Japanese SEO Analysis: Does Schema Markup Help Rankings?

An analysis of 407 Japanese search results reveals why conventional schema wisdom may not apply to the Japanese market.

1. What is Schema Markup?

Imagine you're organizing a filing cabinet. You could throw all your documents into one drawer, or you could use labeled folders: "Invoices," "Contracts," "Personal." The documents are the same, but the labels help anyone find what they need instantly.

Schema markup works the same way for websites.

It's invisible code that labels your content so search engines don't have to guess what they're looking at. Without these labels, Google sees your website as a wall of text. With them, Google instantly knows: "This is a business address. This is a product price. This is a recipe with a 30-minute cook time. This person is a doctor with 15 years of experience."

1.1. What You See vs. What Google Sees

When you search for a recipe, you've probably noticed some results look different:

Without schema markup:

Chocolate Cake Recipe - Best Ever! - MyBlog.com Learn how to make the best chocolate cake with this easy recipe...

With schema markup:

⭐⭐⭐⭐⭐ (4.8) · 45 min · 320 calories Chocolate Cake Recipe - Best Ever! - MyBlog.com Learn how to make the best chocolate cake with this easy recipe...

That star rating, cooking time, and calorie count? That's schema markup in action. The website told Google: "This is a recipe. Here's the rating. Here's the prep time." Google then displays this information directly in search results.

1.2. Real-World Examples

Schema markup powers the enhanced search results you see every day:

Without schema, these would just be plain blue links with text descriptions.

1.3. Why Should You Care Schema Markup?

For website owners, schema markup promises three things:

1. Stand out in search results Rich snippets (stars, images, prices) catch the eye and can increase clicks by 20-30%.
2. Help Google understand your content If you're a law firm, schema tells Google: "This is an organization. Here's our address. These are our practice areas. This attorney has these credentials."
3. Appear in voice search and AI answers When someone asks Siri "What's a good sushi restaurant in Shibuya?", the answer often comes from websites with proper schema markup.

1.4. The E-E-A-T Connection

Google evaluates websites using a framework called E-E-A-T: Experience, Expertise, Authoritativeness, and Trustworthiness. This is especially important for topics that affect people's health, finances, or safety (called "YMYL" — Your Money or Your Life).

Schema markup helps communicate E-E-A-T signals directly to Google:

A medical article with proper Person schema showing the author is a licensed physician carries more weight than an anonymous blog post.

1.5. The Importance of Schema in the Age of AI Search

Here's where it gets interesting for 2026 and beyond.

Google's AI Overviews now appear at the top of many search results — an AI-generated summary that answers your question directly. ChatGPT, Perplexity, and other AI tools are changing how people find information.

These AI systems need to understand content quickly and accurately. Schema markup acts like a cheat sheet:

If an AI assistant is answering "What's the best accounting software for small business in Japan?", it needs to understand which websites are legitimate software companies, which are review sites, and which are random blog posts. Schema provides these signals.

The shift: Schema markup may not boost your traditional Google ranking (our data shows it doesn't in Japan), but it may determine whether AI systems cite your content as a source.

2. The Japanese Schema Paradox

If you've worked with SEO in any capacity, you've probably heard some version of this advice: "implement schema markup to help Google understand your content, earn rich snippets, and improve your click-through rates."

The logic seems sound. Schema markup uses the Schema.org vocabulary—a collaborative project between Google, Bing, Yahoo, and Yandex—typically implemented via JSON-LD format as recommended by Google. Google's documentation states that structured data helps search engines "understand the content of a page." Major SEO platforms recommend schema implementation as a best practice. Case studies from Western markets show correlations between schema adoption and improved visibility.

2.1. Schema Doesn't Improve Japan Rankings

Pages without schema markup rank better than pages with schema.

The difference is small—0.11 positions—but the direction contradicts everything the SEO industry has been teaching for the past decade.

Before dismissing this as statistical noise, consider that the pattern holds across search intent:

For informational queries—the exact category where schema should theoretically help Google understand content—pages without structured data outperform those with it by nearly a full position.

Important caveat: This data reflects Japanese SERP behavior specifically. Results in English-language or other markets may differ. However, the findings align with Google's official statements about schema's role in rankings.

2.2. Position Tiers Tell a Different Story

Pages ranking 1-3 have the lowest schema adoption rate. The highest adoption appears in positions 4-7 — suggesting these sites focus on technical checkboxes while missing what actually drives rankings.

