All playbooks

For the CMO who needs one defensible number

Five playbooks in the order the board conversation goes: the number, why the answer moves, the rival on your axis, the direction over time, and the branded link you send.

5 playbooks21:43 of video
WorkflowBeginner

Does AI name you at all?

Register a brand, run one scan, and answer the board question about AI naming you, with the prompts and the rival names behind the score.

6 minutes
CMO, Marketing Director +1
Video WalkthroughAI VisibilityMetricsOnboarding+1 more
Read Playbook
WorkflowAdvanced

Show how unstable the AI answer really is

Roll one question ten times, see which brands hold across every answer and which flicker, then hand finance the PDF.

5 minutes
Marketing Manager, Marketing Director +1
Video WalkthroughStability AnalysisDice RollResponse Consistency+1 more
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WorkflowAdvanced

Track a rival on your own chart

Add a competitor as its own project, scan it with the same AI model, and draw its line beside yours on one axis over the same window.

6 minutes
CMO, Strategy Director +1
Video WalkthroughCompetitive IntelligenceCompetitive AnalysisMetrics+1 more
Read Playbook
WorkflowBeginner

Prove the needle moved, with a chart

Answer the quarterly question with a dated chart, the seven parts under the score, sentiment theme by theme, and the pages AI cited.

6 minutes
CMO, Marketing Director +1
Video WalkthroughAI VisibilityMetricsClient Reports+1 more
Read Playbook
WorkflowBeginner

Hand over a client report without building a deck

Send your client a branded, PIN-protected AI visibility report as a link they open in a browser. No account for them, no slide editor for you.

5 minutes
Consultant, Agency Owner +1
Video WalkthroughClient ReportsClient DeliverablesPublishing Workflow+1 more
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One board-ready score with every prompt and answer behind it. Rebuilding that number by hand costs EUR 3,240 to EUR 6,480 a year.

You need one number you can say out loud in a board meeting and still be standing when somebody asks where it came from.

The question arrives the same way every quarter. Does AI name us when a buyer asks the category question? Is that better or worse than last quarter? How do we sit against the two names everyone in the room already worries about? Then comes the follow-up that ends the meeting: fine, but what are they saying about us, and who built that figure?

Right now the answer is a screenshot of a chat window from last Tuesday. It does not line up against last month, it names no source, and the analyst who produced the previous version counted things slightly differently. So the movement you report upstairs may have come out of the method while the market stood still.

What it costs today

In-house and analyst time at EUR 90 an hour, agency time at EUR 120.

The board questionHow it gets answered by handCost
Does AI name us at all25 buyer prompts written once, then run and tallied on three models, 7 h at EUR 90EUR 630, first round
Is that number still true this monthre-run the battery, re-tally by brand and position, redraw the chart, 3 to 6 h at EUR 90EUR 270 to 540 a month, EUR 3,240 to 6,480 a year
Does the answer even hold stillone question rolled ten times and tallied, 1.5 to 3 h at EUR 90EUR 135 to 270 a question
Where do we sit against two rivalsthe same seven-hour audit round on each, every month, at EUR 90EUR 1,260 a month, EUR 15,120 a year
Give me something I can circulatepull the numbers, build the charts, write the narrative, brand the deck, 8 to 16 h at EUR 120EUR 960 to 1,920 a cycle

Line one is the build. Line two is the same work repeating, and it never stops.

Marketer is EUR 196 a month, EUR 2,352 a year, and it carries the score, the trend and the report. The ten-roll stability run and the rival project both need Strategist at EUR 496 a month. At EUR 270 a stability question, the second question covers the plan; at EUR 135, the fourth does.

The workflow

Five playbooks, 27 minutes, in the order the conversation with your board actually goes.

1. The number. Does AI name you at all? registers the brand, asks you seven questions once, and runs one scan. What comes back is a score out of 100 with its band beside it and four named metrics under it: Brand Recall, Message Alignment, Value Understanding, Content Structure. Click the mention count and every prompt opens, the buyer type that asked it and the model’s answer beside it. Click Competitors mentioned and read the brands the model recommended while you were absent, with a count on each. PDF for the board pack, CSV for whoever wants to argue with the method.

2. Why one screenshot proves nothing. Somebody will open ChatGPT on a phone in that meeting, type the category question once, see your name and conclude the problem is imaginary. Show how unstable the AI answer really is rolls one question ten times against one model and sorts every brand into four bands by how many rolls named it: Always at 80% of rolls and above, Frequent from 50, Occasional from 20, Rare below that. A rival sitting in Always beside your own name sitting in Occasional is the slide, and the ten answers sit underneath it in full.

3. The rival, measured your way. Track a rival on your own chart makes the competitor a project of its own: same crawl, same model, same prompt discipline. Then a Compare with picker draws its line on your axis over the same window, and one metric switch moves both lines together across the Rankfor Index and its seven pillars. The gap you report upstairs came out of two independent crawls run the same way.

4. The direction, with the working shown. Prove the needle moved, with a chart is the quarterly answer. A dated line you can set to a year, the seven parts of the score, each with the weight it contributed so the total is arithmetic somebody can check, and sentiment theme by theme with a positive share and a signed value per theme. Then the part that closes the meeting: one export listing every cited page, grouped positive, neutral and negative.

5. The thing you send. Hand over a client report without building a deck films an agency handing a report to a client, and the same screen builds the link you circulate before a board meeting. Pick the brand, pick your accent colour, type who it is prepared for. Out comes a twelve-slide deck behind a six-digit PIN that opens in a browser with no account, a PDF of the same page for the inbox, and a sources CSV. The link is fixed to the run it was built from, so what you send today reads the same next week.

What this does not do

Nothing watches the number for you. There is no monitoring product here and no alert when a figure moves. Each project takes one scan per model per calendar month, refused server-side after that, and one chart point is one scan. A ten-point line is ten months of scanning. The cap is what keeps the points comparable.

Two rivals, and the comparison leaves as a screenshot. A workspace holds three projects on Strategist, so you and two competitors, and nothing lifts that ceiling. Competitor projects stay out of the report generator by design and the chart card has no export button, so the two-line chart reaches the board pack as an image you take yourself.

Three models. Gemini, ChatGPT and Grok. Claude and Perplexity sit outside the picker and we publish no numbers for them.

No statistics, and no promised position. The consistency and overlap scores are weighted composites between 0 and 1 shown as percentages, with no confidence levels and no margins of error. The themes behind the sentiment score are a fixed set carried on every prompt, so nothing there is discovered inside your own data. Rankfor.AI measures what the models say and gives you the evidence underneath it. Nobody can promise you a place in an answer.

Start here

Watch Does AI name you at all?. Five minutes and forty-three seconds.

It comes first because it is the only one in the set that hands you a number in a single sitting. Three and four need months of scans before a line means anything, and two needs Strategist. This one needs a website address, seven answers and one scan. And when somebody asks where the number came from, you click through to the questions themselves with the model’s answers beside them, which is the part that survives the challenge.

Then watch Show how unstable the AI answer really is, because the meeting where you ask for the budget is the meeting where somebody produces a phone.

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