Contents
Introduction
The advancement of machine translation and AI has greatly simplified the process of localizing apps for global markets. The truth is, while AI and machine translation tools have certainly made strides in understanding and translating languages, when it comes to ASO, they often fall short. This is particularly true in complex languages such as Japanese, where the nuances of the language can make a big difference in app visibility and user engagement. For App Store Optimization (ASO), machine-translated results often require further refinement to effectively target local audiences and boost app visibility.
The Challenge of Written Forms in Japanese
One critical limitation of machine translation in ASO arises from linguistic nuances in non-Latin scripts, such as Japanese. Japanese utilizes three different scripts—Kanji, Hiragana, and Katakana—each of which can express the same word in different forms. These variations can significantly impact keyword optimization. For instance, the word “children” can be written as 子供 (Kanji), こども (Hiragana), or コドモ / キッズ (Katakana). And sometimes a combination of Kanji and Hiragana also works, like 子ども. Each form might be used differently by a local audience, affecting search behavior and app discoverability.
Machine translation tools often default to one script without considering the contextual use of others, potentially overlooking critical keywords. Continuously updating and testing keywords across these scripts can enhance visibility and user engagement in the app stores.
Spacing and Readability Issues
In Japanese, text does not include spaces between words, which can complicate the parsing of phrases and keywords. Words are often separated by punctuation such as commas or periods, but understanding where one word ends and another begins, especially when they are written in different scripts (Kanji, Hiragana, Katakana), requires practice and familiarity with the language.
Given this unique aspect of Japanese writing, a Japanese phrase or a compound keyword can be indexed even if the keywords are used separately in the metadata. However, caution is necessary when targeting a compound keyword or phrase composed of characters in the same script. This is because keywords in the same script can sometimes be difficult to distinguish from one another, potentially confusing both users and search algorithms.
When optimizing for keywords in such a context, it is essential to clearly understand how these terms are likely to be interpreted and indexed, ensuring that your content is as discoverable as possible while still being clear and user-friendly.
Homophones and Keyword Opportunities
Homophones emerge as another noteworthy consideration in ASO. They can be a goldmine for keywords if used correctly. These words, despite sounding identical, may carry significantly different meanings and contexts.
For instance, 町 and 街, both read as “machi,” and means town – the first one as a small town, and the latter as a more developed town. Each kanji can easily be confused in usage, and both can be valid to use depending on your app’s theme. Identifying and utilizing homophones effectively requires a deep understanding of the language, something that machine translations often lack.
Also sometimes, it would depend on the app searchers which kanji they’d choose use to search (regardless if in correct usage or not). So you would also find opportunities from these keyword variants. For example, your app is related to town building/making – “machi tsukuri”, you’d probably want to utilize all the “machi” + “tsukuri” keywords to increase your visibility.
Conclusion
While AI and machine translation have significantly advanced and can facilitate initial localizations, they often fall short in the nuanced realm of ASO. To truly capitalize on app store optimization, manual intervention, continuous testing, and cultural adaptation are essential. Starting with machine translation can set a foundation, but deepening understanding and customizing content for local markets is crucial for achieving superior app performance. The key is not just translating words but also conveying meanings that resonate with the local audience.
