AEO measurement can look impressive while the strategy behind it is quietly going nowhere.

Your brand might appear more often in ChatGPT. Your AI visibility score might rise. You may even begin earning citations for questions where competitors previously dominated.

But there is a fundamental question that needs to come first:

Are these prompts your buyers actually ask?

A strong AEO prompt strategy focuses on the questions your ideal buyers use when they are trying to understand a problem, evaluate solutions, compare options, or make a purchase decision. Search volume can help identify broader demand, but it cannot determine whether a prompt matters commercially. The most valuable prompts reflect your ICP’s real problems, buyer role, buying stage, geography, decision criteria, and level of intent. Optimizing for irrelevant prompts can increase AI visibility without improving qualified discovery, leads, or pipeline. Before measuring how often AI mentions your brand, make sure you are measuring the questions that matter.

That principle sits at the center of Xeo’s  ⁠AEO Strategy Starter Kit for AI Startups: Would the right buyer ask this before buying?

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A Higher AI Visibility Score Does Not Automatically Mean a Better AEO Strategy

AI visibility scores are useful because they establish a baseline.

You can select a group of prompts, test them across AI platforms, record whether your company appears, and repeat the process over time. That gives you a way to monitor movement.

The quality of that measurement, however, depends entirely on the prompt set underneath it.

Imagine an AI cybersecurity company tracks 100 broad questions about artificial intelligence and cybersecurity. After several months of content optimization, the company begins appearing for 40 instead of 15.

On paper, visibility has improved dramatically.

Now imagine that its actual buyers are enterprise security leaders evaluating AI vendor risk, and almost none of those 100 questions relate to vendor assessment, governance requirements, procurement risk, or the problems that trigger a buying conversation.

The visibility increase is real. Its commercial significance may be minimal.

This is one of the easiest ways to build a misleading AEO dashboard: choose prompts because they are easy to track rather than because they represent real buyer demand.

Prompt selection therefore belongs at the beginning of an AEO strategy, before optimization and before reporting.

Search Volume Is Useful. It Is Not a Prompt Strategy.

SEO trained marketers to pay close attention to search volume, and for good reason. It can help identify topics people search for and estimate relative demand.

AEO introduces a different research environment.

People often interact with AI assistants through longer, more contextual questions. They can describe their company, problem, constraints, location, use case, or decision criteria within the same conversation.

A buyer might search Google for:

AI compliance software

But ask an AI assistant:

What should a mid-sized financial services company look for when evaluating AI compliance software?

Or:

Which AI governance platforms are suitable for a Canadian financial institution that needs stronger vendor-risk controls?

The latter prompts may never produce an impressive traditional search-volume number. They can still be extremely valuable because they contain considerably more information about the buyer and the decision being made.

Search-volume data can inform your topic strategy. It should not become the sole filter for deciding which prompts deserve AEO investment.

Commercial relevance needs to sit beside it.

Start With the ICP Problem, Not the Keyword

The best prompt research starts with the buyer.

Ask what causes your ideal customer to begin researching in the first place.

Perhaps a security leader is concerned about employees adopting AI tools without governance. A marketing executive may be seeing competitors appear in ChatGPT while their own company is absent. An operations leader may need to automate a process without increasing headcount.

Those problems produce much richer prompt territory than simply expanding a list of category keywords.

Xeo’s AEO Starter Kit recommends collecting prompt language from places where buyers are already telling you what matters:

• demo requests;
• sales calls;
• support questions;
• lost-deal notes;
• customer conversations;
• objections raised during evaluation.

Then turn that language into natural questions.

This is particularly useful because internal marketing terminology and buyer terminology are often different. Your team may describe a capability using the product category you want to own. The buyer may describe the same need through the operational problem keeping them up at night.

AEO needs to understand both.

A Useful Prompt Contains More Than a Topic

A practical way to evaluate a potential AEO prompt is to break it into four components:

Real buyer + real problem + decision being made + relevant constraints

Consider the difference.

Weak prompt:
“What is AI security?”

There may be a reason to target it. It is broad, informational, and potentially useful for establishing topical authority. But we know very little about the person asking or what they intend to do next.

Stronger prompt:
“How should a mid-market security team evaluate AI vendors before procurement?”

Now we have a buyer context, a problem, and a decision.

Add a meaningful constraint:

“How should a mid-market security team evaluate AI vendors that handle sensitive customer data before procurement?”

The question becomes even more specific.

Specificity should still be earned. Adding random qualifiers simply to create hundreds of prompt variations does not make the strategy more sophisticated.

A constraint belongs in the prompt when it materially changes the answer or the buying decision.

Buyer Intent Changes the Value of a Prompt

Two prompts about exactly the same product category can have very different commercial value.

Consider:

“What is an AI governance platform?”

versus:

“What should I compare when choosing an AI governance platform for my company?”

The first signals learning.

The second signals evaluation.

Neither should automatically be considered better. They serve different functions in the buyer journey.

That is where TOFU, MOFU, and BOFU remain useful for AEO.

TOFU: Understanding the problem

Top-of-funnel prompts often help buyers define a problem, understand terminology, or learn why something matters.

Examples might include:

• What is AI vendor risk?
• Why do companies need AI governance?
• What are the risks of employees using unauthorized AI tools?

These questions can help establish topical authority and introduce your brand during early research.

MOFU: Exploring and comparing approaches

Middle-of-funnel prompts indicate that the buyer understands the problem and is considering ways to address it.

For example:

• How do companies assess third-party AI vendors?
• What should an AI vendor risk assessment include?
• AI governance platform vs manual governance process: which is better for a mid-sized company?

These prompts bring the buyer closer to a solution category.

BOFU: Reducing purchase risk

Bottom-of-funnel questions often contain stronger buying signals.

