The Free Trap: Why Free Data Isn’t All It’s Cracked Up To Be

The internet is a great and wondrous thing, where with just a few key word searches, you can find anything and everything, including pay data. But is typing “software engineer salary” into your search engine and then using the information you find really the best way to figure out what to pay for your jobs? Here are five questions to consider if you’re thinking about using free salary data to make pay decisions.

1. Do you know where the data is coming from?

Has it been collected from employees, employers, recruiters or job postings? Is the data skewed towards large Fortune 500 companies, or those only in major metro areas from a particular industry? These factors, in particular, are important to know because organization size, location and industry all tend to heavily influence pay.

2. Has the data been validated?

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When looking at free salary information online, it may not be readily apparent how the information was derived. Do you know the methodology used to generate the data? For example, are you looking at salaries that are “averages of averages”? Do you know if the data was scrubbed to remove extreme or nonsensical outliers? Knowing the answers to these kinds of questions is key because they get at the heart of whether or not you can trust the data.

3. Is the data current?

Pay data isn’t stagnant; the market for jobs across different locations is changing all the time, which is why it’s important to know whether the information you’re looking at online is current, a few months old, or reflects pay from a year or more ago. If you don’t know, then you run the risk of underpaying for a hot job or overpaying for a job where the market has gone down. Consider jobs in the oil and gas industry, where pay was hot from 2011 into 2014 but then turned downward in 2015 as oil prices dropped. If the free salary data you’re looking at for a Mechanical Engineer in the oil industry is more than a year old, then you probably don’t want to use it to make an offer today.

4. Does the data reflect your organization’s compensation strategy?

When people talk about paying competitively to the market, remember that there isn’t just one “market”; your market is defined by your compensation strategy, which consists of the industries, organization sizes and locations where you compete for talent. If you’re a 100-person software development company in Boise, Idaho, does it make sense for you to use free salary data for a software engineer job that comes from Fortune 500 companies in San Francisco if you’re not actually trying to hire engineers there? On the other hand, if you’re one of those larger companies in San Francisco and the free data you’re looking at represents a national average, then it might be too low for you to attract and retain the people you need in the Bay Area’s competitive labor market.

5. Is the job you’re pricing online the same as the job within your organization?

Job-specific factors like experience, education, skills and certifications all affect pay. Is the salary you found online for a software engineer with three years of experience or eight? Does it factor in the specific skills that you need in an engineer? For example, what if you need an in-demand skill like Hadoop that commands a market premium? In that case, free data likely won’t be specific enough or provide you with an understanding of how these kinds of factors affect pay for a job. Remember that the job title and function matter too. Does the free data include a job description or list of tasks so you can be sure you’re making an apples-to-apples comparison to your organization’s job? And are you able to drill down to the appropriate level of the job; i.e., Junior Software Engineer versus Senior Software Engineer?

If you don’t know the answers to these questions, then think carefully about whether that free salary data you found online is the truly the best foundation upon which to base your organization’s pay decisions. Since compensation is often an organization’s largest operating expense, it’s important to get it right. As they say, you get what you pay for.

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4 Comments on "The Free Trap: Why Free Data Isn’t All It’s Cracked Up To Be"

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Great points! Very insightful!

Anderson J.

All of these arguments can be made for paid data as well. It depends on the specific vendor so blanket statements are relatively meaningless.


Thank you, Sarah!


Yes, the same questions should be asked when purchasing salary data. When an organization purchases data from a vendor, they should absolutely expect the vendor to be able to answer these questions. With free data found through internet searches, though, there is no vendor/buyer relationship and thus often little or no opportunity to get solid answers to these questions, which is why using free data to make pay decisions may be ill-advised.