Use job postings to discover geodiffs

Should you pay less in Seattle than San Francisco?

To answer this, I suggest you look at salary ranges disclosed on job postings.

Many companies include multiple ranges for different cities on the same posting:

Seattle and Austin ranges are 71% of San Francisco for this role at Expedia (link)

For other companies, you can often find postings for two identical (or very similar) roles in different cities:

Washington ranges are 85% of San Joes for these roles at AMD (link, link)

After browsing a few job postings you can get a pretty good sense for how the market defines the cities:

Source: Job postings (link to spreadsheet)

50% pay the same in SF and Seattle. Seattle is 87% of SF for those that pay differently, and 93% overall across all 10 companies.

Why not look at real benchmarking data?

You could do that, too.

This is what the geodiff looks like in Compa for enterprise tech companies:

Source: Compa Index

Seattle is 93% of San Francisco in Compa’s data (offers from applicant tracking systems) — it happens to be exactly the same as the job postings.

This helps validate the job posting estimate.

…but I actually prefer the job posting data.

Here’s my point:

Match your analysis to the type of market information you’re trying to understand.

For something like geodiffs, using imperfect disclosures from a small number of companies is a decent estimate, and more useful than formal market data because you can company-specific insights.

Conversely, using pay range disclosures to price jobs is problematic. The jobs aren’t leveled and matched, the ranges are broad (and it’s hard to know where companies actually pay in the range, or if they’re disclosing the real range), and of course you can only see base salary, a small part of the story.

PS — whatever you’re disclosing is easily referenced by your competitors.

PPS — if your ranges are lower in Seattle, the best talent won’t accept less than SF-level pay anyway. 😉

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