Multi-Currency Pricing Calculator

How to build a multi-currency pricing table

SaaS localization is a pricing decision, not a translation decision

Translating a marketing site into Hindi, Portuguese, and Spanish is fine, but it does not lift conversion if the price-to-income mismatch is the problem. SaaS localization in 2026 means delivering both the language a buyer reads and the price they can plausibly pay. The calculator focuses on the second half: given a base USD price and 40 country profiles, what should the local sticker actually be?

The blended price for a $29/mo SMB SaaS in India lands around ₹599–₹699 at default weights — not the ₹2,436 a flat FX conversion produces. That single change typically moves the price from 33% of estimated monthly disposable income (critical churn risk) into the 0.7–1% range (low risk), which is the actual constraint. The math is the easy part; deciding to ship the discount is the company decision.

Localized pricing: the four-method blend, line by line

For each enabled country the engine produces four candidate prices and one blended recommendation, then snaps to the local charm convention.

Worked example: base $29, India. FX = ₹2,436, PPP = ₹632, Big Mac = ₹1,221, GNI = ₹77. Blend (10/50/20/20) = 0.10×2436 + 0.50×632 + 0.20×1221 + 0.20×77 = ₹819. At 70% strength, effective = 0.70×819 + 0.30×2436 = ₹1,304 — charm rounded to the nearest ladder value (₹1,299 or ₹1,499). For a more aggressive PPP-weighted blend (20/60/10/10), the same inputs land near ₹430.

VAT and GST in 2026 — who charges what

Standard rates the calculator applies to inclusive prices, current to 2026:

Brazil completed its tax reform in 2026, replacing legacy ICMS handling for digital services with the combined CBS (federal) and IBS (state/municipal) regime — the calculator uses the combined effective rate. EU sellers traditionally quote inclusive (sticker = total); US sellers quote exclusive. Toggle the mode in the input panel — every country row updates both columns.

Charm pricing across currencies

Once the blend produces a raw localized price, the calculator snaps it to the country's charm convention. This matters more than it sounds: a price of ₹247.30 reads as broken in a market where the entire ladder runs in 99-suffix steps.

The Charm Rounding dimension on the report card scores how well your output prices honour the local convention; if it drops below A, a country is rendering with awkward decimals and should be re-anchored to the nearest ladder value before shipping.

Churn risk: the price-to-income ratio threshold

An emerging-market customer who pays a meaningful fraction of their monthly disposable income for software churns at multiples of the rate of a developed-market customer paying the same amount in absolute dollars. The calculator estimates monthly disposable income as GNI per capita × 0.42 ÷ 12 (the Atlas-method approximation of disposable share) and bands the resulting price-to-income ratio:

These thresholds drive the multipliers in the global-MRR projection. A high-risk market contributes 78% of its theoretical MRR; a critical-risk market contributes 55%. Lowering price by 30–40% in those markets often raises projected revenue, not lowers it, because the retention curve is the binding constraint. The heatmap surfaces which countries to re-tier, and the "Reverse: max base for churn ceiling" mode tells you the highest base USD that keeps every enabled country at or below medium risk.

Geo pricing in practice — what the billing layer handles

The price table is a configuration artefact. The billing layer is where it ships. Three architectures dominate in 2026:

The MRR delta between flat-USD billing and a localized 4-method blend is rarely small. For an SMB SaaS targeting India, Brazil, Vietnam, and the Philippines, the projected lift typically runs +30% to +60% on the same customer count — driven entirely by recovering paying users who otherwise churn at the flat-USD price.

Why "international pricing" queries return 10 incumbent pages

A search for "international pricing" today returns Harvard Business Review, HubSpot, Shopify, Paddle, Bain, McKinsey, Deloitte, and Harvard Business School — ten domains in the top ten. None of those pages is a calculator; they are 2,000-word essays on pricing strategy. The query intent is informational, not interactive — buyers researching how to think about international pricing strategy land on essays.

This calculator targets the operator who has already decided to localize and now needs the actual numbers — a different intent. Building the price table itself takes about four minutes once you pick a strength and a blend. The static text on this page exists so the math is auditable; the interactive layer above is where the work happens.

Worked example: a $29/mo SaaS across 8 markets at 70% strength

At 50,000 MAU split with 30% US, 6% UK, 5% Germany, 3% Australia, 2.5% Japan, 4% Brazil, 2% Mexico, 10% India (+ smaller shares for the other markets), the projected global MRR at 70% strength is materially higher than the same customer base on flat $29 — the lift comes almost entirely from converting India, Brazil, Vietnam, and Indonesia traffic that otherwise churns. The exec deck overlay (E key) renders this configuration as a one-pager suitable for board prep.

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