Why an AEO Tech Audit is Important
Search behaviour is shifting from clicking links to asking questions. Increasingly, users are conducting research, comparisons and decision-making within AI platforms before ever visiting a website. As a result, organisations must optimise their digital presence not just for search engines, but for answer engines and generative AI platforms.
Answer Engine Optimisation (AEO), Generative Engine Optimisation (GEO) and Artificial Intelligence Optimisation (AIO) all refer to the optimisation of websites and digital content so AI platforms can understand, extract, trust and cite your information when generating answers.
- Traditional SEO focused on rankings, clicks and traffic.
- AEO focuses on being cited, referenced and recommended by AI platforms.
- The objective is no longer just to rank — it is to be the answer.
A Sonar AEO Tech Audit Consists of 3-Key Steps:
Step 1: AI Visibility Analysis
A visibility analysis evaluates how well your content is appearing nd being selected, as an answer across AI-driven surfaces such as search assistants, chatbots, and generative answer engines. It examines where your brand is currently visible, which queries or intents you’re winning or losing, and how consistently your content is being surfaced as the authoritative response. The goal is to understand your real footprint in AI-generated results so you can identify opportunities, close gaps, and strengthen your overall answer presence.
Step 2: AEO Optimisation Checklist
The purpose of a Technical SEO Audit & AEO Checklist is to identify and prioritise changes to your website that will increase its ability to gain visibility on search engines and AI tools, including structured data, entity optimisation, content clarity, schema markup, site speed, crawlability, indexing, internal linking, semantic relevance, and alignment with AI-driven answer engines and search intent.
Step 3: Query Fanout Analysis
A query fan-out analysis helps you understand all the different ways a user’s question can be interpreted, expanded, or branched by an AI system. Its purpose is to map the full landscape of related intents, sub-queries, and semantic variations so you can create or optimise content that answers the entire cluster of user needs. By analysing this “fan-out,” you can identify gaps, detect high-intent opportunities, and structure content so AI models are more likely to select your site as the best, most comprehensive answer.