

• Crowdsourced anonymous forums – directional but methodologically weaker
• Single employer postings with listed ranges – informative but narrow

Verifying the salary data Perplexity finds.

For salary benchmarking used in negotiation:

• Identify what data sources Perplexity found and their methodologies
• Access the authoritative sources directly (BLS is free and publicly available at bls.gov)
• Check when the data was collected – compensation data more than two years old may significantly understate current market rates
• Build a range rather than a single number – ranges are more defensible in negotiation