The problem this solves
A growing share of buying research now starts as a question to an AI assistant, and the answer arrives with a handful of citations that function as the new page one. Most teams have no idea what those answers say about their category: which brands get named, which sources get cited, whether their own product appears at all. Checking manually means typing dozens of prompts into multiple engines, screenshotting answers that change between sessions, and trying to tally the patterns by eye.
Flying blind here has a specific cost: the recommendations are being made either way. If assistants consistently send buyers to two rivals and a review site, that is a distribution channel you are absent from, and no amount of traditional ranking data will reveal it. The starting point is simply measurement - a structured read of where your buyers' actual questions lead, captured as evidence a leadership team can act on.
How the mission runs
- Build the question set. The mission starts from 25 questions real buyers ask in your category - you can supply them, or the agent drafts the set from your positioning and refines it with you. Good questions span the funnel, from problem framing through to direct comparisons.
- Query the live engines. AI Visibility runs each question against the live AI answer engines and captures the full responses: which brands are named, which sources are cited, and how each recommendation is framed. Responses are recorded verbatim with timestamps, since answers shift over time.
- Score the landscape. The agent tallies citations and mentions into a visibility scorecard: your appearance rate, each competitor's, and the third-party sources - review sites, communities, publications - that assistants lean on. The sources matter most, because they are the surfaces you can actually influence.
- Find the patterns behind the citations. For questions where rivals win, the agent inspects what got cited and why it was quotable: format, freshness, directness of the answer. These patterns become the basis of the five moves, each tied to specific questions you can realistically win within a quarter or two.
- Build the Gamma deck. Findings land as a Gamma presentation: the scorecard, verbatim answer excerpts as evidence, the citation-source map, and five prioritized moves with the expected effect of each. The deck is staged for your review first, so you control when and where it circulates.
The prompt
This is the exact objective the agent receives. Swap the obvious placeholders for your own domain, segment or channel and run it as-is from the console, Slack, or the API.
What comes back
A Gamma deck built for a leadership audience: your citation scorecard across 25 buyer questions, verbatim excerpts showing exactly how assistants describe the category, a map of the sources those answers rely on, and five concrete moves ranked by expected impact - each tied to the specific questions it targets. The raw captures stay attached to the mission run as the evidence base.
Make it yours
- Re-run the same 25 questions monthly and add a movement slide, turning the deck into a trend report on your AI visibility over time.
- Focus all 25 questions on one product line or segment when a launch or a struggling category needs the sharper, deeper read.
- Add your top three competitors' names to the question set directly to see how the assistants handle head-to-head comparison prompts today.
Frequently asked questions
How are the AI assistants actually queried?
AI Visibility sends each question to the live answer engines at run time and captures the actual responses, so the deck reflects what a buyer would have seen that day. Nothing is simulated or estimated; every excerpt in the deck comes from a recorded answer with a timestamp.
Answers vary between runs - is one snapshot meaningful?
A single run establishes a defensible baseline: consistent patterns across 25 questions are signal even when individual answers wobble. The deck reports patterns over one-off phrasings, and monthly re-runs separate durable position from noise. Most teams treat the first deck as the starting line.
Can I see the full answers behind the deck?
Yes. Every capture - question, engine, full response, timestamp - is stored with the mission run. The deck quotes excerpts for readability, and any slide can be traced back to its complete source answers when someone asks how a conclusion was reached.