Plain-English guides on Answer Engine Optimisation — how AI engines choose sources, and how your brand becomes one.
The first peer-reviewed study on AI citations tested nine tactics across 10,000 queries.
What the Pew study found about clicks when AI summaries appear in Google Search.
A practical Australian baseline for AI search readiness, using official adoption data and a transparent framework for measuring whether brands can be found, understood and cited by AI systems.
A rigorous template for documenting AI visibility work without cherry-picking prompts, overstating causation or presenting one screenshot as evidence.
A transparent methodology for comparing how often Australian brands are mentioned, recommended and cited across major AI answer engines.
A plain-English definition of AEO, why it matters now, and how brands earn citations inside ChatGPT, Perplexity and Google AI Overviews.
How generative AI engines assemble answers, how GEO differs from AEO and SEO, and how brands get surfaced inside AI-generated responses.
They share DNA but optimise for different outcomes. Here’s how AEO and SEO differ — and why you need both.
Typical retainers, audit pricing, cost drivers and how AEO pricing compares with SEO.
A practical comparison of how brand visibility differs between ChatGPT search and Google AI Overviews, and what website owners should optimise for in both.
A practical measurement system for tracking brand mentions, recommendations, citations and referral traffic across AI search experiences.
A practical comparison of three AI discovery environments and the implications for brand monitoring.
A plain-English explanation of why AI systems select some sources over others, and what brands can improve without chasing shortcuts.
How entity clarity helps AI systems understand what a business is, where it operates and when it should be recommended.
How to test whether FAQ schema affects machine understanding without confusing correlation with causation.
A practical framework for testing whether cleaner canonical signals improve source consolidation and retrieval consistency.