Geographic Pay Differentials: How HR and Compensation Teams Can Build Fair, Market-Aligned Location Pay

Introduction

Geographic pay differentials are adjustments to base salary—typically expressed as a percentage above or below a national anchor—that reflect cost-of-labor differences across U.S. locations. For HR and compensation teams managing employees in multiple geographic locations, these differentials have become essential to remain competitive, control costs, and maintain internal equity. This article is written specifically for U.S.-based compensation professionals, not individual job seekers, and focuses on the practical decisions required to determine geographic pay differentials that are defensible, transparent, and aligned with modern labor market conditions.

The pressure to get location-based pay right has intensified. Pay transparency laws in states like California, Colorado, New York, and Washington now require salary ranges on job postings—and those ranges often vary by geographic location. Remote work has scattered workforces across metropolitan areas and rural regions alike, making it harder to justify a single national pay approach. Meanwhile, volatile labor markets mean that salary data from 12 months ago may already be obsolete for high-demand roles.

Direct answer: Geographic pay differentials are percentage or flat-dollar adjustments applied to a reference pay level (such as a national median or headquarters market rate) to account for cost-of-labor variations across cities, states, or regions. Most companies apply these adjustments to base salary, using market rates from salary surveys and real-time benchmarking tools to set location-specific pay levels.

Scope: This article covers definitions, calculation methods, implementation frameworks, remote work considerations, review cadences, and the technology and tools that support geographic pay strategies. It does not address global mobility, expatriate tax implications, or advice for individual salary negotiations.

What you will learn:

How to decide whether your organization needs geographic differentials
How to select a national anchor market and appropriate level of geographic granularity
How to build and maintain geo zones using real-time salary data
How SalaryCube supports geo-differential workflows with daily-updated U.S. benchmarks
How to communicate location-based pay transparently and handle employee relocations

Understanding Geographic Pay Differentials

Before designing any policy, HR and compensation teams must align on foundational concepts. This section establishes the terminology, strategic rationale, and core design components that underpin every geographic pay strategy. The focus here is on U.S. labor market data and practices, where geographic differentials are driven primarily by cost of labor—what employers must pay to attract talent in a given market—rather than cost of living alone.

Geographic differentials connect directly to broader compensation strategy. They influence how you build salary ranges, set pay bands, conduct pay equity analyses, and communicate total rewards to candidates and employees. Without clarity on these foundations, later decisions about zones, percentages, and review cadences will lack coherence.

What Are Geographic Pay Differentials?

Geographic pay differentials are adjustments to a reference pay level—such as a national median or the pay rate in a headquarters city—to reflect cost-of-labor differences across U.S. locations. These adjustments are typically expressed as a percentage (e.g., +18% for San Francisco, −8% for Phoenix) or as a fixed dollar amount added or subtracted from a baseline.

Key terminology to clarify:

Cost of labor refers to what employers must pay to attract and retain talent in a specific market, driven by supply, demand, and competition for skills. This is distinct from cost of living, which measures the relative expense of housing, goods, and services for individuals.
Geographic differential and location-based pay are often used interchangeably, though some organizations reserve “differential” for the percentage adjustment and “location-based pay” for the resulting salary.
Geographic zones group similar markets together (e.g., Tier 1, Tier 2), while city-level pricing assigns unique differentials to each metro area.

Numeric example: If your national anchor for a Senior Product Manager is $150,000 and you apply an +18% differential for New York City, the NYC midpoint becomes $177,000. If Phoenix carries a −8% differential, the midpoint there is $138,000. These adjustments flow into your salary ranges—minimum, midpoint, and maximum—for each location.

Geographic differentials directly support pay transparency. When job postings show pay ranges that vary by location, defensible geo differentials explain why a role in San Francisco pays more than the same role in Des Moines. This transparency builds trust with candidates and reduces legal risk in states with disclosure requirements.

Why Organizations Use Geographic Pay Differentials

Organizations use geographic pay differentials for several strategic reasons:

Talent attraction and retention: Paying market rates in each location helps you remain competitive for local talent. Underpaying in a hot market like Seattle leads to offer declines; overpaying in a lower-cost market like Omaha inflates costs without improving hiring outcomes.
Internal equity: Employees performing the same job at the same level should experience comparable purchasing power and career value, even if their nominal salaries differ by location.
Cost control: When expanding into lower-cost markets, geo differentials allow you to capture savings without sacrificing competitiveness.
Compliance: State pay transparency laws require salary ranges on postings. Geo differentials provide the rationale for location-specific ranges, making compliance defensible.

