PLAYBOOK · 02
Schema & Entity Graph Sprint
Make AI engines and traditional search read your business as a defined entity. JSON-LD across Organization, LocalBusiness, Service, FAQ, Article, Breadcrumb, and Review — wired with internal linking and entity disambiguation so Perplexity, ChatGPT, and AI Overviews quote you, not your competitors.
04CAPABILITY LAYER
This lives inside the Search & Discoverability layer.
Structured data is no longer optional — it is how AI engines decide what to cite. Without a clean entity graph, Google AI Overviews and Perplexity guess, and the guess is rarely you. With one, your business becomes an indexable entity that AI engines surface in answers, not a string of words competing for keyword rank.
See: Answer Engine OptimizationOutcomes
What this hands you when it lands.
- 01JSON-LD deployed across Organization, LocalBusiness, Service, FAQ, Article, Breadcrumb, Review
- 02Entity disambiguation via sameAs links to Wikidata, LinkedIn, Crunchbase, GitHub
- 03Schema validated in Google Rich Results Test and Schema.org validator
- 04Entity graph documented so future content extends, not breaks, the structure
- 05AEO content patterns: question-format H2s, atomic answers, supporting evidence
- 06Visibility check: confirmed citation in at least one AI engine within 30 days
The problem
Why most teams get this wrong.
Most websites publish content as flat HTML — fine for keyword-era Google, fatal for AI-era discovery. AI engines need structured signals to cite confidently. Without schema, your business is a string of words; with schema, it is an entity. The gap between those two states determines whether AI surfaces your services or someone else's when buyers ask.
The system
Six modules. One indexable entity graph.
Organization + LocalBusiness
Root entity definition with logo, sameAs (LinkedIn, Crunchbase, Wikidata), areaServed, contactPoint, knowsAbout. The anchor every other entity links back to.
Service catalog
Service schema for every offering with serviceType, provider link, areaServed, hasOfferCatalog. Lets AI engines understand what you actually do without prose-mining.
FAQ + atomic Q&A
FAQPage schema on every page with deserving questions. Atomic answers (one paragraph each). The structure AI engines extract directly into answer cards.
Article + Author + Breadcrumb
Article schema on every blog and playbook with author, datePublished, dateModified, mainEntityOfPage. Breadcrumb schema for site hierarchy. Both feed AI Overviews directly.
Review + AggregateRating
Pull verified reviews from GBP, Yelp, third-party platforms. Display with Review + AggregateRating schema. Drives star-snippet visibility in SERPs.
Entity disambiguation + linking
sameAs across Wikidata, Wikipedia, LinkedIn, Crunchbase, GitHub. Internal linking strategy that reinforces entity relationships. Disambiguates "TechStack Consulting" from generic "tech stack consultants".
Deliverables
Artifacts handed off, in writing.
Timeline
A 14-day sprint in three phases.
Audit + entity map
Inventory existing schema. Map your business as an entity graph. Identify gaps and disambiguation risks. Output: target schema architecture and sameAs strategy.
Implement + validate
Deploy JSON-LD across all template types. Wire sameAs links. Author atomic FAQs. Validate every page in Rich Results Test and Schema.org validator.
Verify citation + hand off
Confirm citation appearing in AI engines (or set the monitoring to detect when). Hand off content style guide so authoring extends the system instead of breaking it.
FAQ
Questions we get asked.
01How fast does AI start citing us after schema deployment?+
7–30 days for AI Overviews, 14–60 days for Perplexity / ChatGPT. The signal needs to propagate through Google's index before AI engines pick it up.
02Do we need a developer to deploy this?+
For most CMS / Vite / Next sites, no — we deploy via a JSON-LD utility (schemaMarkup.js style) and inject in Helmet / next/head. Custom templates may need 1–2 hours of dev time.
03Will schema replace the need for content?+
No. Schema is the structure, content is the substance. AI engines need both — a well-formed entity graph AND atomic, evidence-led prose.
04What about WordPress / Webflow / Shopify?+
WordPress: Yoast SEO + custom JSON-LD. Webflow: custom embed blocks per template. Shopify: theme.liquid injection. We have shipped this on all three.
05Can schema get penalized?+
Yes — if you mark up content the user cannot see, claim aggregate ratings you do not have, or use schema types that misrepresent the business. We deploy only verifiable, on-page entities.
06How do we measure success?+
GSC impressions for "answer" queries, AI engine citation tracking (Perplexity Pro, monitorai.com), and CTR on rich-result pages. We hand off the dashboard.
07What is sameAs and why does it matter?+
sameAs links your entity to authoritative external profiles (Wikidata, LinkedIn, Crunchbase). It is how AI engines disambiguate your business from similarly-named ones — and how they verify legitimacy.
08Does this help local SEO too?+
Yes — LocalBusiness schema with NAP, areaServed, and openingHours is a primary trust signal for the local pack and Maps. Local SEO and AEO share schema infrastructure.
Run it
Make the entity graph indexable.
A strategy call gets you a tailored 14-day plan scoped to your CMS within 48 hours.