How to implement LocalBusiness, FAQPage, Article, and Service schema for security company websites - with copy-paste JSON-LD code examples ready to add to your WordPress pages today.
Written to the same answer-first standard we apply when optimising your content for AI extraction and featured snippets.
Schema markup is structured data added to a web page's HTML that tells search engines and AI systems exactly what the page is about - not just through text analysis but through machine-readable labels. For security companies, schema markup is the technical layer that enables AI Overviews to extract your answers, rich results to display your FAQs, and knowledge panels to recognise your business as a verified entity. Without schema, AI systems must guess at your content's meaning; with schema, they know.
The four schema types with the highest impact for security companies are: LocalBusiness (communicates your business identity, address, service area, and contact information - essential for local search); FAQPage (directly powers AI Overview Q&A extraction and People Also Ask inclusions); Article with dateModified (provides freshness signals that AI systems use to prioritise recently updated content); and Organization with sameAs (confirms brand entity across the web, building the entity recognition that AI recommendation systems use).
This article is Article 09 in the SecurityBlogs.com.au complete Security Industry SEO Guide - a 10-chapter topic cluster covering every dimension of SEO for security companies.
A practical implementation framework - not theory. These are the specific actions that produce results for security companies.
LocalBusiness schema communicates your business identity to Google and AI crawlers. Use the SecurityCompany sub-type if available, otherwise use LocalBusiness with a security-specific description. Include: @type, name, url, telephone, address (with streetAddress, addressLocality, addressRegion, postalCode, addressCountry), openingHoursSpecification, areaServed (list each suburb or city you serve), and sameAs (your LinkedIn, ASIAL listing URL, Facebook, and any other official profiles). This stacked information gives AI systems everything they need to verify and recommend your business.
FAQPage schema is the highest-impact schema type for AI visibility. It directly feeds the Q&A extraction mechanism used by Google AI Overviews, Bing Copilot, and Perplexity. For each service page, write 5–8 buyer evaluation questions and concise, direct answers (50–150 words each). Implement them as a JSON-LD @graph block in the page's head alongside an Article @type. The questions should exactly match the buyer evaluation queries you identified in your keyword research - because these are the queries where being the featured answer matters most.
Article schema signals to AI systems that a page is a piece of authored, dated content - not just a web page. The dateModified field is particularly important: AI systems prioritise recently updated content for answer extraction. Update the dateModified value every time you revise a page's content - even minor updates count. Include: headline (matching your H1), description (matching your meta description), datePublished, dateModified, author (Organization or named Person), and publisher.
After implementing any schema markup, validate it using Google's Rich Results Test (search.google.com/test/rich-results). This tool shows exactly what schema Google reads from your page, flags any errors or warnings, and previews how rich results will appear in search. Fix all errors before moving to the next page. Also submit your updated sitemap to Search Console after adding schema - this accelerates re-indexing of updated pages.
We implement the complete schema stack - LocalBusiness, FAQPage, Article, and Organization - across your security company's key pages, with validation and Search Console monitoring included.