Single national range vs. geo-differentiated ranges: A single national range works when your workforce is concentrated in one market or when pay levels are so high that local variations become immaterial. But once you’re hiring in five or more materially different markets—or when the spread between your highest- and lowest-cost locations exceeds 15–20%—a single range typically becomes unsustainable. You’ll either overpay in low-cost areas (eroding margins) or underpay in high-cost areas (losing candidates).

Geographic differentials also connect to workforce planning. When modeling site selection or headcount mix, compensation leaders can use geo differentials to quantify the cost difference between building a team in a high-value hub like San Francisco versus distributing roles across secondary markets like Austin, Denver, or Nashville.

Recognizing the value of geo differentials is the first step. The next is understanding the core design choices that shape your strategy.

Core Design Components of a Geo Pay Strategy

Every geographic pay strategy rests on three foundational design decisions:

Anchor market: Will you benchmark against a national composite (e.g., U.S. median) or a specific city (e.g., San Francisco or your headquarters location)? The anchor sets the baseline from which all differentials are calculated.
Level of geographic granularity: Will you price at the city level (NYC, SF, Austin), by state, or by geographic zones (Tier 1, Tier 2, Tier 3)? Granularity affects precision, administrative complexity, and employee understanding.
Component(s) of pay that vary by location: Will only base salary adjust by location, or will you also differentiate short-term incentives, sign-on bonuses, or other elements? Equity grants are typically tied to role level, not location.

These choices drive downstream decisions about administration, communication, and technology. For example, city-level pricing requires more frequent data updates and more sophisticated HRIS configuration than zone-based pricing. Similarly, percentage-based differentials scale with salary level, while flat-dollar differentials treat all employees in a location equally.

Later sections will cover each component in depth. For now, understand that clarity on these three decisions is the prerequisite for building or refining your geo pay framework.

With the concepts in place, the next step is understanding how geographic pay differentials work in actual pay ranges, offers, and adjustments.

How Geographic Pay Differentials Work in Practice

This section shifts from definitions to application. Here, we examine how geographic differentials manifest in pay ranges, offer letters, and ongoing salary administration for U.S. employers—whether you operate a handful of offices, manage a hybrid workforce, or support a fully distributed team across different locations.

Common Models for Applying Geographic Pay

Most companies use one of four models to apply geographic pay:

1. Single national range (no geo differentials): One salary range applies everywhere. This approach simplifies administration and avoids perceptions of unfairness but risks overpaying in low-cost markets and underpaying in high-cost metros. Example: A software engineer earns $140,000–$180,000 regardless of whether they work in San Francisco or Boise.

2. HQ-based pay with premiums/discounts: The headquarters city sets the anchor, and other locations receive percentage adjustments. Example: If HQ is in New York at 100%, Denver might be 90% and Atlanta 85%. This model is intuitive but can feel arbitrary if employees don’t understand why HQ is the benchmark.

3. City-level differentials: Each major metro receives a unique differential based on local labor market conditions. Example: San Francisco at +22%, Seattle at +18%, Austin at +5%, and Phoenix at −8%. This model offers high precision but requires robust salary data and more complex administration.

4. Geographic zones or tiers: Locations are grouped into 3–5 tiers based on cost of labor. Example: Tier 1 (SF, NYC, Seattle) at +15–25%; Tier 2 (Boston, LA, DC) at +5–10%; Tier 3 (national baseline) at 0%; Tier 4 (lower-cost metros) at −5–10%. This approach simplifies administration while preserving meaningful differentiation.

Trade-offs to assess:

Precision vs. simplicity: City-level pricing captures local nuance; zones reduce admin burden.
Employee perception: Zones feel less personal than city-specific rates, which can reduce pushback.
Administrative overhead: More granular models require more frequent updates and tighter HRIS integration.

What Parts of Pay Should Vary by Location?

Geographic differentials typically apply to base salary—the fixed component of cash compensation. Some organizations also adjust short-term incentives or sign-on bonuses by location, though this is less common.

