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SEO Guide

Structured Data: Help Search Engines Understand Your Site

Schema markup in JSON-LD tells search engines what your pages mean. This guide covers Organization, Breadcrumb, Article and FAQ types with code examples.

Search engines and AI engines are both trying hard to "read" web pages, but machines have no semantic intuition — they rely on structured clues. Structured data (Schema markup) is a page description written for machines: using the shared vocabulary of schema.org, it marks up "this is a company, this is an article, these are FAQs" so that Baidu, Google and even AI engines like Doubao and DeepSeek can accurately understand what a page is about. For any business site doing technical SEO, this is the lowest-cost, highest-certainty foundational work available.

What is structured data: a page description for machines

schema.org is the shared structured-data vocabulary maintained by Google, Microsoft, Yahoo and Yandex. Three encoding formats exist: JSON-LD (recommended), Microdata and RDFa. JSON-LD is injected as a script tag, does not affect rendering, and is the cheapest to maintain — it is Google's officially recommended format, and Baidu supports it as well. Validate every page's markup with a testing tool before launch: invalid JSON-LD is silently ignored by crawlers and only adds noise. For bilingual sites, localize schema strings so the JSON-LD on your Chinese pages carries Chinese values.

A minimal Article-type JSON-LD example:

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Article",
  "headline": "SEO vs GEO: The New Traffic Landscape of Search and AI",
  "datePublished": "2026-08-04",
  "author": { "@type": "Organization", "name": "Shanghai Zheming Information Technology Co., Ltd." }
}
</script>

Five Schema types every business site should use

Schema typeWhat it doesPossible search enhancement
OrganizationDeclares company name, address, contact, brand infoKnowledge graph display, entity recognition
WebSite + SearchActionDeclares site identity and on-site searchSitelinks in search results
BreadcrumbListMarks the page's breadcrumb hierarchyBreadcrumb path in search results
Article / NewsArticleMarks article title, author, publish dateRich snippets, top-story images
FAQPageMarks frequently asked questions and answersCollapsible FAQ display in results

Structured data for Baidu, Google and AI search

The first layer of value is in the Baidu ecosystem. According to Baidu Search Resource Platform documentation, Baidu supports structured data markup; properly submitted markup helps the engine understand content more accurately, and some industries can obtain enhanced display such as rich snippets — a meaningful bonus for Chinese-language search optimization.

The second layer is in the Google ecosystem. According to Google Search Central documentation, correct structured data can qualify pages for Rich Results — breadcrumbs, FAQs, ratings and more — which directly lift click-through rates in search results.

The third layer is in AI search. Large language models' retrieval-augmented generation (RAG) pipelines depend heavily on parseable entity information: Organization, Service and FAQPage markup helps AI engines accurately associate your brand entity with your service capabilities. In other words, structured data is not only the technical foundation of SEO, but also a prerequisite for GEO optimization — AI engines must be able to "read" your content before they will cite it.

Technical SEO has no shortcuts, but structured data offers the best return on effort. Shanghai Zheming Information Technology Co., Ltd. builds Schema deployment and validation (Google Rich Results Test, Baidu structured data testing tools) into its website development and SEO optimization services. Call +86 18917757529 or email jaysun@widesight.cn for a consultation. For more on corporate site essentials, see B2B Website Guide: Build a Site That Generates Leads.