Schema Markup and Structured Data

Schema markup tells search engines what your content means, not just what it says. A plumbing service page without schema is plain text. The same page with Service, Organisation, and FAQPage schema is a structured entity Google can parse, categorise, and surface in rich results.

We implement schema as hand-written JSON-LD within an entity-interconnected @graph. Every schema node on every page references back to your site-wide Organisation and WebSite entities through @id, creating a web of structured data that reinforces your site's topical identity across every page.

Schema Types We Implement

How Do You Connect Entities with Schema Markup?

Connect entities with schema markup by assigning each entity a stable @id. Reference the organisation through the provider property of each Service and the publisher property of each Article or WebSite where those relationships apply. Use one @graph per page to organise the nodes.

Use an absolute URL such as https://example.co.uk/#organization as the organisation's @id. Reuse that identifier wherever the markup describes the same organisation. In JSON-LD, objects with the same @id identify the same entity. Repeating a full object with that identifier does not create a separate entity. Consistent identifiers express relationships explicitly but do not guarantee how Google reconciles entities across pages.

{
  "@context": "https://schema.org",
  "@graph": [
    { "@type": "Organization", "@id": "https://example.co.uk/#organization",
      "name": "Example Plumbing Ltd", "url": "https://example.co.uk/" },
    { "@type": "WebSite", "@id": "https://example.co.uk/#website",
      "url": "https://example.co.uk/",
      "publisher": { "@id": "https://example.co.uk/#organization" } },
    { "@type": "Service", "@id": "https://example.co.uk/boiler-repair/#service",
      "name": "Boiler repair",
      "provider": { "@id": "https://example.co.uk/#organization" } }
  ]
}

Our entity linking process runs in four steps:

1. Step 1: Audit existing schema. We crawl your site to identify any existing schema markup, check for errors in current implementations, and document which pages have schema and which do not.
2. Step 2: Define the entity graph. We map out the entities on your site (your organisation, your services, your content types) and define how they connect through @id references within a single @graph per page.
3. Step 3: Write per-page JSON-LD. Each page receives a hand-written JSON-LD block containing the schema types appropriate to its content. Every node references back to the site-wide Organisation and WebSite entities.
4. Step 4: Validate and deploy. All schema is tested through Google Rich Results Test and Schema.org Validator. We fix any warnings or errors before deployment and verify that rich results are eligible where applicable.

Schema Validation

Invalid structured data can prevent the affected markup from qualifying for supported rich results. We validate every page through three layers: Google Rich Results Test for eligibility checking, Schema.org Validator for specification compliance, and manual JSON-LD inspection for entity relationship integrity.

Check for invalid JSON, inappropriate property values, inconsistent @id references and markup that does not match the visible content. Check required properties against the documentation for each supported Google search feature. Organisation names and article publication dates are recommended details rather than universally required properties.

Frequently Asked Questions