Perth, Western Australia · AI Search Research

AI SEO Perth: Research, Data & Guides to AI Search Visibility

New research · published 13 September 2026

Between 60% and 78% of AI-recommended businesses did not appear in the Google Maps top 20 for the same question.

200 questions · 3 runs each · 4 AI systems · 2,400 recorded answers · Perth, WA · 8 to 10 September 2026

Perth AI Search Study 2026. Methodology v2.0, with the observation dataset, the full method and the limitations published alongside it.

AI SEO Perth monitors and documents how AI-assisted search affects businesses in Perth, Western Australia. It records how systems such as ChatGPT, Google AI Overviews, Gemini and Perplexity retrieve, cite and recommend sources for Perth prompts, publishes the definitions and methodology behind that work, and releases the data as it is collected.

All research Data and downloads Read the methodology

A research and reference publication published by Search Scope. Methodology v2.0, updated 2026-09-11.

What is AI SEO in Perth?

AI SEO in Perth is the practice of making a Perth, Western Australia business visible to AI-assisted search: the systems, such as ChatGPT, Google AI Overviews, Gemini and Perplexity, that retrieve sources and compose an answer instead of listing links. It covers whether those systems can reach a site, identify the business, retrieve the right passage, and cite or recommend it when someone asks a Perth question.

The term is used loosely in the market. Generative Engine Optimisation and Answer Engine Optimisation describe overlapping ideas, and this publication keeps a reference definition of AI SEO alongside separate entries for GEO and AEO so the terms stay distinguishable. What none of them means is control over an AI system's output. The documented levers are access, identity, retrievable content and corroboration; whether a given answer names a given business is something to observe, not promise.

What the publication tracks

One observation record per prompt, per platform, per run. These are the fields every study records; counts for the published rounds are in each report and in the observation data.

What the publication tracks
Tracked	What is recorded
Brand mentions	Every business named in an answer, recommended or not.
Recommendations	Brands presented as a shortlist, in the order given.
Cited domains	The domains behind each citation, classified by source type.
Cited URLs	The exact pages cited, so recurring source pages surface.
Source overlap	Which sources recur across prompts, platforms and runs.
Platform differences	One prompt set, every platform in scope, compared side by side.
Query and prompt classes	Informational, commercial, comparison, recommendation, local, brand, competitor, trust-validation.
Change over time	Repeated rounds on a fixed prompt set so movement is measured, not assumed.

View the data model

Perth AI search observatory

The research programme runs a fixed set of Perth prompts across each platform in scope, repeats every prompt, and records who was named, who was recommended and what was cited. Repetition is the point: a single answer is an anecdote, a frequency across runs is an observation.

Explore Perth findings · Industry observatory

Published

Perth AI Search Study 2026

We asked four AI systems 200 commercial questions about 20 Perth industries, three times over three days, and recorded 2,400 AI answers. Most of the businesses they recommended were not the ones ranking at the top of Google Maps, and most recommendations changed between runs.

Google AI Overviews
Google AI Mode
ChatGPT
Gemini

Updated 2026-09-13

Read the report

Latest research and reference

Published

Perth AI Search Study 2026

Google AI Overviews
Google AI Mode
ChatGPT
Gemini

Updated 2026-09-13

Read the report

Planned studies: ChatGPT Perth Recommendation Study · Gemini Perth Recommendation Study · Google AI Overviews Perth Source Study. See the programme.

Core definitions

Each definition opens its own reference page with a standalone answer, key facts and sources.