What is typically not geo-adjusted:

Equity grants: Stock options, RSUs, and other equity awards are usually tied to job level and role, not location. This avoids complexity in grant administration and ensures equity serves as a unifying element across the workforce.
Core benefits: Health, retirement, and leave benefits are generally standardized, though some employers offer location-specific perks (e.g., commuter benefits in transit-heavy cities).

Implications for pay equity analysis: When conducting pay equity studies, location must be included as a control variable. Two engineers at the same level but in different locations will have different base salaries if geo differentials apply. Your analysis should account for this so that location effects don’t distort findings on gender, race, or other protected characteristics.

Example: An engineer in San Francisco earns $180,000 base; an engineer in Denver at the same level earns $156,000. Both receive identical equity grants of 2,000 RSUs. In a comp ratio analysis, both may appear at 100% of their location-adjusted range midpoint—even though nominal pay differs by $24,000.

Illustrative Example: Multi-City Pay for a Single Role

Let’s construct a concrete example. Consider a Senior Product Manager role with a national anchor midpoint of $150,000.

Location	Differential	Adjusted Midpoint	Range (±15%)
San Francisco	+20%	$180,000	$153,000–$207,000
Denver	+5%	$157,500	$133,875–$181,125
Dallas	0% (baseline)	$150,000	$127,500–$172,500
Des Moines	−10%	$135,000	$114,750–$155,250
Step-by-step application:

Start with the national anchor midpoint ($150,000).
Apply each location’s differential (e.g., +20% for SF yields $180,000).
Build the range by applying your spread (e.g., ±15%) to the adjusted midpoint.
Use these ranges for offers, promotions, and internal mobility decisions.

Key observations:

The gap between San Francisco and Des Moines is $45,000 at the midpoint—a 33% spread.
Talent competition in San Francisco justifies the premium; hiring in Des Moines offers cost savings.
Budget planning must account for headcount distribution across locations to model total labor cost accurately.

With these practical mechanics in hand, we now turn to the formal process of building a geographic pay differential framework.

Building a Geographic Pay Differential Framework

This section is the “how-to” guide for HR and compensation teams ready to formalize their approach to geographic pay. The examples here assume U.S.-based exempt roles, but the principles apply broadly to any workforce distributed across multiple states or cities.

Step-by-Step Process for Designing Geo Differentials

Run a formal design process when your organization hits 100+ employees, enters three or more materially different markets, or faces new pay transparency requirements. Here are the recommended steps:

Define your compensation philosophy and geographic stance. Decide whether you’ll pay to local market medians, a specific percentile (e.g., 60th), or a national composite. Document the rationale.
Select your anchor market. Choose between a national composite (recommended for distributed workforces) or your headquarters city (simpler to communicate but potentially distorting if HQ is an outlier).
Decide on geographic granularity. Use your current workforce distribution and hiring plans to determine whether city-level pricing, state groupings, or zones best fit your needs.
Gather market data for target locations. Use real-time salary benchmarking tools like SalaryCube DataDive Pro and Bigfoot Live for up-to-date cost-of-labor signals across U.S. locations. Supplement with legacy salary surveys where needed, but recognize their lag.
Calculate preliminary differentials. For each location or zone, express the differential as a percentage vs. the anchor market. Model the impact on your current employee base.
Model scenarios for cost impact, hiring velocity, and internal equity. Use unlimited reporting from SalaryCube to run sensitivity analyses on budget, offer competitiveness, and pay equity.
Stress-test with stakeholders. Share proposed differentials with leaders, legal, and DEI stakeholders. Identify concerns before rollout.
Document policies, guardrails, and decision rights. Specify who approves exceptions, how relocations are handled, and how often differentials are reviewed.

Choosing City-Level vs. Zone-Based Differentials

This decision is pivotal for administration and employee understanding. The right choice depends on your workforce distribution, data maturity, and comp tech stack.

City-level pricing:

City-level differentials assign a unique percentage to each metro area (e.g., San Francisco at +20%, Austin at +5%, Phoenix at −8%). This model offers high precision and aligns pay tightly with local market rates.

Best for: Large enterprises with heavy concentration in a few high-cost metros, sophisticated HRIS/comp systems, and dedicated compensation staff.
Pros: Maximum competitiveness in each market; clear rationale for candidates.
Cons: Higher maintenance burden; more complex communication; requires robust, frequently updated salary data.

