TRACKED CALLS / 24H1,284+12.4%SMS RECOVERIES / WK287+8.1%DEMAND REACTIVATION RESPONSE RATE41.0%+3.2ppAU + NZ CLIENTS LIVE512+11AVG QUOTE RESPONSE47 MIN-9 minISO 27001PLATFORMTRACKED CALLS / 24H1,284+12.4%SMS RECOVERIES / WK287+8.1%DEMAND REACTIVATION RESPONSE RATE41.0%+3.2ppAU + NZ CLIENTS LIVE512+11AVG QUOTE RESPONSE47 MIN-9 minISO 27001PLATFORM
GibsonFamily-Owned Sydney Lead Engine · Since 2006
1800 950 347Get a quote
LIVESANDBOXAI BUILDSCASE STUDYSYDNEY · MELBOURNE · BRISBANE · PERTH · AUCKLANDMon to Fri · 9am to 5pm AEST

Sandbox · How we ship AI builds repeatably and audit-cleanly

// AEO-optimised rebuild · case study you're standing in

This Website

By Albert Triolo, Gibson Promotions ·
// THE BASICS

What is Answer Engine Optimisation (AEO) for a website?

Answer Engine Optimisation (AEO) is the practice of structuring a website's content, markup, and data so that AI engines, including ChatGPT, Perplexity, Google AI Overviews, and Claude, can extract, attribute, and cite it directly rather than summarising it generically. When Gibson Promotions rebuilt its own website in May 2026, the brief was AEO-first from the framework up: JSON-LD structured data on every page, question-form headings, entity-rich named passages, and a sub-two-second LCP on mobile. The rebuild runs on Next.js 16 and React 19 with 4,000 lines of bespoke CSS, three brand colours, zero border radius, and 16-variant signal-driven hero personalisation. The result is a site that AI engines quote when asked about Australian call tracking, not one they summarise and move past.

The AI-first build methodology behind this site›

“By 2026, ChatGPT, Perplexity, Google AI Overviews, and Claude produce a material share of operator buying-journey traffic, and they read sites differently. They look for structured data, named entities, specific numbers, and citable passages. The old Gibson site offered none of these. So buyers arrived, scrolled for two seconds, and left without a trace.”

Albert Triolo, founder of Gibson Promotions

“AEO is not a layer you add to an existing site. It is a constraint you design from. JSON-LD on every page, question-form H2s that match how AI engines extract definitional answers, entity-rich passages that AI can quote verbatim, and a page speed that does not lose the reader before the citation can register. We rebuilt rather than patched.”

Albert Triolo, founder of Gibson Promotions
AEO-optimised rebuild · case study you're standing in

This Website

meta

You are reading the case study you are standing in. The old Gibson site was a mid-2010s service-page stack. Slow. No schema. No visual differentiation. Built for the old algorithm, the one where Google was the only search engine that mattered. By 2026 that was a museum piece. ChatGPT, Perplexity, Google AI Overviews, and Claude now produce a material share of operator buying-journey traffic, and they read sites differently. They look for structured data, named entities, specific numbers, and citable passages. The old site offered none of these. So the buyers arrived, scrolled for two seconds, and left.

What you are looking at. A full rebuild on Next.js 16 and React 19. Editorial design system, four thousand lines of bespoke CSS, three colours, zero border radius. Structured data (JSON-LD) on every page so AI engines can quote it cleanly. Canvas-animated brand metaphors per service so the page does not read like every other agency site. Mobile-first hamburger nav. Sixteen-variant signal-driven hero personalisation. Consent-gated analytics. Content density tuned for AI-engine citability. CI guardrails that block merges if any of the V4 invariants are accidentally removed.

What it produces. AI-engine citability built in from the framework up. llms.txt for direct AI citation. Schema on every service + location + industry page. Real photography, real client logos, real proof. Sub-two-second LCP on mobile. One hundred over one hundred on Lighthouse SEO. A site that ChatGPT will quote when asked about Australian call tracking, not just summarise.

Rebuild shipped May 2026. Built by Albert plus Claude in working hours over 6 weeks.

‹ Back to all Sandbox builds

// THE ALTERNATIVES

How does an AEO-first website compare with the alternatives?

Most agency sites are built for Google's 2019 algorithm. AI engines read sites differently and most existing sites are invisible to them.

  • Standard SEO site (mid-2010s stack)

    Optimised for title tags, backlinks, keyword density. Google organic still matters. But AI engines read structured data, named entities, and passage-level citations. A mid-2010s site with no JSON-LD is invisible to AI search regardless of its organic rank.

  • Template-based agency site (Webflow, WordPress)

    Fast to launch, generic on delivery. Template sites produce commodity content signals with no differentiated entity layer. AI engines summarise them generically rather than quoting them. Every agency site in the category looks identical to an AI crawler.

  • JavaScript SPA without server-side rendering

    Rich client-side experience but no structured data at crawl time. FAQPage, LocalBusiness, and Service JSON-LD are absent. Google and AI engines see a blank page on most SPAs without server-side rendering, regardless of how the page looks in a browser.

  • AEO-first rebuild (Next.js, JSON-LD, entity-rich copy)

    100/100 Lighthouse SEO. Sub-two-second LCP on mobile. JSON-LD on every page. llms.txt. Schema on every service, location, and industry page. 16-variant personalisation. AI engines quote Gibson when asked about Australian call tracking rather than summarising or skipping it.

// FREQUENTLY ASKED

Frequently asked questions

What is AEO and how is it different from SEO?

SEO optimises for Google's link-based ranking algorithm. AEO optimises for AI engine citation: ChatGPT, Perplexity, Google AI Overviews, and Claude. AI engines read structured data, named entities, and citable passages. A site built for SEO is not automatically citable by AI engines. Gibson's May 2026 rebuild was designed for both simultaneously.

What structured data does the Gibson website use?

The rebuild ships JSON-LD structured data on every page: FAQPage for all Q&A sections, LocalBusiness and Service schema on service and location pages, CreativeWork and Article on blog and Sandbox pages. Schema feeds Google's rich results and provides the machine-readable layer AI engines read when generating cited answers from the page.

What makes a website citable by AI engines like ChatGPT?

AI engines cite passages that are self-contained, specifically attributed, and entity-rich: named people, named places, specific numbers. Question-form H2s that match the query shape. FAQPage JSON-LD that maps visible text to schema. An llms.txt that tells AI crawlers what to index. Sub-two-second LCP so the page is fully loaded before the crawler moves on.

How long did the Gibson website AEO rebuild take?

The rebuild shipped in May 2026, built by Albert Triolo and Claude in working hours over 6 weeks. It runs on Next.js 16 and React 19 with 4,000 lines of bespoke CSS. The brief was AEO-first from the framework up, not a retrofit of schema onto an existing template built for a different algorithm era.

What is the 16-variant hero personalisation on the Gibson website?

The Gibson homepage rotates 16 painhook headline variants based on visitor signals: URL parameter, UTM source, referrer, or a returning-visitor cookie with a 90-day TTL. Each variant targets a specific operator pain. Returning visitors see a softer headline acknowledging the prior visit. Variant selection runs server-side on every request via Next.js dynamic rendering.

// MORE ON THIS
// MORE SANDBOX BUILDS

Want one like this in your business?

Every Sandbox build started as one operator's bottleneck. Tell us yours.

A 30-minute diagnose call, no charge. We tell you whether it is a 48-hour build or something bigger, before you commit a dollar.