The Language Selection Problem#

You've decided to localize your app. Now what? With 7,000+ languages in the world and app stores supporting 40+, where do you start?

Choosing the wrong languages wastes time and money. Choosing the right ones can transform your business. This guide gives you a data-driven framework for making that decision.

The Framework: ROI-Based Language Selection#

Every language decision should be based on a simple formula:

Expected ROI = (Market Size × ARPU × Accessibility) / (Translation Cost + Maintenance Cost)

Let's break down each factor.

Factor 1: Market Size#

Not all languages are equal in terms of addressable market:

LanguageSmartphone Users (approx.)App Store Markets
English1.5BUS, UK, AU, CA, etc.
Chinese (Simplified)1.0BChina (special rules)
Spanish500MSpain, Latin America
Hindi450MIndia
Portuguese300MBrazil, Portugal
Arabic300MMiddle East, North Africa
French280MFrance, Africa, Canada
Japanese120MJapan
German100MGermany, Austria, Switzerland
Korean55MSouth Korea

But market size alone is misleading. India has 450M smartphone users, but ARPU is a fraction of Japan's 120M.

Factor 2: Average Revenue Per User (ARPU)#

ARPU varies dramatically by market:

MarketRelative ARPUBest For
United StatesVery HighAll app types
JapanVery HighGaming, lifestyle
South KoreaVery HighGaming, entertainment
Germany/DACHHighProductivity, business
United KingdomHighAll app types
FranceHighLifestyle, utility
AustraliaHighAll app types
BrazilMediumSocial, entertainment
IndiaLowVolume play
Southeast AsiaLowVolume play

Key insight: 5 languages covering high-ARPU markets often outperform 15 languages covering low-ARPU markets.

Factor 3: Competition#

Less competition means easier visibility:

  • English: Extremely competitive — millions of apps
  • Japanese: Moderate competition for Western apps — an advantage
  • Korean: Lower competition for non-gaming apps
  • German: Moderate — many apps don't localize into German
  • Portuguese (Brazil): Lower competition, massive market

Pro tip: Check how many of your direct competitors are localized in each language. Gaps are opportunities.

Factor 4: Translation Complexity#

Some languages are more complex (and potentially more costly with human translators):

ComplexityLanguagesWhy
LowSpanish, French, Portuguese, ItalianSimilar structure to English
MediumGerman, Dutch, Polish, SwedishSome structural differences
HighJapanese, Korean, ChineseDifferent writing systems, cultural adaptation
HighArabic, HebrewRTL layout, different number systems

With AI translation, the cost difference is minimal. But testing and cultural review may take more effort for high-complexity languages.

The Tier System#

Based on the factors above, here's a practical tier system:

Tier 1: Start Here (Best ROI)#

LanguageWhy
Spanish500M speakers, medium ARPU, easy translation
GermanHigh ARPU (DACH), many apps don't localize
French280M speakers, high ARPU, covers multiple markets
JapaneseVery high ARPU, lower competition for Western apps
Portuguese (BR)200M+ in Brazil alone, growing market

Translate to Tier 1 first. These 5 languages typically capture 60-70% of the international opportunity.

Tier 2: Expand Here#

LanguageWhy
KoreanVery high ARPU, especially for gaming
ItalianDecent ARPU, underserved market
DutchHigh ARPU, small but affluent market
Chinese (Simplified)Massive market, but app store restrictions
PolishGrowing market, low competition

Tier 3: Maximize Coverage#

LanguageWhy
TurkishGrowing smartphone market
ArabicLarge market, few localized apps
SwedishHigh ARPU, small market
RussianLarge market, complex geopolitics
ThaiGrowing market, low competition

Data-Driven Decision Making#

Use Your Own Data#

The best language decisions come from your existing data:

  1. App Store Analytics: Check "Sources" in App Store Connect → which countries already show interest?
  2. Google Play Console: Check "User acquisition" → which countries have organic installs?
  3. Website Analytics: If you have a landing page, which countries visit most?
  4. Support Requests: Are you getting requests in other languages?

Example: Data-Driven Decision#

Scenario: A productivity app sees this in analytics:

CountryOrganic VisitsCurrent Language Support
Germany2,500/monthNone
Japan1,800/monthNone
Brazil1,200/monthNone
France900/monthNone
Spain800/monthNone

Decision: German and Japanese first (highest organic interest + ARPU), then Portuguese and French.

Special Considerations#

App Category Matters#

Different categories perform differently by market:

  • Gaming: Japan, South Korea, China dominate spending
  • Productivity: DACH (German-speaking), Nordic countries
  • Social: Latin America, Southeast Asia (volume)
  • E-commerce: Follows local market maturity
  • Health & Fitness: US, UK, Germany, Australia

Chinese Market: Special Rules#

Localizing for China requires more than translation:

  • App stores are fragmented (no Google Play)
  • Government regulations and content restrictions
  • Different social platforms (WeChat, Weibo)
  • Consider Chinese (Simplified) for the broader Chinese-speaking market outside mainland China

Latin American Spanish vs European Spanish#

You may need separate localizations:

  • Latin American Spanish: Preferred in Mexico, Colombia, Argentina, etc.
  • European Spanish: Used in Spain
  • Key differences in vocabulary, informal pronouns (tú vs. vos), and expressions

For most apps, Latin American Spanish covers the larger market.

The Budget Factor#

With shipglobal.dev's pay-per-use pricing, adding languages is incredibly affordable:

LanguagesEstimated Cost (10,000 strings)
5 Tier 1~€15
10 (Tier 1+2)~€25
15 (All tiers)~€35

At these prices, the question shifts from "can we afford it?" to "why wouldn't we?"

Step-by-Step Action Plan#

  1. Analyze your data — check existing traffic and downloads by country
  2. Pick 3-5 Tier 1 languages based on your app category and data
  3. Localize and launch — translate strings + App Store metadata
  4. Measure for 4-6 weeks — track downloads, revenue, and engagement by market
  5. Optimize top performers — improve keywords, screenshots, descriptions
  6. Add Tier 2 languages based on results
  7. Repeat until diminishing returns

Conclusion#

Choosing target languages isn't guesswork — it's a data-driven decision. Start with the languages that offer the best combination of market size, ARPU, and low competition.

For most apps, starting with Spanish, German, French, Japanese, and Portuguese covers the largest opportunity with the least complexity. Then let your data guide the expansion.

The cost of trying is low. The cost of not trying is months of missed international revenue.