Zone-based pricing:

Zones group similar markets into tiers. For example:

Zone 1 (+15–25%): San Francisco, New York, Seattle
Zone 2 (+5–10%): Boston, Los Angeles, Washington DC
Zone 3 (baseline): National average
Zone 4 (−5–10%): Lower-cost metros and rural areas

This approach simplifies administration and reduces the number of distinct pay structures you manage.

Best for: Mid-sized companies, distributed workforces, organizations with limited comp resources.
Pros: Easier to explain and administer; fewer data points to maintain.
Cons: Less granular; may underpay in niche hot markets or overpay in cooler pockets within a zone.

Signals you’re ready for city-level pricing:

You have 500+ employees concentrated in 5+ distinct metros.
Your comp team has capacity for quarterly data refreshes.
You use a modern compensation platform with real-time data integration.

Signals you should stay with zones:

Your workforce is spread thinly across many locations.
You lack dedicated comp staff for ongoing maintenance.
You want simpler communication with employees and candidates.

Percentage vs. Flat-Dollar Differentials

Two main approaches exist for calculating geographic pay differences:

Percentage differentials: Apply a percentage to the anchor salary. Example: +15% for NYC means a $100,000 anchor becomes $115,000 in NYC; a $200,000 anchor becomes $230,000.

Flat-dollar differentials: Add or subtract a fixed amount by location. Example: +$15,000 for NYC means both a $100,000 and a $200,000 anchor rise by the same $15,000.

Criterion	Percentage	Flat Dollar
Equity impact	Increases gaps at higher levels	More equitable across bands
Admin simplicity	Scales automatically	Requires band-specific rules
Transparency	Easy to explain	May feel arbitrary to some
Risk of underpaying	Low at all levels	Senior roles in high-cost markets
Guidance: Most private-sector organizations use percentage differentials because they scale naturally with salary level and are straightforward to apply. Flat-dollar amounts are more common in public-sector or union environments where equity across pay grades is prioritized.

Choose the approach that aligns with your philosophy and data maturity. Then build processes to review and maintain differentials over time—the subject of the next section.

Keeping Geo Differentials Current with Real-Time Market Data

Labor markets shift. The tech hiring surge of 2021 and the corrections of 2023–2024 demonstrated how quickly salary data can become obsolete. Static differentials based on annual salary surveys leave HR teams exposed to market drift, compliance risk, and offer declines in competitive roles.

Setting Review Cadence and Triggers

Baseline recommendation: Conduct a full review of geographic differentials annually. For high-volatility roles (e.g., software engineering, data science, AI/ML), add interim checks at the 6-month mark or when market signals change.

Triggers for off-cycle review:

Hiring difficulty: Sudden rise in offer declines or extended time-to-fill in a specific location.
Cost-of-labor shifts: Real-time tools like Bigfoot Live reveal significant movement in local pay levels.
Regulatory changes: New pay transparency requirements in a state (e.g., Illinois, Minnesota).
Business changes: Entering a new market, closing an office, or acquiring a company with different pay practices.

Distinguish structural shifts from temporary blips. A 10% jump in one quarter for a single role may reflect a talent war that cools off. Use 3–6 months of trend data before adjusting differentials. For short-term spikes, consider spot bonuses or sign-on incentives rather than permanent range changes.

Data Sources and Methodology Considerations

Recommended data stack:

Real-time salary benchmarking (primary): SalaryCube DataDive Pro and Bigfoot Live provide daily-updated U.S. salary data without survey participation requirements.
Legacy salary surveys (supplemental): Use for validation and historical context, but recognize that survey data often lags the market by 12–18 months.
Internal pay data: Calibrate differentials against your own employee population for internal equity and pay gap analysis.

Risks of crowd-sourced data: Self-reported salary data from job boards or employee forums lacks methodological rigor and is vulnerable to outliers, selection bias, and manipulation. For defensible decisions—especially under pay transparency laws—rely on structured, transparent data sources with documented methodology.

Why methodology matters: When auditors, employees, or regulators ask why you pay differently by location, you need a clear, defensible answer. SalaryCube’s methodology and security documentation explains how data is collected, validated, and updated, giving you the audit trail you need.

Operationalizing Updates Across Systems

Once you update differentials, changes must flow into:

Pay ranges and bands in HRIS/comp systems: Update your salary structures so that recruiters and managers see current ranges.
Job descriptions and postings: Use tools like SalaryCube Job Description Studio to generate job descriptions with geo-specific ranges baked in.
Offer letter templates: Ensure templates pull the correct location-adjusted range for each candidate.
Internal mobility and relocation policies: Update guidelines so that HR and managers apply consistent rules when employees move between locations.

