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

Best fit for

This type of optimization is useful for businesses that want to become easier for AI tools and search engines to understand, classify, and recommend:

  • Real estate agents seeking AI-generated local recommendation visibility
  • NYC real estate teams wanting clearer online positioning
  • Brokerages wanting stronger service, location, and authority signals
  • Service businesses relying on expertise, trust, and local visibility

Overview

This case study documents how Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO) were applied to Finlay Systems’ own consulting website. 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 rebuild focused on entity clarity, schema markup, FAQ structure, content positioning, and a testing process, so Finlay Systems could be understood clearly as an AI consulting firm for high-volume NYC real estate teams.

The problem

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.

Gaps identified: schema markup presence, entity language clarity, FAQ specificity, E-E-A-T signals, explicit relationships between David Finlay, Finlay Systems, AI consulting, NYC real estate, and AEO/GEO, and no repeatable testing system.

AI systems cannot recommend what they cannot clearly understand.

The solution

The core positioning statement: “I specialize in AI consulting for high-volume NYC real estate teams.” That sentence became the anchor for the website, LinkedIn profile, schema, service pages, FAQs, and testing process.

Architecture

Seven layers, in order:

1
Positioning
The core exclusivity statement.
2
Authority
Credentials, real estate experience, testimonials.
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, Google Rich Results Test.
7
Monitoring
A manual AEO testing tracker.

How it works, end to end

  1. Define the entity — the positioning statement above.
  2. Identify authority signals — MSc in Information Systems Management (University of Galway), Certified AI Consultant (Innovating with AI), Member of the IWAI AI Consulting Group, 6+ years producing real estate media for NYC agents and teams.
  3. Choose pillar topics — AI consulting for NYC real estate teams, AI workflow automation and implementation, AEO/GEO visibility for real estate professionals.
  4. Optimize LinkedIn first — so external entity signals match the website before the website itself changes.
  5. Audit the website — schema gaps, entity clarity, E-E-A-T signals, FAQ opportunities, internal linking.
  6. Generate schema with AI — JSON-LD for who owns the business, what it does, services, audience, and page types.
  7. Add schema in WordPress — via BBH Custom Schema Plugin.
  8. Validate the schema — Schema.org Validator and Google Rich Results Test.
  9. Optimize page content — Home, Services, About, Contact, plus a new standalone buyer-intent page.
  10. Create a dedicated buyer-intent page rather than hoping AI systems infer positioning from the homepage.
  11. Test AI visibility — a spreadsheet tracker of prompts run across AI systems, turning this into an ongoing monitoring process.

Schema types used

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

Impact

This project does not claim guaranteed AI rankings. It created a stronger foundation for AI visibility: clearer positioning, schema deployed across priority pages, FAQ content addressing specific buyer questions, website and LinkedIn brought into alignment, and a manual AEO/GEO testing tracker for ongoing monitoring. The biggest outcome wasn’t a single ranking — it was a reusable AEO/GEO framework.

What this means for NYC real estate teams

A real estate team doesn’t only need to rank on Google — increasingly, it needs to be understood by AI systems when prospects ask “Who are the best real estate agents in the West Village?” or “Which NYC real estate team specializes in luxury buyers?” Most real estate websites are built for human browsing. AEO/GEO requires them to also be built for machine understanding.

About this build

This was an internal Finlay Systems AEO/GEO implementation project, using free validation tools, existing infrastructure, AI-assisted schema generation, and manual prompt testing.

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.

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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