How to Choose Languages to Localize First (A Practical Framework)

One of the most common questions I hear from teams when they start thinking about localization is simple but deceptively hard:

Which languages should we localize first?

As a developer, this usually comes up right after you’ve done the hard technical work. You’ve cleaned up your strings, added context, maybe migrated to Xcode string catalogs, and now the question shifts from how to localize to where to start.

I’ve seen teams get a lot of value from localization quickly. I’ve also seen teams create long-term maintenance work for themselves without much payoff. The difference usually comes down to this early decision.

This article walks through the framework I use and recommend for choosing your first languages, based on real signals instead of guesswork or generic “top 10 languages” lists.

Start With Real User Demand

Before looking at global language rankings, start with your own data.

Good signals include:

• App Store or Play Store downloads by country
• Website traffic broken down by locale
• Support emails or feedback written in another language
• App reviews that aren’t in English

If users are already downloading your app or struggling through an English UI, that’s a strong indicator that localization will have immediate impact. Even small percentages can matter if those users are active or paying.

If you’re early-stage and don’t have much data yet, that’s fine. Treat your first localization pass as an experiment, not a permanent commitment. The goal is to learn quickly, not to localize everything at once.

Balance Revenue Potential Against Effort

Not all languages cost the same to support.

Some increase effort more than others due to:

• Complex pluralization rules
• Longer average string lengths
• Right-to-left layout requirements
• Cultural adaptation beyond literal translation

At the same time, market size doesn’t always correlate with revenue. A language spoken by hundreds of millions of users may still convert worse than a smaller, higher-ARPU market.

A simple mental model I use is:

Impact = potential users × likelihood to convert ÷ ongoing maintenance cost

You don’t need precise numbers for this to be useful. Directionally correct decisions are already a big improvement over intuition alone.

Pay Attention to Platform Signals

Both iOS and Android give you useful hints if you know where to look.

On iOS:

• Check which storefronts are generating installs
• Look at the languages users choose for reviews
• Pay attention to TestFlight feedback language

On Android:

• Country install breakdowns tend to be even more granular
• Review language diversity often appears earlier

These signals matter because they reflect actual usage, not abstract market size.

High-Leverage Languages Many Teams Start With

This isn’t a prescription, but certain languages tend to be high-leverage for many apps:

• Spanish for broad geographic reach
• German for strong conversion in productivity and developer tools
• French for relatively consistent coverage across regions
• Japanese for high engagement and expectations around localization
• Brazilian Portuguese for a large, mobile-first market

The point isn’t the list itself. It’s understanding that some languages unlock multiple markets and learning opportunities at once.

Common Mistakes I See Teams Make

A few patterns show up over and over:

• Localizing too many languages at once
  This increases cost and complexity before you know what works.

• Choosing languages based on intuition alone
  “We think Europe sounds good” isn’t a strategy.

• Ignoring ongoing maintenance
  Every new string multiplies across languages. The first translation is always the cheapest one.

• Treating localization as a one-time task
  Apps change constantly. Localization needs to keep up with normal development.

How Automation Changes the Equation

This is where tooling choices start to affect strategy.

When localization is manual or disconnected from your codebase, every new language feels expensive and risky. When it’s automated and integrated into your development workflow, the marginal cost of adding a language drops dramatically.

That experience is exactly why I built String Catalog.

I wanted localization to work directly with Xcode string catalogs and feel like a natural extension of normal development. When your strings, context, and translations stay in sync automatically, you can confidently start with one or two languages, measure impact, and expand later without rethinking your entire setup.

As a result:

• You can start small without locking yourself in
• You can expand incrementally as real data comes in
• Localization stops being a reason to delay shipping

From a developer’s perspective, that’s the difference between localization being a blocker and localization being part of your regular release loop.

A Simple Starting Strategy

If you want something concrete, this is what I usually recommend:

1. Pick one or two non-English languages
2. Base the choice on your data, even if it’s limited
3. Ship, measure, and learn
4. Expand once the workflow feels boring

If localization feels boring, you’ve probably set it up correctly.

Final Thought

Choosing which languages to localize first isn’t about finding the perfect answer. It’s about making a defensible decision, setting up a workflow that scales, and leaving yourself room to grow.

Once you know which languages to support, the next challenge is keeping translations accurate as your app evolves. That’s the problem I built String Catalog to solve.