Schema Coverage Ratio

Schema coverage ratio answers two questions at once: what fraction of your crawlable pages have any JSON-LD at all, and how many of those use the *right* schema type for the page context?

The audit crawls every indexable URL from your sitemap and renders the source to extract all <script type="application/ld+json"> blocks. Each block gets parsed and validated against the Schema.org vocabulary. Pages land in one of four buckets: correct and relevant schema, wrong schema type for the page (Organization on a blog post instead of Article -we see this constantly), malformed JSON-LD, or no schema at all.

The final ratio: (pages with correct, relevant schema) / (total crawlable pages) × 100. We also track a secondary metric -"schema type accuracy" -the percentage of schema-bearing pages where the primary @type actually matches the content. A product page should carry Product schema, not just a generic WebPage.

Beyond the top-level number, we measure schema depth. A Product page with just name and description scores lower than one with price, availability, brand, aggregateRating, and image. The bare minimum isn't enough when your competitors are filling in every recommended property.

Here's the mistake we see on almost every audit: beautiful structured data on the homepage, and nothing -zero -on the other 200 pages. AI engines and search crawlers evaluate your site holistically. When 90% of your pages lack schema, the domain-level signal is weak regardless of how polished that homepage markup is.

Google's Rich Results eligibility is per-page. Every product page without Product schema is a missed rich snippet. Every article without Article schema loses the chance for a featured result with author and date info. At scale, this compounds fast -a 200-page e-commerce site with schema on only 15 pages has a 7.5% coverage ratio. That's 92.5% of the catalog invisible to structured data consumers.

AI answer engines like Perplexity and ChatGPT increasingly use structured data to validate facts before citing a page. When they find proper schema confirming the content is an Article published on a specific date by a specific author, they treat that page as more trustworthy than an identically-worded page with none. Site-wide coverage means no matter which page an AI engine lands on, it gets machine-readable context.

There's an entity problem too. If your Organization schema appears on 10 pages but is absent from 190, crawlers may not associate all your pages with the same entity. Uniform coverage reinforces that every page belongs to one authoritative publisher.

The automated audit performs a full-site crawl starting from the XML sitemap and following internal links up to a configurable depth (default: 3 levels). For each URL, the crawler fetches raw HTML and extracts all JSON-LD script blocks.

Each block goes through three validation stages. First, JSON syntax -unclosed braces, trailing commas, encoding errors. Second, Schema.org vocabulary -does the @type exist in the hierarchy, are required properties present? Third, contextual relevance -a page with pricing in the body should have Product schema, not just WebPage.

The audit generates a per-page report card: green (correct schema), yellow (schema present but wrong type or missing required properties), orange (malformed JSON-LD), red (no schema). These roll up into the site-wide coverage ratio.

Here's where it gets powerful: pages are grouped by template type when detectable. All /blog/* pages, all /products/* pages. This reveals template-level gaps -your blog template might be missing Article schema entirely, which means every blog post inherits that gap. Template-level findings are the highest-priority fixes because patching one template improves coverage for hundreds of pages simultaneously.

The crawler respects robots.txt directives and Crawl-delay settings. Pages returning 4xx or 5xx are excluded from the denominator but flagged separately as potential sitemap issues.

Schema coverage uses a tiered rubric based on the percentage of pages with correct, contextually relevant JSON-LD:

Coverage ratio tiers: - 90-100%: Score 10/10 -Exceptional. Nearly every page has correct schema. - 80-89%: Score 8/10 -Strong. Minor gaps, typically on edge-case pages. - 60-79%: Score 6/10 -Moderate. Significant template gaps exist. - 40-59%: Score 4/10 -Weak. More pages lack schema than have it. - 20-39%: Score 2/10 -Poor. Schema isolated to a handful of pages. - 0-19%: Score 1/10 -Minimal. No site-wide schema strategy.

Deductions for quality issues: - -1 point if more than 10% of schema blocks have JSON syntax errors - -1 point if the dominant type is WebPage when more specific types apply - -0.5 points if Organization schema is inconsistent across pages (different names, URLs, or addresses) - -0.5 points if required properties are missing on more than 25% of typed schemas

Bonus for depth: - +0.5 points if average schema depth (recommended properties present / total recommended) exceeds 70% - +0.5 points if the site uses @graph to combine multiple related schemas per page

Maximum: 10. Minimum: 0 for sites with zero JSON-LD anywhere.