Walkthrough · AI Visibility
“How do we get ChatGPT to talk about our brand?”
Every agency is hearing that question. This is the walk that answers it with measurements — what you run, what each number means in a client meeting, and how every finding arrives with the recommended action already attached. The craft is included: how the numbers become conversations, and the conversations become retainers.
The whole walk · five stops
From the question to the signed work
Every AI visibility engagement follows the same five stops. The rest of this page walks them one at a time — what you run, what each number means, and how every finding becomes work a client signs off on.
It starts with fifty questions — the client's, not ours.
AI visibility isn't measured in keywords. It's measured in the questions real buyers ask, and what five different engines answer.
Step 1 · Point it at the brand
Fifty questions across five lanes
The pulse runs on a question pack: fifty real buyer questions in five lanes — category, brand, comparisons, use cases, reputation. There are two roads to a pack, and both end with you in control.
Then you press run, and the engines answer for themselves.
Step 2 · The run
Fifty questions, five engines, 250 live answers
Every question is asked live, with web search on — the mode buyers actually use — pinned to the client's market. Each answer is kept whole, along with every source the engine cited.
A few minutes later, you're reading deep insights — and exactly where action will create impact.
Not traffic. Not rankings. What the AI engines actually say when buyers ask about the client — measured, compared to competitors, and tracked month over month.
Step 3 · Read the numbers
Measurements your clients will value — each one opens a conversation
A few minutes after you press run, the dashboard fills. These aren't rankings borrowed from search — they're measurements of the AI answers themselves. And every one of them maps to a conversation you can have the same week.
Of fifty answers, how many named the brand at all — one rate per engine, side by side, lined up against how frequently each competitor is named. And behind every rate: the sentiment, and every source the engine used while forming its answer.
Across the unbranded category and use-case answers: what share of the mentions belong to the client, and what share to each rival. One brand can sit at 27% while the nearest rival holds 15 — or the other way around.
When an engine mentions the client, is it reading their website — or someone else's version of them?
Where the client shows up, by question type and engine — brand questions vs comparisons vs use cases — with a delta chip on every cell.
When engines quote complaint themes on “is it legit” questions, that's not an error to hide — it's what shoppers hear at the moment of purchase doubt, quoted verbatim.
Every number carries its change since the last completed run of the same pack — the pulse re-measures, so improvement is visible, not asserted.
And the numbers aren't even the deep part.
Step 4 · The answers, verbatim
Read the exact answer the buyer saw
Behind every number sits the answer itself. The answers browser holds all 250, verdict-tagged per engine per question — and one click opens the full text, exactly as a buyer received it.
Four engines answered a trust question with complaint themes; one never named the brand at all. The verbatim answers — with every claim and every cited source — sit one click below the pills. Show the client the actual answer. Nothing you paraphrase will land harder than what the engine really said.
The engines disclose the searches behind their answers — and the pulse keeps them. Whether each engine went to the web at all, and the exact queries it wrote for itself:
Step 5 · Open the sources
Every answer came from somewhere. That's the audit.
The pulse detects every page of citations behind the answers. Before anything else runs, you see the shape of the problem: which sources already name the client, which name a rival instead, and which name nobody — open ground. Then the audit opens the pages and reads them.
The proof column matters as much as the gaps: the sources already naming the client are what's working — the audit shows what to defend, not just what to fix.
Every source carries its engine roster — which of the five cited it, and which didn't. A page used by two or more engines is consensus ground; a page all five lean on is load-bearing for the client's whole AI presence.
This is where it stops being a report and becomes a work order.
Five lanes of sources, each analyzed for you — sentiment scored, crossovers counted, competitors flagged, and every recommended action tagged with who owns it.
Step 5 · The five lanes, worked one by one
Every lane arrives analyzed, with the moves already written
You choose which lanes to open, and how deep. Each one comes back the same way: an AI analysis of everything the lane read, action items tagged for who owns them — agency, client, or community — and every source carrying its verdict, its author, its date, and a realistic path to inclusion.
