Schema markup for contractor sites (2026 Google guidance): GeneralContractor / HomeAndConstructionBusiness / LocalBusiness, Service per service-line, Review + AggregateRating, Person for principals, FAQPage on service pages, Project (Article subtype) on case studies
Claim: As of 2026 Google guidance, contractor websites should deploy the following schema.org markup:
GeneralContractor/HomeAndConstructionBusiness/LocalBusiness— the primary business-entity schema. Pick the most specific applicable type.Serviceschema per service line — kitchen renovation, basement finishing, custom home, etc.ReviewandAggregateRating— subject to Google's authenticity requirements (reviews must be first-party, not third-party-collected).Personschema for principals — withsameAslinks to LinkedIn for E-E-A-T credentialing; pair withhasCredentialfor Gold Seal / P.Eng. / PMP (see Rule (Tier-2 ICI GC sites): use schema.org Person + hasCredential + EducationalOccupationalCredential markup so Gold Seal credentials surface in Google knowledge panels and AI overviews).FAQPageschema on service pages — surfaces in AI Overviews and zero-click features.Project(Article subtype) schema on case studies — withdatePublished,address,image, photographer credit where applicable.
Sources: schema.org; Google Search Central. Confidence: Verified for the schema types; Industry-consensus for the contractor-vertical adoption recommendations.
Documented adoption rate in the contractor vertical
Based on HTTP Archive structured-data tracking, contractor sites lag the broader local-business average by roughly 15 percentage points in schema adoption.
Confidence: Directional — HTTP Archive 2024/2025 structured-data chapter; not vertical-isolated.
This is the live frontier in 2026: AI-Overview and AI-summary visibility is correlated with schema deployment. With 45% of consumers now using ChatGPT/AI for local recommendations (BrightLocal Local Consumer Review Survey 2026 (n=1,002 US adults via SurveyMonkey): average of 6 review sources used; 97% read reviews online; 45% use ChatGPT/AI for local recommendations (up from 6% in 2025)), schema-rich pages are increasingly the ones that get cited. Schema-rich content gets cited; HomeStars profile pages do not.
Cross-references to parallel schema rules
- Rule (Tier-2 ICI GC sites): use schema.org Person + hasCredential + EducationalOccupationalCredential markup so Gold Seal credentials surface in Google knowledge panels and AI overviews — Person + hasCredential for individual credentials
- Rule (Ontario builder/renovator sites): build a dedicated /affiliations or /memberships page listing each HBA with a one-sentence description AND year joined, marked up with Organization schema + memberOf properties — Organization + memberOf for HBA affiliations
- Contractor owned-trust-signal stack: HCRA / Tarion / RenoMark / WRHBA / OHBA / CHBA / COR / WSIB / Gold Seal / insurance / ENERGY STAR / Net-Zero / LEED AP / GuildQuality / Google Business Profile — verifiable, portable, free-or-low-cost — HomeStars cannot replicate any of these — the trust-signal stack the schema markup surfaces
For a Tier-2 Ontario ICI GC client, the complete schema build-out is roughly:
Organization(root, in layout)LocalBusiness/GeneralContractorper office locationServiceper service-line pagePerson+hasCredentialper team-bioFAQPageper service pageArticle(Project subtype) per case studyBreadcrumbListsite-wideOrganization+memberOffor HBA affiliations on the/affiliationspage
This is the same discipline executed on the B&J marketing site (B&J — JSON-LD schema deployment VERIFIED (v2) — supersedes the "biggest technical gap" claim in v1) — different vertical, same pattern.
Related
- rule Rule (Tier-2 ICI GC sites): use schema.org Person + hasCredential + EducationalOccupationalCredential markup so Gold Seal credentials surface in Google knowledge panels and AI overviews
- rule Rule (Ontario builder/renovator sites): build a dedicated /affiliations or /memberships page listing each HBA with a one-sentence description AND year joined, marked up with Organization schema + memberOf properties
- reference BrightLocal Local Consumer Review Survey 2026 (n=1,002 US adults via SurveyMonkey): average of 6 review sources used; 97% read reviews online; 45% use ChatGPT/AI for local recommendations (up from 6% in 2025)