What Foreign Visitors Actually Search for in Japan—And Why Local Platforms Don't Serve Them Well

Three Million Monthly Visitors Face a Wall

Since March 2024, foreign tourists visiting Japan have exceeded three million per month. This represents record-breaking numbers and a significant opportunity for Japan's tourism industry. However, it also highlights challenges related to language and information access.

Surveys indicate that approximately 22% of visitors to Japan reported difficulty communicating with staff at hotels, restaurants, and other facilities. This figure suggests not merely a language proficiency issue but a systemic challenge in information system design.

Foreign Visitor Search Patterns

When foreign tourists search for restaurants in Japan, several patterns emerge.

First, natural language question formats predominate. "Where can I find authentic ramen near Shinjuku?" "What's a good sushi place that takes credit cards?"—such sentence-format searches require different approaches than keyword-based queries.

Second, searches typically contain compound conditions. Budget, location, cuisine type, payment method, allergy accommodation—visitors seek establishments meeting multiple criteria simultaneously. Single keywords cannot express such multifaceted needs.

Third, context-dependent preferences appear frequently. "Somewhere easy to enter with children," "atmosphere suitable for a date," "casual enough for dining alone"—these subjective conditions rarely exist in structured data.

Misalignment with Japanese Metadata

The core problem lies in the "misalignment" between English searches and restaurant information registered in Japanese.

Consider the word "izakaya." For foreign tourists, this signifies a "Japanese-style pub" or "izakaya-style dining establishment." However, Japanese platforms categorize more granularly: "izakaya," "washoku" (Japanese cuisine), "creative cuisine," "yakitori," and so on.

Searching "izakaya with good yakitori" may not work well when Japanese databases classify "yakitori specialty shops" and "izakaya" as separate categories. This conceptual misalignment reduces search accuracy.

Japan-specific dish names also create barriers. "Obanzai," "motsu-nabe," "chanko"—these lack direct English equivalents, making them difficult to find through descriptive searches.

The Limits of Keyword Search

Traditional keyword search operates on exact or partial matching. Searching "ramen Shibuya" returns results containing both "ramen" and "Shibuya."

Natural language needs are more complex. "I want something light but filling after a long flight"—keyword search is powerless against such requests. The keywords "light," "filling," and "flight" don't exist in restaurant databases.

Negative conditions are also difficult to handle. "No raw fish," "not too spicy"—expressing these through keyword search is challenging. Japanese platforms often lack systematic registration of allergy information or dietary restriction accommodation.

Platform Response Status

Japanese restaurant platforms are progressing on inbound tourism support. Tabelog offers an English version, and HotPepper Gourmet provides some information in English. Google Maps supports multilingual search.

However, fundamental challenges remain. Even with English versions, translation quality varies. Machine translation struggles to accurately convey dish names and restaurant atmosphere. Furthermore, Japanese-language reviews—the most valuable information source—remain inaccessible.

One survey found that 70% of restaurants indicated "no plans" to accommodate inbound tourists. The primary reason cited was "difficulty with multilingual support," noted by approximately 60% of establishments.

The Limits of Translation Apps

Many tourists rely on translation apps. Google Translate, DeepL, and other tools serve daily conversation needs. However, for restaurant selection, they have limits.

While menus can be translated, whether a restaurant suits your specific needs cannot be determined. Translating reviews one by one takes too much time. More fundamentally, translation apps don't help at the stage of deciding which restaurants to research.

The language barrier isn't simply a "translation" problem. Information filtering, context understanding, implicit cultural knowledge—these combine to enable appropriate restaurant selection.

What's Needed Is Understanding, Not Just Translation

What foreign tourists truly need isn't mere translation. They need a layer of "understanding" that comprehends their preferences and circumstances and presents appropriate options from Japan's vast restaurant information ecosystem.

LocalWays addresses this challenge. It accepts natural language questions, interprets user intent, and searches Japanese databases to find suitable establishments. Rather than exact keyword matching, it provides suggestions based on context and intent.

"A quiet place, not too expensive, Japanese food other than seafood"—such compound requests cannot be handled by simple keyword search. Understanding meaning, decomposing conditions, finding appropriate options—this is the role of an AI assistant.