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GLOSSARY

Structured Data

Structured data is extra markup that explains your content to search engines. It powers rich snippets, product stars, and AI answers.

What is Structured Data?

Structured data is a standardized way to annotate content (often with JSON-LD) so search engines and applications can interpret meaning. Examples: Product schema for PDPs, FAQPage schema, Breadcrumb schema, and Article schema.

How It Works (quick)

  • Formats: JSON-LD (preferred), Microdata, RDFa.
  • Vocabularies: Schema.org, OpenGraph, Dublin Core.
  • Implementation: Add markup to HTML <head> or inline; validate with tools.
  • Consumption: Search engines use it for rich snippets, AI overviews, and knowledge panels.

Why It Matters in E-commerce

  • Rich results: Stars, price, availability, reviews boost CTR.
  • AI visibility: Provides structured facts for AI overviews and shopping assistants.
  • Trust: Clear, machine-readable context reduces ambiguity.
  • Navigation: Breadcrumb schema improves sitelinks and UX.

Best Practices

  • Use JSON-LD in <head>; validate with Rich Results Test.
  • Keep data consistent with visible content.
  • Mark up all eligible entities (Product, Offer, Review, FAQ, Breadcrumb, Article).
  • Update dynamically with stock/price changes.
  • Avoid spammy markup; follow Google’s guidelines.

Challenges

  • Drift between visible content and markup.
  • Vendor feeds vs live stock mismatch.
  • Over-marking (e.g., every page as FAQ).

Examples

  • PDP: Product + Offer + Review schema.
  • Category: Breadcrumb + ItemList.
  • Help article: Article + FAQPage.

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Summary

Structured data clarifies meaning for search engines. Use JSON-LD with schema.org types, keep it aligned with content, and refresh dynamically for trust and visibility.

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FAQ

Does structured data guarantee rich results? No—it enables eligibility but doesn’t guarantee.

Should I use multiple schemas? Yes, if accurate and consistent.