AI SEO: AI SEO is the practice of making a business visible to AI-assisted search: systems such as ChatGPT, Google AI Overviews, Gemini and Perplexity that retrieve sources and compose an answer rather than listing links. It covers whether those systems can reach a site, identify the business, retrieve the right passage and cite or recommend it. In Perth, Western Australia, that means being one of the sources an assistant draws on when someone asks a Perth question.
Generative Engine Optimisation: Generative Engine Optimisation (GEO) is the practice of improving how visible a source is in the answers composed by generative engines, the search systems that use a large language model to synthesise a response with citations. The term was introduced in a 2023 research paper that tested content changes against a benchmark of queries. In practice GEO overlaps almost entirely with AI SEO; the difference is origin and emphasis, not mechanism.
Answer Engine Optimisation: Answer Engine Optimisation (AEO) is the practice of structuring content so a search system can extract it as the direct answer to a question. It predates generative AI: featured snippets, voice assistants and knowledge panels were the original answer engines. AI Overviews, AI Mode and chat assistants extend the same demand for passages that answer a question plainly, near the top, in a form that stands on its own when lifted from the page.
AI search optimisation: AI search optimisation is the work of making a source usable by AI-assisted search: systems that retrieve documents at answer time, compose a response with a language model, and attach citations to some of what they used. It differs from optimising for a ranked list because the unit is the retrieved passage and the outcome is being composed from and cited, not a position. What the platforms document is access and eligibility; how they select among eligible sources is largely undisclosed.
ChatGPT SEO: ChatGPT SEO is the work of making a business reachable and usable by ChatGPT when it searches the web to answer a question. OpenAI documents three agents: GPTBot gathers training data, OAI-SearchBot indexes sites for ChatGPT's search features, and ChatGPT-User fetches pages when a user asks. Sites that opt out of OAI-SearchBot are not shown in ChatGPT search answers. How ChatGPT ranks the sources it retrieves is not documented.
Google AI Overviews: Google AI Overviews are generative summaries shown at the top of some Google Search results, with links to supporting pages. Google states they are a core Search feature drawn from the normal Search index: a page must be indexed and eligible for a snippet to be a supporting link, there are no additional requirements, and no special markup is needed. AI Overviews are available in Australia, so they appear for Perth searches.

All reference pages and glossary

Why Perth is its own research environment

Each dimension is labelled by how well it is established. A hypothesis is a reason to measure something, not a claim that it changes what an AI system does.

Perth research dimensions
Dimension	Why it matters for observation	Status
Local intent	Perth prompts are often recommendation or comparison prompts with a place attached, which narrows the eligible sources before any other factor applies.	INFERRED
Australian source ecosystem	ABN Lookup, ASIC, state regulators, Australian directories, review platforms and Australian publishers are candidate sources. Which ones get cited for Perth prompts is a question for observation.	HYPOTHESIS
Local business entities	Whether a Perth business is identifiable and consistent across its site, Google Business Profile, directories and registries is a measurable property of that business.	DOCUMENTED
Local organic search	Google documents that AI Overviews and AI Mode draw on its index and core ranking systems, so Perth organic performance is an input to Google surfaces.	DOCUMENTED
National versus Perth prompts	The same question with and without "Perth" can return different brands and sources. The gap is part of the programme design.	HYPOTHESIS

Perth market reference

How observations are collected

Methodology v2.0, published 2026-09-11. Versioned, so every observation says which rules it was collected under.

Read the methodology

Fixed prompt sets. Prompts are written once per study and kept constant across rounds.
Repeated runs. At least 3 runs per prompt per platform, because outputs vary between sessions.
Date, time and platform. Every record carries when it was collected, on which surface, with which model label.
Controlled sessions. A clean baseline account plus seeded personas, so personalisation shows up as divergence between profiles.
Citations and brands. Cited URLs, cited domains, brands mentioned and brands recommended, with order preserved.
Source classes. Each cited domain classified as owned, third-party, platform-owned, UGC, directory, publisher or brand source.
Variance reported. Frequencies across runs are published; a single run is never presented as a result.
No universal score. There is no GEO score here. Results are frequencies per prompt set, platform and period.

Published by Search Scope

Where a page on this site touches commercial questions, such as the cost of AI SEO in Perth, it says so and links to Search Scope once. Nothing here is a service page. About the publication.