3. What Google Actually Says

These findings don't contradict Google's official position. They contradict the industry's interpretation of that position.

Google has been remarkably consistent on this topic. In October 2023, Danny Sullivan, Google's Search Liaison, stated plainly:

"Schema doesn't make you rank better."

John Mueller has echoed this sentiment repeatedly since 2018, explaining that while schema helps Google understand entities on a page, "that doesn't mean that just because people are doing things in a technically correct way on a website that the page is a better page."

First Page Sage's 2025 algorithm analysis places schema markup in a group of 23 factors that together comprise only 1% of Google's ranking algorithm—a significant demotion from its perceived importance in SEO circles.

The gap between Google's statements and industry practice has always existed. What the Japanese search engine results page (SERP) data suggests is that this gap may be especially pronounced in non-English markets.

4. The Japanese SERP Landscape

One of the most striking findings from this analysis is how dramatically schema adoption varies by industry in Japan.

4.1. Japanese Schema Adoption by Industry

Industries with highest adoption (Education, Real Estate, Technology) don't necessarily rank better. Travel & Tourism has the lowest adoption among major industries — representing an opportunity gap.

4.2. Content Quality Over Technical SEO

First, content quality appears to trump technical SEO signals. Japanese sites are ranking well without schema, suggesting that Google's Japanese algorithm places greater weight on content relevance, linguistic quality, and user engagement than on structured data markup.

4.3. Japan Uses Less Technical SEO Signals

Second, the Japanese market may be less saturated with technical SEO optimization. In highly competitive English-language markets, schema has become table stakes—everyone implements it, so no one gains advantage from it. In Japan, where adoption remains lower, the playing field may be more level, allowing content-focused sites to compete without heavy technical investment.

4.4. Is Japan Ahead Over the Curb?

Third, Japanese SEO practices may be ahead of the curve. If Google's algorithm genuinely doesn't reward schema with ranking improvements, then Japanese sites with lower adoption aren't missing anything—they're simply not wasting resources on signals that don't matter.

5. The Schema Types That Actually Correlate With Rankings

Not all schema is created equal. When we break down performance by schema type, patterns emerge that align more closely with Google's stated priorities around E-E-A-T:

The pattern is revealing. Schema types that establish identity and authority—Organization, Person—correlate with better rankings. Schema types that merely describe content format—Article, NewsArticle—show weaker or negative correlations.

BreadcrumbList, the most commonly implemented schema type with 86 instances, shows no ranking advantage whatsoever. It has become table stakes in Japan just as it has elsewhere, providing no differentiation.

This suggests a refined understanding of schema's role: structured data that communicates who you are may carry more weight than structured data that describes what your content is. Organization and Person schema feed directly into Google's Knowledge Graph, strengthening entity recognition beyond individual page rankings. This aligns with Google's increasing emphasis on author verification and E-E-A-T signals.

6. Industry-Specific Schema Performance

The relationship between schema and rankings varies by industry vertical. The following analysis focuses on verticals with sufficient sample sizes (30+ pages) for meaningful conclusions.

6.1. Legal & Business Services (法務・ビジネス) — 36 pages

Schema shows its strongest positive correlation in this vertical:

Insight: E-E-A-T schema dominates in Legal/Business. Organization (2.25) and Person (3.14) rank highest — credentials and authority matter in YMYL verticals. Generic Article schema performs worst (7.00).

6.2. Technology (テクノロジー) — 53 pages

Schema performance is mixed but generally positive:

Person schema performs well, suggesting that authorship signals matter for technical content. This aligns with Google's guidance on author structured data for establishing expertise.

NewsArticle schema, however, correlates with position 6.33—a significant penalty compared to other schema types. This may reflect Google's ongoing efforts to combat misinformation by applying stricter scrutiny to content marked as "news."

6.3. Travel & Tourism (旅行・観光) — 78 pages

With the largest sample size in this dataset, Travel provides robust insights:

Insight: Content-focused schema (BlogPosting, Article) outperforms structural markup. FAQPage performs worse in Travel than Technology — search intent differs by industry.). WebSite schema shows poor correlation, suggesting that generic site-level markup provides no ranking advantage for travel queries.

7. The AI Search Wildcard

Everything discussed so far applies to traditional Google Search rankings. Traditional SERP features like rich snippets and knowledge panels rely on structured data for enhanced display—but they don't directly influence position. Now, AI Overviews represent a fundamentally different approach to search results, and the landscape is shifting rapidly.

