Grow revenue
Localizing per country captures more buyers and unlocks revenue you're leaving behind.
+20–40%revenue
Wappier · industry research
Enter your base price in USD. Get App Store prices adjusted for local purchasing power across 175 countries.
| Country▲ | Code | Currency | Tier | Language | PPP suggested |
|---|---|---|---|---|---|
| Loading pricing matrix… | |||||
PPP = Purchasing Power Parity. In short: $10 isn't $10 everywhere. A price that's a coffee in the US can be a day's wages elsewhere. Adjusting prices by country means fair pricing — so more people can actually afford your app.
Each country is assigned to one of 5 tiers based on purchasing power, local app-subscription willingness-to-pay, price sensitivity, and pricing norms in that market. Tiers map to multiplier ranges applied to your base price:
0.90–1.20. High purchasing power, mature subscription market (US, UK, AU, JP, DE…).0.70–0.90. Good purchasing power, more price-conscious than the US (FR, IT, ES, KR…).0.45–0.70. Growth markets where US pricing hurts conversion (BR, MX, PL, TR…).0.20–0.45. Large user bases needing meaningful PPP discounts (IN, ID, PH, VN…).0.10–0.25. Low willingness/ability to pay monthly (NG, PK, EG…).The pill on each row shows tier · multiplier · confidence. This is a curated dataset — not raw World Bank PPP.
base price × tier multiplier × FX rate, then snapped to a real Apple price point — preferring charm-priced endings like X9.99 (49.99, 99.99) over odd FX-derived prices (56.99, 73.99), with per-country conventions baked in (.90 in Brazil, whole-number tiers in JPY/KRW).
Click any price to copy the local-currency value, ready to paste into App Store Connect.
App Store Connect's auto-equivalent applies Apple's own FX margin (~5–15% over mid-market) plus local VAT/GST, so it often picks a slightly higher tier than a pure PPP × FX calculation.
Treat values here as a starting point — verify in App Store Connect before publishing.
That's the confidence level for each country's multiplier — based on how strong the underlying data is. High means large, well-documented markets (US, UK, JP, BR). Medium is reasonable data with some inference. Low is sparse data, often smaller markets extrapolated from regional peers. Treat low-confidence rows as starting points and validate with your own conversion data.
They're recommendations, not raw FX — based on purchasing power, local app pricing norms, mobile-subscription willingness-to-pay, localization relevance, and price sensitivity.
Always validate against trial conversion, paid conversion, retention, refund rate, and LTV by country.
Pricing tiers come from Apple's official price matrix — 842 price points across 175 territories. FX rates are pulled live from exchangerate-api.com (via open.er-api.com), with a hardcoded fallback if the API is unreachable.
Localizing per country captures more buyers and unlocks revenue you're leaving behind.
+20–40%revenue
Wappier · industry research
In countries like Switzerland and Norway, prices tend to run higher than the US. Match local pricing and earn more per customer.
+10–20%ARPU
Industry benchmarks
Pocket Trains saw revenue double in countries where prices were adapted to local purchasing power.
2×revenue
NimbleBit · Pocket Trains
Buyers refund less when prices feel fair. Renderforest cut refunds 60% after aligning pricing to local purchasing power.
−60%refunds
Renderforest
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