Measuring AI Visibility in Asian Markets: Why Translated Prompts Give You the Wrong Answer

If you sell into Asia, you have probably seen an AI visibility report showing near-zero presence in Japan, Korea, or Taiwan — and assumed it reflects reality. It may instead reflect how the measurement was built.

Failure one: translated prompts

Most tools that advertise multi-country coverage prepare one set of English prompts and translate them. Two things break at once.

The phrasing is wrong. A Japanese buyer looking for a cafe does not ask the translation of “best cafes in Tokyo.” They ask something closer to “which cafe would you recommend for going with friends” — the situation, the company, and the intent are built into the sentence. Translate the English and you are asking a different question.

The competitor set is wrong. Translated prompts tend to surface international chains rather than the local players you actually compete against. You receive a competitive analysis listing brands you will never meet in that market.

The right-hand column carries situation, identity, and hesitation. AI answers those very differently — and names different brands.

Failure two: the brand-name gap

This one is the easiest to miss and the most damaging. A brand is often written differently across languages: an official localized name, a common abbreviation, and the original Latin-script name all coexist. If measurement matches only one spelling, the AI may well have recommended you and the system records it as a miss.

The result is a quiet, systematic underestimate. Nothing looks broken — you simply see a low score, with no indication that it was measured wrong.

Worth asking any vendor directly: if the AI mentions my brand using the local-language name, does that count, and how do you verify it?

Failure three: China runs on different engines

ChatGPT, Gemini, and Perplexity are not the mainstream assistants in mainland China. Local users are asking DeepSeek and Kimi. Measuring the Chinese market with Western engines describes a world your Chinese customers never see.

An honest caveat about our own coverage: our China measurement operates at the model layer — what the local models answer — and its search grounding is less complete than the Western engines. Treat it as a signal of model-level awareness, not as an equivalent of live Western search results.

What accurate multi-market measurement requires

1. Prompts generated natively per market, including local cities and local buying situations — not translated.
2. A competitor set built per market. Local rivals and international rivals are different lists.
3. Brand-name matching that covers local-language names, abbreviations, and the Latin-script original.
4. Engine selection per market: Western engines for most markets, local models for China.
5. Fixed prompts across periods. Change the questions and month-over-month comparison becomes meaningless.

How GEO by TriloAI handles it

Each market runs its own prompts, its own city context, and its own competitor set. A single brand can be tracked across several markets in one account and compared month over month.