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How to build the business case for AI search optimisation (AEO and GEO)

A business-case model for AI visibility work that a finance team can audit: what you can and cannot claim, an ROI and payback worksheet with three scenarios, leading and lagging indicators, costs by company size, a competitor gap memo, a six-slide board outline and a 90-day pilot.

  • ROI and payback worksheet with a break-even line and three scenarios
  • "How did you hear about us" field design and CRM tagging rules
  • Budget-sizing worksheet by company size, build vs buy vs agency
  • Competitor gap memo fed by a baseline of real answers
  • Six-slide board deck outline and a 90-day pilot with go/no-go criteria

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The short answer

Build it on your own data, not forecasts. Baseline how often AI assistants name you and your competitors for buying questions, add an AI option to your "how did you hear about us" field, then calculate the break-even: how much AI-sourced pipeline must rise to repay the programme. Ask for a 90-day pilot with go/no-go criteria, not a permanent budget.

For CMOs, VPs of marketing and heads of SEO or digital who need budget and board backing for AEO and GEO

What you will learn

  1. Chapter 1

    Frame the problem for leadership

    • Leadership needs a measurable question, not a trend: are we in the answers our buyers read, and what do they say about us?
    • Cite only primary figures with their date and definition, and name the publisher's interest when it has one.
    • Your own data, collected in a few weeks, is more persuasive than any market forecast.
    • A problem statement with named competitors and measured gaps is the foundation of the whole case.

  2. Chapter 2

    A business-case model you fill in with your own numbers

    • The bridge from an AI answer to revenue is what buyers tell you, so self-reported source data is the foundation of the model.
    • Lead with the break-even uplift: how much AI-sourced demand must grow to repay the programme.
    • Change only the uncertain assumptions between scenarios, and tie each one to a signal you will observe.
    • An honest model may show payback beyond one year; saying so is what makes the rest credible.
    • Do not price a mention with an equivalent ad value; treat it as a leading indicator.

  3. Chapter 3

    Leading and lagging indicators

    • Use a chain of indicators: answers move first, visits confirm, self-reports and revenue settle the case.
    • Define each answer-layer metric once and report trends across several runs, because answers vary.
    • A required "how did you hear about us" field with an AI option is the bridge from answers to revenue.
    • Count pipeline as AI-influenced only where a buyer said so, and keep it separate from AI-sourced.

  4. Chapter 4

    Costs, resourcing and how much to ask for

    • Show five cost lines, including internal time, and split one-off from running costs.
    • Most teams buy measurement, build content and borrow specialist help.
    • Size the budget from questions, gaps and sources, not from a quoted share of marketing spend.
    • Reallocation from low-yield work is easier to approve than new money, and a pilot is easier than a programme.

  5. Chapter 5

    The risks of doing nothing, made checkable

    • A risk becomes useful when anyone can check it by asking the same questions.
    • A repeatable baseline with saved answers is the evidence behind every risk statement.
    • Wrong descriptions are a separate risk from absence, and they bring sales, legal and support onto your side.
    • A one-page competitor gap memo with quoted answers often moves leadership faster than an ROI model.

  6. Chapter 6

    Getting it approved

    • Meet the CFO, CEO, sales, legal and IT before the decision meeting, each with what they need to hear.
    • Answer objections with the method: fixed questions, repeated runs, self-reported attribution and break-even.
    • Six slides cover it: where buyers research, what answers say, what it is worth, plan, risks, decision.
    • Agree go/no-go thresholds in numbers before the pilot starts and do not move them.

7 worksheets inside

The chapters explain the method. The worksheets are what you fill in to run it: print them, or copy the tables into a document of your own.

  • W1ROI and payback worksheet
  • W2Indicator scorecard and attribution field kit
  • W3Budget-sizing worksheet
  • W4Competitor gap memo
  • W5Six-slide board deck outline
  • W690-day pilot plan and go/no-go criteria
  • W7Baseline before you ask
Get the playbook

Questions

How do you prove the ROI of AI search optimisation?
Build it on your own data: a baseline of how often assistants name you, a "how did you hear about us" field with an AI option, and your CRM's pipeline figures. Calculate the break-even uplift, the rise in AI-sourced opportunities needed to repay the cost, and test it with a 90-day pilot rather than forecasting revenue.
What is a good metric for AEO or GEO success?
Use a chain. Answer-layer metrics such as visibility rate, share of voice and description accuracy move first; assistant referral visits confirm; self-reported AI source and the pipeline it carries settle the case. No single metric is enough on its own.
Can you track traffic from ChatGPT and other AI assistants?
Partly. Some assistants pass a referrer, so visits appear under hostnames such as chatgpt.com or perplexity.ai and can be grouped into a segment. Google says AI Overviews and AI Mode traffic is included in Search Console's Web search type rather than shown separately. Many buyers read an answer without clicking, so referrals undercount influence.
How much budget should we put into AI visibility?
There is no reliable public benchmark for the share of marketing budget, so size it from the work: the number of priority questions, the gaps your baseline found, and the content, PR, tooling and engineering needed to close them. Start with a pilot, ideally funded by reallocating from low-yield work.
How do I attribute pipeline to AI search?
Count an opportunity as AI-sourced only when the buyer named an assistant as their source on a form or in a call. Record wider mentions as AI-influenced and report them separately. Do not infer influence from visibility alone.
Is AEO just SEO under a new name?
Part of the work overlaps: crawlable, well-structured pages that answer real questions help both. The difference is that an answer names a few brands or none and leans on third-party sources, so PR, review sites and how engines describe you matter more than position on a results page.
How long before AI visibility work shows results?
Answer-layer changes can appear within weeks of fixes shipping, though answers vary between runs, so judge trends. Self-reported attribution and pipeline take one to two quarters to accumulate. That is why a 90-day pilot uses answer-layer and attribution criteria, not revenue alone.
What should a board deck on AI search strategy include?
Six slides: where your buyers research, what the answers say about you today, what it is worth using a break-even model, the plan and cost, the risks of acting and not acting, and the decision with go/no-go criteria.
Is The AI Visibility Business Case free?
Yes. Give a first name and a work email and the download starts at once. We also email you the link, and one person from the Noma team follows up a day later; reply and say so if you would rather not hear from us.
Why do you ask for a work email?
The playbooks are written for teams at companies, and a work address tells us which company is reading, so a follow-up can be about your brand rather than generic. Personal and temporary inboxes are not accepted.
What format is it?
A PDF of 38 A4 pages, laid out to print, with worksheets you can fill in by hand or copy into a document of your own.

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Updated 20 October 2026 · Written by the Noma team · All resources