Best practices for version control and audit trails:

Date each differential set and store historical versions.
Document the rationale for each update (e.g., “Q2 2025: Seattle differential increased from +15% to +18% based on Bigfoot Live data showing 6% market movement”).
Use SalaryCube’s unlimited reporting exports (CSV, Excel, PDF) for clean uploads and archival.
Assign designated owners for differential tables and require sign-off for changes.

With the operational foundation in place, the next challenge is adapting geographic pay for remote and hybrid work—a reality for most U.S. employers today.

Geographic Pay Differentials in a Remote and Hybrid World

Since 2020, remote work has reshaped how employees are distributed across the country. Many organizations now have employees working remotely in states where they have no office, complicating location-based pay strategies. This section focuses on U.S.-based employees working remotely across different locations—not global mobility or expatriate assignments.

Policy Archetypes for Remote Location Pay

Organizations typically adopt one of three archetypes for paying remote employees:

1. Location-based pay (fully tied to where the employee lives/works): Employees receive the salary for their work location, regardless of where the office is. If an employee moves from San Jose to Boise, their pay adjusts to Boise market rates.

When used: Enterprises with mature geo frameworks, organizations prioritizing cost control, employers subject to strict pay transparency laws.
Pros: Defensible, equitable, consistent with local labor market conditions.
Cons: Can feel punitive to employees who relocate to lower-cost areas; requires robust tracking and policy communication.

Example: An engineer hired in San Francisco at $180,000 moves to Salt Lake City. Under location-based pay, their salary adjusts to $150,000 (Salt Lake City differential of −17%).

2. Office-based pay (tied to a designated hub): Employees are paid based on their assigned office hub, not their home location, as long as they remain within a defined radius or region.

When used: Hybrid employers expecting regular in-office attendance, organizations with strong hub identity.
Pros: Simpler administration; avoids pay changes for moves within the hub’s catchment.
Cons: Can overpay if employee moves far from the hub; may create internal equity issues.

Example: An engineer assigned to the Denver hub earns Denver rates even if they live 60 miles away in a lower-cost town.

3. National or narrow-band pay (minimal or no geo differentials): Certain roles or levels receive national pay rates, ignoring location. This model is common for highly specialized or executive roles where talent is scarce.

When used: Startups competing for top talent nationally, roles with extreme demand and limited supply.
Pros: Simple to communicate; removes location as a variable in offers.
Cons: Overpays in low-cost markets; may not be sustainable at scale.

Example: A principal engineer earns $250,000 regardless of whether they work in Austin or Atlanta.

Handling Employee Location Changes

Clear guidelines prevent confusion and legal risk when employees relocate. Address the following scenarios:

Voluntary relocations (employee-driven moves):

Define whether pay adjusts up, down, or stays flat when employees move.
Specify the effective date for pay changes (e.g., 30 days after relocation confirmation).
Communicate the policy clearly in offer letters and employee handbooks.

Employer-directed moves (office closures, hub consolidations):

Determine whether employees affected by closures retain their original pay or transition to local rates.
Consider transition periods or one-time payments to ease the shift.

Temporary work-from-anywhere arrangements:

Set maximum durations for temporary relocations before pay policy applies (e.g., up to 60 days with no change; beyond that, local rates apply).

Recommended policy elements:

Notice periods and effective dates for pay changes.
Minimum time-in-location rules (e.g., 6 months) to prevent frequent toggling.
Communication scripts that transparently connect pay changes to the geo policy.

Tools like SalaryCube can rapidly reprice roles when employees relocate, supporting quick but defensible decisions without manual recalculation.

Balancing Fairness, Transparency, and Cost

Geographic differentials inevitably raise questions about fairness. Two people doing the same job may earn different salaries because of where they live. HR teams must balance:

Pay equity analyses: Include location as a control variable. Geo differentials are legitimate, non-discriminatory factors—but only if applied consistently and documented.
Employee morale: Transparency is the antidote to resentment. Employees accept location-based pay when they understand the rationale.
Budget targets: Finance teams appreciate the cost control that geo differentials provide—but only if savings don’t come at the expense of hiring velocity or turnover.

