AI visibility report template

What an AI Visibility Report Tracks

An AI visibility report measures how well a brand or a set of pages shows up inside AI answers - the responses that chat assistants and AI search features generate when someone asks a question in your client's space. Unlike a ranking report, it is not about position one through ten on a results page. It is about whether the model knows your client exists, whether it cites the right pages, and whether the facts it repeats about them are correct. This template gives that work a fixed shape so you produce the same deliverable each cycle instead of improvising a new document every time an assistant changes its behaviour.

The report is built for agencies and freelance consultants who are starting to field the question "are we showing up in ChatGPT or Google's AI answers" and need an honest, repeatable way to answer it. It pairs with the AI search visibility checklist and the generative engine optimization report elsewhere on this site: the checklist tells you what to fix, this report tracks whether the fixes moved anything over time. Every example in the file is synthetic, so you can adapt it to a real account without exposing anyone's data.

How the Workbook Is Organized

The workbook is split into tabs that follow the path of a single question through an AI system: which prompts you test, what the model answered, which pages it cited, where it got things wrong, and what you plan to do about it. Each tab can be filled independently and then rolled up onto a front summary page, so a client who only wants the headline can read it in a minute while you keep the working detail underneath.

• Prompt coverage: the question set you test on, grouped by buyer intent, so coverage is a deliberate list rather than whatever you happened to type that week.
• Answer capture: the assistant's response for each prompt, recorded as your own observation with the engine and date, never as a screenshot reused from a third-party product.
• Cited pages and entity clarity: which of the client's URLs the model pulled from, and whether it described the brand, products, and people accurately.
• Answer gaps and action notes: prompts where the client is absent or misrepresented, paired with the specific next move and an owner.

Field Map

Each prompt you test is recorded as one row using the same set of fields, so results stay comparable from one reporting cycle to the next. The map below explains what each field is for and how to fill it honestly without inventing numbers the assistants do not give you.

Filling It During an Engagement

Start by building the prompt set, because everything else depends on it. Sit with the client and write the questions a real buyer would ask an assistant - comparison questions, "best tool for" questions, how-to questions, and questions about the client by name. Keep that list stable across cycles so you are measuring change rather than measuring a different test each time. The AI search visibility checklist generator can help you turn a topic into a starting prompt set if you are working from a blank page.

Then run each prompt yourself in the engines that matter for the account and record what you actually see. Capture the answer, note which pages were cited, and flag whether the brand was present, absent, or described incorrectly. Resist the urge to fix things mid-pass; the value of the report is the gap list at the end, where you can see which missing or wrong answers are worth the effort to correct. Convert the highest-value gaps into action notes that name a page to publish or change, not a vague intention to "improve content".

• Lock the prompt set with the client before the first run so later cycles are genuine comparisons.
• Record answers as dated first-hand observations, since AI responses vary by session and over time.
• Mark each prompt as present, absent, or inaccurate rather than scoring it with an invented number.
• Turn the top gaps into specific, owned action notes tied to a real page or entity fix.

Checks Before You Send It

AI visibility is a young, noisy signal, so the report earns trust by being careful about what it claims. Before delivery, confirm that every answer you reported was something you observed directly, with the engine and date noted, and that you have not implied a stable ranking where the assistant actually gives different answers on different days. The honest framing is "here is what we saw across these runs and what changed," not "we are ranked first in AI."

Run the front summary past the same standard you would apply to any client report: it should name the few gaps that matter, tie each to an action, and avoid leaning on counts that look precise but are not reproducible. Pair the finished report with the AI visibility checklist PDF so the client can see both the measurement and the remediation list in one handover.

• Every recorded answer has an engine name and a date, because results are not stable.
• No invented percentages or visibility scores; describe presence, absence, and accuracy in plain terms.
• Each flagged gap has a concrete action and an owner, not a generic recommendation.
• No third-party tool screenshots reused as report content; observations are your own.