You’re trying to set pay for a role and you need a number you can defend. Maybe you’re benchmarking a new position before you post it. Maybe you’re rebuilding pay ranges across the org. Maybe you have a top performer threatening to leave and you need to know what counter-offer makes sense.
A compensation survey is the tool that answers the question. Done well, it tells you what the market pays for the role you’re trying to price, how much variation there is, and which percentile fits your strategy. Done poorly, a quick AI-generated answer, a free aggregator search, or a stale survey pulled from a folder tells you nothing useful and can cost you the hire, the retention save, or the budget argument.
We help Northeast Ohio employers run compensation projects every week. Reading a survey well is the difference between a defensible pay decision and a guess with a spreadsheet behind it. Here’s how to choose a survey, how to read what’s inside one, and how to turn it into a market rate you can stand behind.
What is a compensation survey
A compensation survey is a report of what a defined group of employers pay for a defined set of jobs over a defined period. The best ones collect data directly from employers (not from job postings, employee self-reports, or scraped aggregators), match positions by job description rather than title, and report multiple measures of pay so you can pick the percentile that fits your strategy.
A survey isn’t a salary number. It’s the underlying data and methodology that lets you arrive at a number you can defend.
Types of compensation surveys
Not every survey works for every job. Picking the right one matters more than reading any single one perfectly.
National surveys. Broad coverage, big sample sizes, often industry-agnostic or industry-segmented. The Bureau of Labor Statistics (BLS) publishes occupational wage data for free. ERC co-sponsors the EAA National Executive Compensation Survey, which covers 9,722 executives in 47 positions at 1,667 organizations across 48 states. National surveys are your default for executive roles and for positions where geography matters less than function.
Regional surveys. Tighter geographic coverage, often better job-match accuracy because participating employers share a labor market. Our ERC Salary Survey Report covers 4,888 employees in 160 positions across 93 Northeast Ohio organizations. Regional surveys are your default for non-executive roles in a specific market.
Industry-specific surveys. Tech (Radford), financial services (McLagan), nonprofit (sector-specific), manufacturing (multiple). Useful when the role has industry-specific skill premiums that a general survey won’t capture.
Published commercial surveys. Mercer, Willis Towers Watson, Economic Research Institute (ERI), Salary.com, Payscale. Each has a different methodology and data source mix. Strengths and limitations covered below.
Custom surveys. When you have a unique role or a tight peer group, you commission your own. Most useful for hard-to-benchmark positions where no published survey gives you enough sample size.
Compensation survey data sources to know
Most HR teams use a mix of two to four sources. Here’s an honest read of the main ones.
ERC Salary, Wage, and Benefits Survey Reports. Northeast Ohio employer-reported data. Strong for regional employers across most industries. Limitation: regional coverage doesn’t help if your labor market is national.
EAA National Executive Compensation Survey. Employer-reported data from 1,667 organizations, 9,722 executives, 47 positions. Strong for executive roles, especially when you want to compare manufacturing vs. non-manufacturing patterns. ERC is a co-sponsor of this 50th annual survey.
Mercer. Large global publisher, broad role coverage, strong methodology. Limitation: expensive, often priced for enterprise.
Willis Towers Watson (WTW). Comparable to Mercer in scope. Strong for executive and total rewards data.
Economic Research Institute (ERI). Subscription-based, broad coverage, useful for cost-of-labor and geographic differentials.
Salary.com. Aggregates multiple sources. Useful as a sanity check. Limitation: less transparent on underlying data sources than employer-reported surveys.
Payscale. Mix of employer-reported and employee-reported data. Limitation: the employee-reported portion is self-selected and can skew.
Bureau of Labor Statistics (BLS). Free, broad, government-collected. Limitation: published with a lag, broad job categories that may not match specific roles.
The two-question test for any source: (1) Is the data employer-reported, or pulled from job postings, employee self-reports, or scrapes? (2) Is the effective date recent enough that you can trust it for a 2026 pay decision? If you can’t answer both, treat the result as a sanity check, not a market rate.
What to look at inside a survey: the eight components
The rest of this guide walks the eight components that show up in nearly every reputable survey, and what to look for in each.
Effective date
The date or range of dates during which the employees in the report were being paid the rates shown.
This is different from the data collection period (when the survey was open) and the publish date (when the report came out). The effective date is the one that tells you whether the data is usable. If you’re making a 2026 pay decision against a survey with a 2023 effective date, you’re undershooting the market by something like 9 to 15% before you start, depending on how you stack three years of typical merit and market increases.
What to look for: a recent effective date (within the last 12 months for most roles, the last 6 months for hot markets) and a standardized period across all data points, not a rolling collection that mixes Q1 and Q4 rates.
Demographic breakouts
How the survey segments its data. Common breakouts include employer size, industry, revenue, non-profit status, union status, and geography. Some surveys also report tenure-based breakouts.
What to look for: breakouts that match your organization. If you’re a 60-person Northeast Ohio non-profit and the survey is dominated by 5,000-person manufacturers in the Southeast, the overall numbers won’t represent your market. Either find better-matched breakouts inside the survey or pick a different source.
A practical note: if you can’t find a breakout that matches your org, you can still use the survey to learn what other employers in your geography pay for common office and administrative roles. Geography often matters more than industry for those positions. Just be ready to make the case for non-cash differentiators (flexibility, culture, growth) when the dollar figures don’t favor you.
Sample size
For the survey as a whole, the number of employers that participated. For each position, both the number of employers reporting data and the number of individual employees represented.
What to look for: sample sizes large enough that a few outliers can’t tilt the numbers. Survey publishers are required by federal regulation to exclude jobs or breakouts with fewer than five reporting employers, so anything you see has at least that. But single-digit employer or employee counts at the breakout level are fragile, and year-over-year changes in those positions are often noise, not signal.
