The checks, vertical-tailored
What the audit checks for residential real estate teams.
Every audit, on every plan, scores Foundational SEO, Technical SEO, Local SEO and AI Visibility at equal weight. Local SEO always applies here, because a missing address or Maps link is itself a finding. The check definitions are constant; the severity, the recommended fix, the competitor set, and the example code shift per vertical via the adapter.
Foundational pillar
Foundational
Keyword universe, content depth, on-page structure, internal link graph.
- h1-presence
Neighborhood landing pages should lead with a single H1 in the pattern "Homes for Sale in [Neighborhood], [City] | [Agent or Team Name]". Agent-name-as-H1 surrenders the neighborhood-intent click to Zillow and Redfin.
- passage-extractability
Neighborhood pages should carry 134-167 word "What is it like to live in [neighborhood]?", "What is the median home price in [neighborhood]?", "What schools serve [neighborhood]?" answer blocks co-located under question-shaped H2 so LLMs can lift the passage verbatim.
- outbound-link-quality
Cite the local school district authority, the local economic-development authority, the local transit authority, and the local crime-stats source where relevant. Outbound authority on hyper-local pages signals trust to both Google and to citation-aware LLMs.
Technical pillar
Technical
Crawl, render, schema validation, Core Web Vitals, render-parity diff.
- schema-validation
RealEstateAgent + Residence + Place JSON-LD must validate against schema.org. For Residence, populate floorSize, numberOfRooms, numberOfBathroomsTotal, address, and a containedInPlace reference to the neighborhood Place. For RealEstateAgent, populate areaServed and a Place reference per neighborhood you actively transact in.
- js-render-parity
Many agent sites embed IDX search via an iframe or a client-rendered widget. The listing data is not in raw HTML and AI crawlers see nothing. The audit flags it and recommends a server-side IDX integration (RETS, RESO Web API) that renders listings into raw HTML for AI crawler visibility.
- core-web-vitals
Buyer research happens on mobile while standing in a kitchen at an open house or in a car driving past a sign. LCP below 2.0s and INP below 200ms are non-negotiable; image optimization and font-display swap typically get the most wins on agent sites.
Local pillar
Local
On-site local signals: LocalBusiness schema, Maps link, phone and address, service-area pages.
- local-business-schema
The audit checks that a LocalBusiness-class type such as RealEstateAgent is declared in your JSON-LD. It does not validate the fields. We recommend geoCoordinates, openingHoursSpecification, areaServed with each neighborhood as a Place, and a Person per agent with a state-license sameAs.
- nap-consistency
The audit reads this page for a complete phone, street address, and ZIP code fingerprint. It does not compare your listings on Google, Zillow, Realtor.com, Redfin, your MLS portal, Homes.com, or the BBB; check those by hand so they match your site exactly.
- service-area-page-coverage
The audit detects service-area pages from internal links that follow a /locations/ or /areas/ URL pattern. It does not grade how unique each page is, so give each neighborhood page unique copy on schools, transit, prices, and recent comps rather than boilerplate.
AI Visibility pillar
AI Visibility
AI crawler readability, schema for AI, passage extractability, entity graph.
- schema-completeness-for-ai
The real-estate AI graph (RealEstateAgent + Residence + Organization + Person + Place + FAQPage + BreadcrumbList) is the densest in any vertical alongside doctors. AI engines triangulate "best [neighborhood] real estate agent" against this graph plus a NAR membership sameAs.
- entity-graph
Per-agent Person sameAs to LinkedIn, the state real-estate-commission license verification page, the NAR member directory, the local Realtors association directory, the Zillow agent profile, the Realtor.com agent profile, and the Redfin agent profile. AI engines treat the per-agent entity graph as a primary trust signal.
- passage-headline-co-location
A page that lists 12 neighborhoods with a one-sentence summary and an H3 link out is unextractable for LLMs. Replace with question-shaped H2 + 134-167 word answer blocks per neighborhood. The page length grows but citation rate roughly triples on "best [neighborhood] real estate agent" queries.