What is Schema Markup?

Schema markup is the language that bridges human-readable web content and search engine comprehension. When you describe a product on your Shopify store, a human visitor understands that "$49.99" is the price and "4.7 stars" is the rating. Search engines need explicit structured data to make those same connections reliably. Schema markup provides that explicit layer by wrapping content in standardized tags that declare "this is the price," "this is the aggregate rating," and "this is the review count."

The most important Schema.org types for e-commerce are Product, AggregateRating, Review, and Offer. The Product type defines the item being sold, including name, description, brand, and SKU. AggregateRating contains the average star rating and total review count. Individual Review entries include the author, rating, date, and review body. The Offer type specifies price, currency, availability, and condition. Together, these types give search engines a complete, structured understanding of your product pages.

Implementation formats include JSON-LD (recommended by Google), Microdata, and RDFa. JSON-LD is the preferred approach because it is a self-contained script block that does not interleave with your HTML, making it easier to implement, debug, and maintain. For Shopify stores, schema markup can be added through theme customization, apps, or directly in Liquid templates. The key is ensuring the structured data accurately reflects the visible page content—discrepancies between markup and displayed content can result in manual actions from Google.

Testing and validation are essential parts of schema implementation. Google's Rich Results Test and Schema Markup Validator identify errors in your structured data before they affect search performance. Common issues include missing required properties, incorrect data types, mismatched information between markup and visible content, and outdated schema vocabulary. Regular auditing catches drift that occurs as products, prices, and review counts change.

Eevy AI automatically injects valid JSON-LD schema markup for Product, AggregateRating, and Review types on your product pages. As new reviews are collected, the structured data updates automatically to reflect current ratings and review counts, keeping your search eligibility current without manual maintenance.