International hiring breaks on two questions you don't want to answer in the hiring conversation: "What's their OTE?" and "Why?" Getting it wrong by 10–20% in either direction costs real money — under-offer and you lose the hire; over-offer and you distort the local market and inflate your peer costs. The reference tables HR hands you are usually 12–24 months out of date, and every recruiter has an opinion that happens to favor the offer they're trying to close.
This tool gives you a defensible starting point. Enter a reference-market OTE (typically US/SF Bay Area or your largest market), pick a target geography, and get the localized OTE with the multiplier shown explicitly. Also includes a side-by-side comparison table for all 13 geographies so you can see how the same role benchmarks globally.
The multiplier — what it includes and what it doesn't
What the multiplier captures
The geo multiplier reflects observed sales-comp differentials between markets — a blend of cost-of-labor (wages for similar skills), cost-of-living, and local market competitiveness. For sales roles specifically, it weights toward what competitive employers actually pay, not just what's "fair" by pure cost-of-living math.
What it doesn't capture
Tenure, seniority, product differentiation, benefits and equity mix, hiring-market competition for specific skills, currency volatility, and recent local market movements. For a senior AE in Berlin with 8 years in a hot product segment, the multiplier is a starting point — your recruiter's real-time market read should adjust ±10%.
Reference market choice matters
Multipliers are relative to a chosen reference. If you reference SF Bay Area (index 1.00), other US markets land 0.72–0.95. If you reference a lower-cost market, US-based roles look expensive. Pick the reference market that represents your largest rep population — the math is consistent across geographies regardless of which is the reference.
Absolute OTE numbers go stale quickly — market rates move 5–15% per year. Multipliers (ratios between markets) move 10x slower than absolute rates. By building on your own current reference OTE rather than a published absolute, the tool stays useful even as your internal comp ranges evolve. If your reference number is current, the localized numbers are current too.
Geo Differential Calculator
Enter reference OTE. Pick target geography. We localize and compare.
ℹ️ How this tool works +
The question it answers: Given a role's OTE in one market, what should we offer for the equivalent role in another market?
What to enter:
- Reference OTE ($) — the full-year OTE for this role in your reference market.
- Reference market — the market the reference OTE is calibrated to. 13 options available.
- Target market — the geography you're pricing the role for.
What you'll get back:
- Localized OTE for the target market, with multiplier shown.
- Delta vs reference (both $ and %).
- Side-by-side comparison table across all 13 geographies.
Multipliers are directional and market-observed. Validate with a local recruiter for senior roles or specialist skills where ±10–15% adjustments are common.
Benchmarks, ranges, and default values in this tool reflect Falcon's practitioner experience across consulting engagements. They are directional starting points, not substitutes for market survey data. For binding compensation decisions, validate key figures against Radford, Mercer, Carta, or WorldatWork survey data for your specific geography, industry, and company stage.
How to use the output
Use the number directly when…
The role is mid-level (2–7 years experience), standard sales skills, in a market with adequate candidate supply, and you're doing a greenfield compensation design. The multiplier-based number is a defensible starting point — present it as "market-benchmarked" with the multiplier shown so candidates and hiring managers can see the logic.
Deviate upward (+5% to +15%) when…
Hiring for a specialized skill in a hot market (e.g., enterprise AE for AI products in SF), the candidate has a competing offer, you're pricing a leadership role (VP/Director where local peer data is thin), or currency volatility has moved sharply. The multiplier doesn't capture skill-specific premiums.
Deviate downward (−5% to −10%) when…
The role is junior or entry-level (multiplier tends to overstate for SDRs and first-year reps), the market is in a hiring freeze phase, or the candidate is transitioning from a higher-paid role in another function and the OTE is still strong relative to their prior comp.
Hiring a rep in India at SF Bay Area OTE is tempting (great candidates, fast hires) but creates long-term problems. The rep quickly becomes the highest-paid person in your India office, local peer dynamics get weird, and when you hire a second Indian rep you either repeat the premium or create internal pay-equity problems. Stick close to local-market rates even when you can afford to pay more.
Hiring across multiple geographies?
We help SalesOps and HR teams build defensible geo-differential frameworks for sales comp. Book a 20-minute review.
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Observed sales-role OTE differentials across enterprise SaaS and tech companies, weighted toward competitive-market behavior rather than pure cost-of-living. Directional, not authoritative — update annually and validate with current market data for senior or specialized roles.
Use the "Remote (US-based)" option for US-remote hires — this reflects the blended market rate that most remote-first companies use. For European remote hires, use "Western Europe (avg)". For country-specific hub strategies (e.g., "remote but only from specific cities"), use the specific city multiplier.
Both should scale by the same multiplier so pay mix stays consistent. Variable-only scaling (base at parity, variable scaled) creates weird dynamics where a rep in a lower-cost market has to over-attain to match US peer earnings. The OTE ratio is the correct scaling point.
Annually at the start of your fiscal cycle. More often if there's been significant local market movement (currency shift, major local hiring freeze or boom, regulatory change). Multipliers evolve more slowly than absolute rates, so annual refresh is usually enough.