Case Study

From Website Copy to AI-Readable Authority

An AEO/GEO Website Optimization Case Study

A portfolio build by Finlay Systems — an internal Finlay Systems AEO/GEO implementation project, applied to our own site, not a paid client engagement.
ChatGPTWordPressBBH Custom Schema PluginSchema.org ValidatorGoogle Rich Results Test

Client context

Finlay Systems’ own consulting website — an internal project, not a paid client engagement. The goal was not to guarantee AI rankings or “hack” AI search — it was to make Finlay Systems easier for AI systems to understand, classify, extract, and recommend when users ask questions about AI consulting, workflow automation, and AI visibility for NYC real estate teams.

The challenge

Traditional SEO helps websites rank in search results. AEO and GEO are different — they focus on whether AI systems can understand a business well enough to mention it, cite it, summarize it, or recommend it inside an AI-generated answer. The site had none of the foundation that requires: no structured schema markup, no explicit entity language, thin FAQ content, unclear E-E-A-T signals, and no stated, repeatable relationship between David Finlay, Finlay Systems, AI consulting, NYC real estate, and AEO/GEO itself.

AI systems cannot recommend what they cannot clearly understand.

The cost of the problem

This wasn’t a time-savings problem, it was a visibility gap, and the baseline made that concrete: zero schema types deployed anywhere on the site, no FAQPage structured content on any priority page, no explicit positioning statement anchoring the website, LinkedIn profile, and service pages to the same language, and no repeatable process for testing whether AI tools could describe the business accurately at all.

The goal

Make Finlay Systems clearly understood as an AI consulting firm for high-volume NYC real estate teams across every AI-facing surface — website, schema, LinkedIn, FAQs — and put a repeatable testing process in place to monitor that understanding over time, without claiming or promising guaranteed AI rankings.

The existing workflow

Before
  1. 1No schema markup anywhere on the site
  2. 2Positioning implied, not stated
  3. 3LinkedIn and website out of alignment
  4. 4FAQ content thin or absent
  5. 5No process to test AI visibility at all
After
  1. 1JSON-LD schema across every priority page
  2. 2One explicit positioning statement, repeated everywhere
  3. 3LinkedIn optimized first, then the website
  4. 4Buyer-intent FAQ content on every priority page
  5. 5A manual AI-visibility testing tracker, run on a cadence

The AI system

The core positioning statement, “I specialize in AI consulting for high-volume NYC real estate teams,” became the anchor for the website, LinkedIn profile, schema, service pages, FAQs, and testing process. Audit the site for schema and entity gaps → generate JSON-LD schema with AI assistance → implement it in WordPress → validate it with independent tools → rewrite priority page content around the same positioning statement → add a dedicated buyer-intent page → test AI visibility on a recurring cadence with real buyer-style prompts.

Implementation

Seven layers, in order:

1
Positioning
The core exclusivity statement, repeated identically everywhere.
2
Authority
Credentials, real estate experience, testimonials — the E-E-A-T signals AI systems weigh.
3
Content
Priority pages rewritten with clearer headings, FAQs, and direct answers.
4
Schema
JSON-LD for company, founder, services, offers, FAQs, articles, events, breadcrumbs.
5
Implementation
Schema added in WordPress via BBH Custom Schema Plugin, after WPCode failed to reliably render it.
6
Validation
Schema.org Validator and Google Rich Results Test, before anything was considered done.
7
Monitoring
A manual AEO testing tracker, run on a recurring cadence rather than a one-time check.

Schema types deployed: Organization, ProfessionalService, Person, WebPage, Service, OfferCatalog, Offer, FAQPage, Article, BlogPosting, TechArticle, CreativeWork, Event, BreadcrumbList, ItemList, CollectionPage, AboutPage, ContactPage.

Human oversight and safeguards

  • Every schema block validated with two independent tools (Schema.org Validator, Google Rich Results Test) before being considered live, not just deployed and assumed correct.
  • The positioning statement was set deliberately, once, by David, and every downstream page, FAQ, and schema block was checked against it rather than allowed to drift.
  • AI-generated schema was reviewed before implementation — AI drafted the JSON-LD, a human confirmed it matched the actual business before it shipped.
  • No claim of guaranteed AI rankings anywhere in the output — the project’s own framing is explicit that AEO/GEO improves the foundation, not a promised result.

