Definition
Schema markup is structured data using the schema.org vocabulary — added to a page as JSON-LD, Microdata, or RDFa — that explicitly describes the page's content type (product, article, FAQ, recipe, review, event, person, organisation) so search engines can render rich results.
Schema markup makes implicit information explicit. A recipe page is recognisable to humans by the ingredient list and steps; schema markup tells the crawler the same thing in a structured form. Once tagged, recipes can show ratings, cook time, and calorie counts directly on the SERP — driving substantially higher click-through.
Schema doesn't directly improve rankings; it improves rich-result eligibility, which improves CTR, which improves engagement signals. The net effect on traffic is often double-digit percentage gains for free, on existing content. The implementation cost is small — JSON-LD pasted into the head of each page type — and the upside is durable.
Origin
Schema.org launched in 2011 as a joint project between Google, Microsoft, Yahoo, and Yandex — a shared structured-data vocabulary. JSON-LD became the recommended format around 2015, replacing the more invasive Microdata and RDFa.
How it works
- Identify content types on your site (article, product, FAQ, organisation, event).
- Pick the schema.org type for each (Article, Product, FAQPage, Organization, Event).
- Generate JSON-LD blocks for each page — most CMSs have plugins; static sites generate at build time.
- Validate with Google's Rich Results Test and Schema Markup Validator.
- Submit the sitemap; monitor rich-result earning in Google Search Console.
- Iterate — Google adds new schema types; opportunities grow over time.
When to use it
Use when
- On every page that fits a recognised schema type — which is most pages.
- Especially: products, articles, FAQs, events, recipes, reviews, organisations.
- When CTR is lower than expected at the same rank — schema can lift it.
Skip when
- On schema that doesn't match the visible content. Google penalises misleading markup.
- On thin content. Schema doesn't fix bad pages — Google just doesn't grant rich results to weak content.
Key metrics
- % of pages with valid schema markup.
- Rich result impressions in Google Search Console.
- CTR on rich-result pages vs. non-rich.
- New rich-result types earned over time.
Examples
- Adding FAQ schema to the pricing page won us a featured snippet.
- Schema markup doesn't move rankings directly, but it dramatically increases click-through rate.
- Article schema on every blog post lifted CTR 18% on average.
In practice at Makreate
Every Makreate website ships with schema markup tailored to its content type — products, articles, services, FAQs — so SERP listings stand out. On a recent ecommerce engagement we deployed Product schema (price, availability, ratings) across 4,000 SKUs. Within six weeks, rich-result impressions rose 240% and CTR on those listings climbed 31% — same products, same content, structured for the SERP.
Website Design & Development →Common mistakes
- Adding schema markup that contradicts the visible page content.
- Marking up everything with vague Article schema instead of the specific subtype (NewsArticle, BlogPosting, TechArticle).
- Missing required properties. Schema must include type-specific required fields to be eligible for rich results.
- Not validating after deployment. Schema breaks silently when CMS templates change.
- Treating schema as a magic ranking pill. It's a CTR lever, not a ranking signal.
Frequently asked
JSON-LD or Microdata?
JSON-LD — Google's recommended format since 2015. Easier to maintain (separate from HTML markup) and less error-prone.
Does schema affect rankings?
Indirectly. Schema makes rich results possible; rich results lift CTR; CTR is a ranking signal. Net effect is positive but not direct.
Will AI overviews replace rich results?
Not entirely. Rich results still drive substantial click-through on commercial and product queries. AI overviews are a layer on top, not a replacement.