When stats look surprising, sample size is usually the first thing to check.
Job titles, descriptions, numbers, and families
Job title is the position name. The description is the summary of major duties. The job number is an organizing code. The job family is the functional grouping (e.g., Finance, IT, HR).
What to look for: a job description that matches your organization’s job at least 70%. Title alone won’t get you there. “Operations Manager” can mean radically different things at different employers. Read the description carefully and compare it to the duties on your job’s actual job description.
If your role spans two survey jobs because it combines duties, don’t pick one and hope. Use the blending technique covered in the next section.
Median, percentiles, and how to land on a market rate
The most important section if you’re going to walk away with a number you can defend.
Median. The value at which 50% of employers pay at or below, or at or above. When data points are listed from lowest to highest, the median is the middle number. If there’s an even number of data points, the median is the average of the middle two.
The median is the workhorse statistic in compensation surveys because it’s less influenced by outliers than the mean. If one employer in the sample pays a 90th-percentile salary because of a one-time retention bonus, the median ignores that distortion.
Market rate. A defensible market rate is calculated by averaging the medians for the same position from at least three independent, reliable, employer-reported sources, where the job description in each source matches your organization’s job at 70% or better.
Three sources is a floor, not a ceiling. The point is to reduce the chance that any one survey’s quirks (which industries participated, which geographies, which year’s effective date) skew your decision. If you only have access to one survey, treat the median as a starting point, not a market rate.
The blending technique for multi-duty roles. When your job combines duties from two or more survey jobs, you weight the medians of each underlying job by the share of duties they represent in yours. Example: if your “Operations Coordinator” is 60% Administrative Coordinator duties and 40% Logistics Coordinator duties, you weight the medians 60/40 and average them. Blending is more accurate than picking the closest single match when the closest single match is only a partial fit.
Other percentiles: when to use the 25th, 75th, or 90th. The 25th, 75th, and 90th percentiles are calculated the same way as the median, but at different points in the distribution. Which percentile you target depends on your compensation philosophy and the role.
- Target above the median (75th or 90th) when you’re recruiting for a strategic, high-impact, or scarce-skill role; when you want to lead the market because that’s the philosophy; when you’re protecting against turnover in a specific job family.
- Target the median (50th) when you’re competing fairly and don’t have a strategic case for paying above market.
- Target below the median (25th) when your benefits, culture, or growth opportunity carries weight in the total package and you’re explicit about that with candidates.
The percentile choice is a strategy choice, not a calculation. A survey gives you the numbers; your compensation philosophy tells you which one to use.
Worth knowing: the median (and every other percentile) is a starting point, not the answer. Once you have it, you still have to weigh organizational strategy, location cost-of-living differences, internal equity, and how much the specific person you’re hiring is worth to you in this role. The median tells you what the market pays. It doesn’t tell you what you should pay.
Employer and weighted averages
Average per employer is the sum of each employer’s rate divided by the number of reporting employers. Weighted average is the sum of each employee’s rate divided by the number of reporting employees.
These are still measures of central tendency, but they’re more sensitive to outliers than the median. Most compensation experts treat the median as the primary statistic and use averages as supporting context.
What to look for: comparing employer average to weighted average. If they diverge meaningfully, it usually means a small number of employers in the sample pay markedly higher or lower than the rest, and the weighted average is pulled by the bigger payrolls.
Types of pay reported
Some surveys report base pay only. Others report bonuses, commissions, equity, total cash compensation, or total direct compensation. Each calculation uses the same statistics (median, percentiles, averages) at different points in the pay package.
What to look for: a clear statement near the top of the report of exactly what’s included in each pay number. If you’re benchmarking an executive or a sales role and you only look at base pay, you’ll undershoot the market significantly because base is a small portion of the total package.
For higher-level positions, the report should distinguish base, short-term incentives (annual bonus), long-term incentives, and total compensation. If those aren’t broken out, the survey isn’t the right fit for executive comp.
Red flags to watch for
Worth a quick scan before you use the data:
- Effective date older than 12 months for a non-hot-market role, or older than 6 months for a hot-market role.
- Single-digit sample sizes in the specific position or breakout you’re using.
- Title-only matching without reading the job description.
- Data sources that aren’t employer-reported (job posting scrapes, employee self-reports, opaque aggregators).
- Missing demographic breakouts that would let you compare to your org’s size, industry, or geography.
- A single source being treated as a market rate. A market rate takes at least three independent sources, not one survey’s median.
What pay transparency changes
Pay transparency laws have expanded to more than a dozen states. They change two things about how to read survey data.
First, posted pay ranges are now more visible than they were even three years ago. That’s useful as a sanity check, but it’s not the same as paid-rate data. Posted ranges are aspirational and often broad. Paid rates are what employers actually pay. Survey data is paid-rate data, which is why it’s still the foundation of a defensible decision.
Second, internal equity matters more than it used to, because employees can now see what their employer posts for new hires in the same role. A survey-based external market rate is necessary but not sufficient. Internal equity audits sit alongside external benchmarking in any serious comp project now.
Where ERC fits
We publish four employer-reported survey reports drawn from Northeast Ohio data: the ERC Salary Survey Report, the ERC Wage Survey Report, the ERC Benefits Survey Report, and the ERC Policies & Practices Survey. We also co-sponsor the EAA National Executive Compensation Survey.
If you’re running a comp project and want help reading the data, blending sources, or building a defensible market rate, our compensation consulting team does this work every day with Northeast Ohio employers. We can review what you’ve pulled, help you decide which percentile to target, or run the project end-to-end.
