Geographic Differentials

A geographic differential (or "geo diff") is a percentage adjustment applied to U.S. national market pay data.

You use it when local market data isn't available or when you want a consistent global pay structure.

Here's how it works:
Start with the U.S. national market rate → apply the location percentage (the geo diff) → use that to set pay ranges for that country or region.

We review geo diffs annually for each location.

They reflect both cost of labor trends (what companies pay in that market) and cost of living (how expensive it is to live there), drawing from multiple reliable economic and labor market sources to ensure accuracy and reviewed by compensation experts.

Geographic differentials give you a simple, scalable way to set pay across countries without maintaining many separate local datasets.

They help you:

• Keep ranges consistent across locations

• Maintain a global structure that’s easy to manage

• Provide clear guidelines, especially remote or distributed teams

• Avoid unreliable or sparse local market data

It’s a clean, defensible framework.

When to use Geographic Differentials:

• Your team is remote or spread across many regions

• You want a simpler way to manage pay ranges without maintaining local benchmarks for every country or metro area 

• Your goal is to create a transparent, scalable global pay structure

• Local pay data for a region is very limited

Many companies use geo diffs because maintaining local ranges across the world isn’t realistic or sustainable.

In the Company Profile, when you select “Geographic Differential” (vs. the Local Market Data option) for your market data cut approach:

For U.S. employees

We apply one of three tiers based on common labor market patterns:

• 115% for San Francisco Bay Area, New York City Area

• 110% for Austin, Boston, Los Angeles, Seattle

• 100% for U.S. national (used for most other locations)

These tiers anchor pay differences without requiring you to manage dozens of city-specific data cuts.

For employees outside the U.S.

We apply a percentage relative to the U.S. national average.

Examples:

• UK (All) = 80%

• Italy = 60%

• India = 40%

These values reflect real pay practices across global markets.

Pay ranges are then generated using the same structure you set for U.S. roles, just scaled by a location-based multiplier.

Kamsa’s geographic differential (or "geo diff") reflect cost of labor (what companies pay in that market) and cost of living (how expensive it is to live there) and reviewed by compensation experts.

For each country, we:

• Analyze HRIS-sourced salary data (real local market data) for the same job family and level

• Benchmark the local pay against the U.S. national rate before converting it into the geographic differential %

• Round to the nearest 5 or 10% to keep structures clean

• Review at least annually to ensure accuracy

• Update geo diff percentages when labor markets shift

This prevents small or uneven datasets from creating misleading swings in your global pay ranges and keeps the structure simple, consistent, and trustworthy.