On January 2, 2025, John Mueller addressed schema's role in the age of AI search:

"This question will stick with us for the next year and longer, and the short answer is yes, no, and it depends."

His explanation clarified that schema's importance now varies by feature and how search engines or LLMs use that feature. Shopping results rely heavily on structured data for pricing, shipping, and availability. Other features use schema primarily to "richen up" search results visually.

This represents a fundamental shift in how we should think about schema's purpose:

Research from Seer Interactive (September 2025) found that organic CTR has declined dramatically across the board due to AI Overviews, with informational queries hit hardest. But pages cited within AI Overviews maintain significantly higher click-through rates than those that aren't.

GrowthSRC's 2025 study of 200,000+ keywords found that position #1 CTR dropped from 28% to 19% (a 32% decline) following AI Overview rollout. The rules of the game are changing.

The implication for Japanese sites with low schema adoption is significant. While they're not currently being penalized in traditional rankings, they may face visibility challenges as AI Overviews expand in the Japanese market. Schema that helps AI systems understand content—particularly Organization, Person, and structured FAQ content—may become essential not for ranking, but for being cited as a source.

8. Practical Recommendations for Japanese SEO

Based on this analysis, here's a revised approach to schema implementation for Japanese websites:

8.1. Prioritize Identity Schema

Organization and Person schema show the strongest positive correlations with rankings, particularly in verticals where trust matters. Implement these first.

For Organization schema, ensure you include:

• Official company name (法人名)
• Logo
• Contact information
• Social profiles
• Founding date

For Person schema on author pages:

• Full name
• Credentials and qualifications (資格・経歴)
• Professional affiliations
• Published works

8.2. Deprioritize Generic Content Schema

Article and BlogPosting schema show weak or negative correlations in most verticals. While they're not harmful, they shouldn't be your priority. Time spent implementing detailed Article schema might be better invested in content quality.

BreadcrumbList has become table stakes—implement it for user experience and rich snippet eligibility, but don't expect ranking benefits.

8.3. Avoid NewsArticle Unless You're Actually News

NewsArticle schema correlates with poor rankings across multiple verticals in this dataset. Unless you're a recognized news publisher, stick with Article or BlogPosting.

8.4. Industry-Specific Recommendations

8.5. Prepare for AI Search

Regardless of current ranking impact, implement schema that helps AI systems understand your content:

• FAQ schema for question-answer content
• HowTo schema for instructional content
• Author/Person schema for all bylined content
• Organization schema for company-affiliated pages

These won't necessarily improve your rankings today, but they position your content for citation in AI-generated answers—increasingly important as AI Overviews expand globally.

9. What This Means for the Japanese Market

1. Stop chasing schema as a ranking factor Pages without schema rank position 4.52 vs 4.80 with schema. The lift doesn't exist.

2. If implementing schema, prioritize E-E-A-T types Organization and Person schema correlate with better rankings. BreadcrumbList and WebSite do not.

3. Match schema to industry context

• Technology: FAQPage, Article
• Travel: BlogPosting, Article
• Legal/Business: Organization, Person

4. Focus on what actually ranks Top 3 results have the lowest schema adoption (45.8%). They're winning on content quality, not technical optimization.

5. Schema remains valuable for rich results Even without ranking benefit, schema enables rich snippets, knowledge panels, and AI Overview citations. Implement strategically — just don't expect position improvements.

📊 KIJI-SEO独自分析 407件の日本語検索結果を分析した結果、スキーママークアップを実装していないページ（平均順位4.52）が、実装しているページ（平均順位4.80）よりも上位に表示される傾向が確認されました。さらに、上位3位のページはスキーマ導入率が最も低く（45.8%）、4-7位が最も高い（57.7%）という結果に。この発見は、日本市場においてコンテンツ品質がスキーマ実装よりも重視されていることを示しています。

This analysis is based on 407 Japanese search results across 152 classified keywords and 323 classified domains. Industry-specific findings focus on verticals with statistically meaningful sample sizes (n≥10), while schema type analysis requires a minimum of 3 occurrences.

For more insights on Japanese SEO:

• Japanese SEO Basics: What Western Tools Miss
• The Secret to Japanese SEO Success
• Compound Keywords: The Japanese SEO Advantage