AEO audit your AI-search baseline.

An AEO audit is a baseline measurement of how AI engines answer your buyer prompts: whether you are cited, your share of voice, and which sources decide each answer. Prefer runs one for free, with no card. An audit is the first step of answer engine optimization, and it ends with measurable targets rather than a to-do list.

How an AEO audit works#

An audit runs a representative set of buyer prompts across the engines that matter (ChatGPT, Claude, Gemini, Perplexity, and Google’s AI surfaces) and reads each answer for three things: are you named, are you cited as a source, and who is cited instead. It is the audit stage of the closed loop that Monitor and Act build on.

Loop diagram of three steps. 1. Audit: baseline your citation rate, share of voice, and the sources deciding each answer, ending with measurable targets. 2. Monitor: track citations across ChatGPT, Gemini, Perplexity and Google's AI surfaces, next to your GSC, GA4 and AI-referral data. 3. Act: ship comparison content, entity and schema fixes, and authentic off-page proof. The loop repeats and each cycle compounds the last.

The audit’s own steps are simple to describe and precise to run:

A 4-step path. 1. Pick the prompts (Choose the buyer questions that decide a purchase in your category); 2. Run across engines (Send each prompt to every AI engine that matters to your buyers); 3. Record the answer (Log whether you're named, whether you're cited, and who is cited instead); 4. Set targets (Turn the baseline into measurable goals for citation rate and share of voice).

Why an AEO audit matters#

You cannot improve AI visibility you have not measured, and the first honest number is almost always low. A low first number is not discouraging. It is the baseline every plan is measured against.

The audit’s most useful output is often the source list. In Prefer’s 2 September 2026 ChatGPT run of 50 buyer prompts about AI visibility tools, the techradar.com domain was cited across 12 of 47 usable answers, and the recurring shortlist across the category was a handful of named competitors. Knowing which sources decide your answers tells you exactly where the work is.

Funnel diagram. A buyer asks an AI assistant for the best software in a category. The assistant builds its answer from third-party sources it trusts: G2 review grids, Reddit communities, and comparison lists, all heavily weighted, while your own website barely counts. The result is a ranked shortlist of competitors that does not include your product.

What an AEO audit measures#

Summary graphic of 4 items: 1. Citation rate: The share of tracked prompts where an engine cites your site as a source. 2. Share of voice: How often you're named versus the competitors in the same answers. 3. The sources cited: Which third-party pages the engines trust to build your category's answers. 4. Entity grounding: Whether the engines recognize your brand as an entity or guess about it.

AEO audit vs a traditional SEO audit#

A traditional SEO audit checks technical health, keywords, and backlinks against Google’s ranked results. An AEO audit checks something different: whether AI engines mention and cite you in their synthesized answers, and which sources they trust to build those answers. Google states that its AI features need no special optimization beyond standard SEO, which is exactly why an AEO audit measures a separate thing: not whether your SEO is healthy, but whether engines actually cite you. One is about ranking a page; the other is about being in the answer.

Example#

A B2B software brand runs an AEO audit and learns it is cited in 1 of 40 category prompts, its share of voice is 4 percent against three competitors, and two review sites plus one Reddit thread supply most of the answers. That is a baseline (4 percent), a target (climb it), and a map (fix the review profiles, earn the Reddit mentions, publish the missing comparison pages).

How Prefer helps with an AEO audit#

Prefer’s audit measures your citation rate, share of voice, and the sources behind every answer across each engine, and ends with the specific targets Monitor and Act then work toward. Run a free AI visibility audit to get your baseline.