Most of this lane is round-ups — and the same rival cluster recurs across independent lists, a shelf your client sits outside. The split that matters: some pages include the client and pass them over; most never name them at all. Those are two different problems with two different fixes.
Every read records who wrote the page, when, and where the client sits on it — ranked first on one list is a different fact from twelfth of fifteen on another. Some negative framings turn out to be competitor-owned properties wearing an editorial costume; institutional explainers often name no brand at all — open ground.
The threads the engines cite split three ways: threads that praise, threads that pile on, and threads where the client is absent while rivals fill the space unopposed. The heaviest-upvoted rooms are often the hostile ones — and a thread can be years old and still shaping this month's answers.
Presence usually isn't the problem — framing is. Solo-creator verdict videos from years back can still shape this month's answers. Every cited video's transcript is read in full, with the client and every rival highlighted at the exact timestamps where they're discussed — who said it, in what light, and what the video concluded.
This lane is pure reputation ground: pages that are about the client, read and scored for sentiment. Recurring bylines emerge — the same dietitian or reviewer behind multiple cited pages — along with brand-safety flags the client may not know exist, sitting unanswered on pages the engines keep reading.
None of it asks you to go digging.
That's the difference this page exists to show: the finding, the evidence, and the move arrive together — and the move is billable.
Step 6 · The platter, priced into the retainer
Insight → move → next month's delta
This is the loop that turns a report into recurring work. Every insight carries a move; every move is measurable by the next pulse; every delta is the first slide of the next meeting.
written by the analysis
agency · client · community
the pulse re-measures it
And then you land the work — in whichever shape the moment calls for.
Step 7 · Land the work
Two ways this lands — the engagement, and the pitch
The same instrument serves both ends of the pipeline: keeping the clients you have, and winning the ones you want.
The white-label client report carries the whole record — verdict, scoreboard, share of voice, the lanes, reputation, exhibits, the full citation audit, recommended actions, and appendices down to complete video transcripts. You choose which sections each report includes.
And the Pulse History keeps every run: reports regenerate from the stored answers — nothing goes stale, and deltas compare completed runs of the same pack. The month-two meeting opens with a number that moved.
Run the pulse on a prospect before you've ever spoken. The report arrives wearing your agency's name and logo — and for the brand that isn't showing up, the gap is the pitch: here's who owns your AI shelf, and here's the plan to take it back.
This is the same over-the-top move from the Agency Lead Gen walkthrough — deliverable-grade value that shows you've done the homework, you want to help them grow, and you're the agency to do it.
These reports run long — typically 200 to 250 pages — so nobody emails a PDF. Download the report as a single self-contained page, drop it on your own website, and send one link. What opens is deeper than anything they've seen, wearing your name, your logo, your domain.
Connect the client's Google Analytics — one click, read-only, saved for that client only — and every run joins two sides of the story: the engines cite you, and the engines send you people — measured visits arriving from the AI engines, beside how often each one cites the brand.
The honesty is built in: visit counts are floors, engines with no measured sessions show as “watching” — never an invented zero — and it reads as directional evidence, because nobody can trace a single AI answer to a single sale. It's still the closest thing to demand-side proof this young channel honestly supports, and it's measured straight from the client's own Google Analytics.
One more deliverable falls straight out of the run: the AI reads the client's live site and writes a proposed llms.txt against the pulse's own gap map — so the questions the brand is losing get answered where the engines look.
A found file is improved, never replaced — what's working is kept, the gaps the pulse measured get filled, and every change is listed for review before anything ships.
Fair note: the industry is still debating how much weight the engines give llms.txt. Until that settles, the file ships correct, current, and reviewed — whichever way the argument lands, your client is already covered.
- Single answers vary run to run — aggregates and deltas are the evidence, and deltas always compare completed runs of the same question pack.
- “Not retrieved” is not “locked in” — engines update over time, and the pulse re-measures every run. Building the brand's record on the web is the long game.
- The audit reads only what opens — pages that refuse automated readers are never counted against you, and you keep the links.
- AI visit counts in the Attribution Read are floors — real measured sessions, never estimates.
Fifty questions, five engines, one client who finally has the answer.