Schema markup for trades businesses

The essential four are LocalBusiness (with the correct trade subtype, e.g. Plumber or Electrician), Service (one entity per distinct offering), FAQPage (on any page with questions and answers) and Review plus AggregateRating (wherever you display customer ratings). These four cover the rich-result and AI-citability requirements for the vast majority of trades websites.

Not directly in the traditional link-authority sense. What it does is unlock rich results — star ratings, FAQ dropdowns, opening hours — that increase your click-through rate from the same position. It also removes ambiguity about your trade and service area, which helps Google assign you to the right local pack. The indirect ranking benefit is real but the primary win is visibility and click-through.

AI models do passage-level retrieval: they extract the fragment that best answers a query and cite it. FAQPage markup structures your answers into discrete, self-contained blocks that are far easier for a model to extract and attribute. Service and LocalBusiness markup reduce the ambiguity about who you are and what you do, making your content a more confident citation candidate.

LocalBusiness is the parent type. Subtypes like Plumber, Electrician, HVACBusiness, RoofingContractor and GeneralContractor inherit all its properties and add categorical precision. Using the correct subtype means Google and AI models do not have to infer your trade from your prose — you declare it. That precision matters most in competitive local markets where multiple firms serve the same area.

For simple cases — a single-location business with one or two service types — a plugin (on WordPress) or a tag manager snippet is achievable without code. For multi-location businesses, per-service pages and accurate FAQPage markup, developer involvement ensures the JSON-LD is generated dynamically from your CMS data rather than maintained manually page by page. Manual maintenance breaks silently after content updates.

Three tools: Google's Rich Results Test (instant validation of any URL), Google Search Console's Enhancements report (shows impression and error trends over time for each rich-result type) and a manual spot-check of AI overviews for your key trade and city queries. We configure monitoring for all three and review them monthly as part of our maintenance service.

It needs maintenance. CMS updates, new service pages, changed opening hours and new review totals can all break or outdate your markup without any visible sign on the page. Google's Search Console Enhancement reports surface these errors, but only if someone is watching. We include monthly validation and fixes in every ongoing schema engagement.

Minimal impact when implemented as JSON-LD in the document head — which is the Google-recommended approach. Inline microdata or RDFa markup woven into HTML can add parse overhead, but JSON-LD is a separate script block processed after render. Page speed remains your primary Web Vitals concern; schema adds essentially nothing to load time.

Yes, provided you have a lawful basis for collecting the review (typically legitimate interests or consent), you do not publish personal data without the reviewer's agreement, and you honour deletion or correction requests. The schema markup itself serialises aggregate data and anonymised review text — no personal data pipeline is required. The ICO has published guidance on AI and data protection that applies to the automated processing of review content.