Messaging principles for internal communication:

Start from philosophy: “We align pay to local markets to remain competitive and fair.”
Use clear examples and published ranges, not opaque formulas.
Offer tools (like SalaryCube’s free compa-ratio calculator) or office hours for employees to explore their pay positioning.
Acknowledge trade-offs honestly: “Yes, some locations pay more—that reflects what it costs to hire and retain talent in those markets.”

Even well-designed policies face real-world friction. The next section addresses common challenges and practical solutions.

Common Challenges and Practical Solutions

Most HR and compensation teams encounter similar issues when implementing geographic differentials. These challenges are manageable with the right processes and tools.

Outdated or Inconsistent Market Data

Challenge: Using salary surveys that lag the market by 12–18 months leads to uncompetitive offers. Inconsistent data sources across roles or locations create internal inequities and erode trust.

Solution: Standardize on a modern compensation intelligence platform for U.S. data. SalaryCube’s DataDive Pro and Bigfoot Live provide real-time benchmarks updated daily, blending survey inputs with market signals. Document your methodology so decisions are defensible.

Set a minimum data freshness standard: no data older than 12 months for fast-changing roles like engineering or data science.

Administrative Complexity Across Locations

Challenge: Managing dozens of city-specific differentials leads to errors in payroll setup, confusion among HRBPs and recruiters, and inconsistent candidate offers.

Solution: Start with zones where possible to reduce the number of distinct differentials. Centralize your differential table and integrate it into your HRIS and comp tools. Use SalaryCube’s unlimited exports (CSV, Excel) for clean uploads and system integration.

Establish governance: designate owners for differential tables, maintain change logs, and document which jobs are geo-differentiated and which are not.

Employee Perception and Pay Equity Concerns

Challenge: Employees feel undervalued when they learn peers in other locations earn more for the same role. This perception can damage morale and retention.

Solution: Transparent communication is essential. Explain that market-based pay reflects labor market conditions, not employee value. Share the policy, the methodology, and the ranges openly.

Use consistent frameworks and audit regularly with pay equity tools. SalaryCube’s analytics can help isolate location effects in pay equity studies, ensuring that geo differentials don’t mask discrimination.

Aligning Geo Pay with Legal and Compliance Requirements

Challenge: Navigating state pay transparency laws when ranges differ by location creates complexity. Additionally, FLSA classification at different wage levels can shift overtime obligations.

Solution: Maintain documented rationale for location-specific ranges. When posting jobs, list the correct range for each location as required by law. Use SalaryCube’s FLSA Classification Analysis tool to avoid misclassification, especially when low-cost locations push salaries near exempt thresholds.

Collaborate with legal counsel when designing multi-state policies. Audit your ranges annually against evolving state requirements.

Conclusion and Next Steps

Geographic pay differentials are a lever for fairness, competitiveness, and cost control when grounded in defensible, real-time U.S. salary data. They enable organizations to compensate employees appropriately across different geographic areas, attract and retain talent in competitive markets, and maintain internal equity as workforces become more distributed.

Actionable next steps:

Audit your current location pay practices. Identify gaps between what you pay and what local markets require.
Choose or reaffirm your anchor market and geographic philosophy. Document the rationale.
Map your current footprint to a draft set of geo zones or key cities. Use workforce distribution and hiring plans.
Pilot updated differentials for a priority job family (e.g., engineering, product, sales) before scaling organization-wide.
Set a review cadence and data sources. Commit to annual reviews with interim checks for volatile roles.

Related topics to explore: Salary range design, pay equity analysis, FLSA classification, and job description development all connect directly to geographic pay strategy. Building competence in these areas strengthens your overall compensation infrastructure.

If you want real-time, defensible salary data that HR and compensation teams can actually use—including geographic differentials built on daily-updated U.S. benchmarks—book a demo with SalaryCube or watch interactive demos to see geo-differential workflows in action.

Additional Resources for HR and Compensation Teams

Use these resources as a toolkit while you build or refine your geographic pay differential strategy:

SalaryCube Salary Benchmarking: Geo-specific market pricing workflows with real-time data.
Bigfoot Live: Real-time cost-of-labor insights across U.S. locations, updated daily.
Free Tools: Compa-ratio calculator, salary-to-hourly converter, and more to model differentials.
Methodology and Security: How SalaryCube builds defensible U.S. salary data and geo differentials.
About SalaryCube: Our mission to make fair, transparent pay accessible to every organization.