Results

These are operational, foundation-level metrics — this project is new enough that revenue-attributable results aren’t yet available, which is why they’re reported honestly as operational rather than financial.

0

Structured schema types deployed across priority pages, up from zero

0

Single positioning statement now consistent across website, LinkedIn, and schema

All

Priority pages (Home, Services, About, Contact, buyer-intent page) rewritten with explicit FAQ content

Ongoing

Manual AI-visibility tracker now run on a recurring cadence

Business impact

The biggest outcome wasn’t a single ranking — it was a reusable AEO/GEO framework. Finlay Systems went from having no structured way to know whether AI tools understood the business at all, to having schema deployed across every priority page, FAQ content addressing specific buyer questions, website and LinkedIn brought into alignment, and a testing process to monitor it going forward. A real estate team doesn’t only need to rank on Google anymore — it needs to be understood by AI systems when prospects ask “Who are the best real estate agents in the West Village?”

I couldn't tell you before this whether an AI tool would describe my business accurately. Now I have a process to actually check.
— David Finlay, Founder, Finlay Systems

Client quote

An internal Finlay Systems project applied to its own site, not a client engagement — David’s quote above reflects the operator’s own perspective rather than a third-party client.

What happened next

The manual AEO/GEO testing tracker built during this project is now run on an ongoing cadence rather than a one-time check, and the same schema and positioning discipline established here now applies to every new page Finlay Systems ships, including its guides and case studies.

What this means for NYC real estate teams

Most real estate websites are built for human browsing. AEO/GEO requires them to also be built for machine understanding — clear entity signals, deployed schema, FAQ content addressing real buyer questions, and a repeatable way to check whether it’s working, rather than guessing.

This is the kind of practical AI workflow Finlay Systems builds for real estate teams and service businesses. If your team is losing hours each week to repetitive work, I can help identify what is worth automating.

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Frequently Asked Questions

What is AEO?

AEO stands for Answer Engine Optimization. It is the process of improving your website and online presence so AI tools can better understand, extract, cite, and recommend your business in AI-generated answers.

What is GEO?

GEO stands for Generative Engine Optimization. It focuses on improving how your brand appears in generative AI tools and AI-powered search experiences, including tools like ChatGPT, Claude, Gemini, Perplexity, and AI search results.

How is AEO different from SEO?

SEO focuses on helping web pages rank in traditional search results. AEO focuses on making a business easier for AI systems to understand and include in direct answers, summaries, citations, and recommendations.

Why does AEO matter for real estate teams?

AEO matters because prospects are increasingly using AI tools to ask for recommendations, compare service providers, and research local experts. Clear entity signals, schema markup, FAQs, and authority signals help AI systems understand what a team should be known for.

Can AEO guarantee that my business appears in AI answers?

No. AEO cannot guarantee rankings, citations, or mentions in AI-generated answers. It improves the foundation by making your business clearer, more structured, and easier for AI systems to understand.

What did Finlay Systems optimize in this case study?

Finlay Systems optimized priority website pages, entity clarity, schema markup, FAQ structure, E-E-A-T signals, LinkedIn alignment, and manual AI visibility testing.

What schema types were used in this project?

The schema included Organization, ProfessionalService, Person, WebPage, Service, OfferCatalog, Offer, FAQPage, Article, BlogPosting, TechArticle, CreativeWork, Event, BreadcrumbList, ItemList, CollectionPage, AboutPage, and ContactPage.

How do you test whether AEO is working?

AEO can be tested manually by entering realistic buyer-intent prompts into AI tools and tracking whether the business appears, whether the website is cited, how accurately the business is described, and which competitors appear.

Is AEO a one-time project?

No. AEO is an ongoing process. The foundation can be improved with schema, FAQs, content, and entity clarity, but visibility should be monitored over time as AI tools, content, competitors, and search behavior change.

What does Finlay Systems do?

Finlay Systems provides AI consulting for high-volume NYC real estate teams, including AI training, workflow automation, strategy, implementation, and AEO/GEO visibility support.