Structured data (typically JSON-LD) embedded in HTML that helps AI engines understand entities, products, FAQs, and articles on your page.
Schema markup uses Schema.org vocabulary in JSON-LD format to label content entities for crawlers and AI engines. Common AEO-relevant schema types include Article (for blog posts), Product (for software products), FAQPage (for FAQ blocks), HowTo (for tactical guides), Organization (for company info), and BreadcrumbList (for hierarchy). Properly-marked content is significantly more likely to be cited cleanly by AI engines because the entities are unambiguous.
AI engines parse schema markup to extract structured facts. A product page with Schema.org/Product markup including price, ratings, and availability gives the AI engine a citation-friendly fact set. A page without schema requires the AI to infer the same facts from prose, which is slower and less accurate.
Every Lantern comparison page includes FAQPage schema for the FAQ block, BreadcrumbList for the navigation hierarchy, and Article schema for the page itself. When ChatGPT or Perplexity cite a Lantern comparison page, they extract the FAQ Q&A pairs cleanly because the markup labels them explicitly.
The terms in this glossary aren't theoretical — they're what Lantern's product calculates and reports every month for B2B SaaS teams. See yours in 7 days. 14-day free trial.
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