ASOGrade Guide

Translation vs. Localization for App Store Metadata

Why a word-for-word translated keyword list underperforms a properly localized one, with real vocabulary and tone examples across major markets.

Translation changes the language; localization changes the words people actually search

Translating your English App Store metadata into another language produces text that is grammatically correct and readable. It does not guarantee that the specific words you chose are the words users in that market actually type into App Store search — those are two different problems, and solving the first doesn't solve the second.

A translated keyword list is a reasonable starting point, not a finished one. The step that turns a translation into a proper localization is checking the actual local-language popularity of each candidate, and researching what a native speaker in that specific storefront searches, which sometimes diverges meaningfully from the dictionary-correct rendering of your original English term.

Vocabulary drift is real, not a rare edge case

Spanish alone illustrates this across its own storefronts: a phone is often 'móvil' in Spain and 'celular' across most of Latin America. A German compound noun for a single concept can have more than one valid written form. Brazilian and European Portuguese diverge on everyday words like 'bus' ('ônibus' versus 'autocarro') closely enough to how American and British English diverge, sometimes more.

None of these differences show up as a translation error — a translator would render each correctly for its target dialect. They show up as a research gap when a single English-to-everywhere translation pass is used to generate metadata for every storefront that nominally shares a language.

Tone and copy conventions differ by market, independent of vocabulary

Beyond individual word choice, the expected style of app copy varies by market. Japanese product pages tend toward detailed, feature-by-feature description copy. US listings favor concise, benefit-led copy. Brazilian copy tends toward a warmer, more conversational, enthusiastic register than either.

This affects promotional text and description more directly than the indexed keyword fields, since those are the fields users actually read in full. But it's part of the same underlying point: a straight translation optimizes for linguistic correctness, not for matching a market's actual expectations and search behavior.

A workable process for turning a translation into a localization

Start from a translated baseline for coverage, then score every candidate keyword's actual popularity in the target storefront using the local term, not the source-language term run through translation. A near-zero score on a grammatically correct translation is the clearest signal that real usage differs.

Check the storefront's own App Store search autosuggest for your core concepts to surface local phrasing you might not have considered. Where a market has genuine dialect variation within a shared language (Spanish, Portuguese, and similar), treat each storefront's vocabulary as its own research pass rather than assuming one list covers the whole language.

Frequently asked questions

Is it ever fine to just translate my keyword list and ship it?
For an initial low-cost test of whether a market has any demand at all, a translated list is a reasonable first pass. Before investing real character-field space and design effort in a full localization, verify the translated terms' actual popularity rather than assuming translation alone is sufficient.
How much does vocabulary really differ within one language across storefronts?
Enough to matter. Spanish and Portuguese both have documented, common everyday-word differences between their major storefronts, comparable in scale to the differences between American and British English, and sometimes larger.
Does this apply to the keyword field, or just visible copy like description and promotional text?
Both. The keyword field is exactly where vocabulary drift matters most, since it's pure keyword coverage — a mistranslated or dialect-mismatched keyword-field term returns close to zero real search demand, wasting character space that a correctly localized term would have used productively.

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