Examples include:

• What questions should I ask an AI governance vendor before signing?
• Which AI governance solutions support financial-services compliance requirements?
• What should I compare when shortlisting AI risk management vendors?

The buyer is now evaluating options, reducing uncertainty, or preparing to make a decision.

A healthy prompt strategy understands these differences instead of treating every appearance in an AI answer as equally valuable.

Product-Category Prompts and Brand Prompts Measure Different Things

Another important distinction is whether the buyer already knows your company.

A brand prompt might ask:

“Is Company X a good AI governance platform?”

A product-category prompt might ask:

“Which AI governance platforms are suitable for mid-market companies?”

Both are worth monitoring, but they tell you very different things.

Brand prompts help reveal how AI systems understand and represent a company that has already entered the buyer’s consideration set. They can expose inaccurate positioning, outdated information, missing proof, or inconsistent descriptions.

Product-category prompts test something more difficult: Can your company enter the conversation before the buyer knows its name?

For companies investing in AEO as a discovery channel, that distinction matters enormously.

If your brand performs well whenever someone explicitly asks about it but disappears from unbranded category and problem-oriented questions, AI may understand the company without seeing it as a relevant answer to broader buyer needs.

Your prompt set should test both situations.

Buyer Role Should Change the Question

A company does not buy software. People within the company evaluate it from different perspectives.

A CISO, procurement leader, CFO, technical user, and CEO may all participate in the same buying decision while asking very different questions.

For an AI platform, a technical buyer might ask about integrations, deployment, model architecture, security, or data handling.

A procurement leader may focus on vendor risk, contractual terms, compliance, and implementation requirements.

An executive may care about business outcomes, scalability, cost, and organizational risk.

If your prompt strategy reflects only the terminology used by marketing, you can miss large parts of the buying committee.

This is especially important in complex B2B purchases. Instead of asking only, “What prompts describe our product?”, ask:

What would each person involved in this decision need to know before they were comfortable moving forward?

Those questions often uncover the prompts that deserve content.

Geography Matters When It Changes the Answer

Geographic qualifiers should be treated similarly to other constraints: use them when they materially affect the decision.

A generic question such as:

“What should companies consider when adopting AI?”

may have one set of answers.

A Canadian buyer asking about privacy requirements, a European company operating under the EU AI Act, and a company evaluating region-specific data hosting may require very different information.

In those situations, geography is commercially meaningful.

Local availability can matter too. A provider may serve certain markets, support particular languages, operate under specific regulatory environments, or integrate with regional systems.

The mistake is adding cities and countries mechanically to every prompt simply to manufacture more variations.

Ask whether location changes what the buyer needs, which vendors are appropriate, or what evidence AI should use. If it does, include it.

Commercial Relevance Should Determine Priority

Eventually, every AEO team faces the same constraint: you cannot optimize for everything at once.

Prioritization matters.

A useful prompt should be evaluated against several questions:

Would our ICP realistically ask it?
If the answer is no, high visibility may have little strategic value.

What buying stage does it represent?
Understand whether the prompt supports discovery, evaluation, or purchase.

Does it relate to a problem we actually solve?
Adjacent visibility can look attractive while bringing the wrong audience.

Could appearing for this prompt influence a commercial decision?
Consider whether the question could contribute to qualified discovery, evaluation, or conversion.

Do we have the expertise and evidence to answer it credibly?
AEO should reinforce legitimate authority rather than manufacture claims around topics the company cannot substantiate.

Are competitors already appearing?
Competitor visibility can reveal where AI already sees a strong connection between buyer intent and particular brands or sources.

The goal is a smaller, more deliberate set of prompts that reflects actual buying behavior.

Separate Site-Wide Discovery Prompts From Page-Specific Prompts

One prompt list should not govern an entire website.

Some questions test whether AI understands the company at a broad level:

• What does this company do?
• Who is it for?
• What category does it belong to?
• What problems does it solve?
• How does it differ from competitors?

These are useful site-wide discovery prompts.

Other questions belong to individual pages.

A product page may target evaluation-oriented prompts. A case study may support questions about results or use cases. A technical article might answer an informational question. An industry page may need prompts shaped by sector-specific problems and requirements.

This distinction is built into Xeo’s AEO Strategy Starter Kit for AI Startups AEO Strategy Starter Kit for AI Startups. The framework recommends defining what each page is meant to do before deciding which prompts it should answer.

It also prevents another common AEO mistake: forcing TOFU, MOFU, and BOFU prompts onto every page.

Some pages primarily exist for one stage of the journey. Let them do that job well.

Build a Prompt Map Before You Build More Content

Once you have collected potential questions, organize them into a working prompt map.

At minimum, record:

Prompt	Buyer role	Buying stage	Geography/constraint	Why it matters	Priority
What is AI vendor risk?	Security leader	TOFU	None	Establishes problem awareness	Medium
How should we assess AI vendors before procurement?	Security / Procurement	MOFU	Enterprise	Directly related to evaluation	High
Which AI governance vendors support Canadian financial institutions?	Compliance / Security	BOFU	Canada + financial services	High commercial relevance	High

The purpose of the map is not to create the longest possible spreadsheet.

It is to force strategic choices.

When you can see buyer role, stage, constraints, and commercial relevance beside each question, it becomes much easier to distinguish a useful AEO opportunity from a vanity prompt.

Your AEO Score Is Only as Meaningful as the Prompts Behind It

AEO teams will inevitably develop better dashboards.

We will measure citations, mentions, recommendations, share of AI visibility, AI referral traffic, engagement, conversions, pipeline, and other signals with increasing sophistication.

None of those improvements fix a weak prompt strategy.

If the underlying questions do not reflect your ICP, the problems they are trying to solve, the people involved in the decision, and the commercial situations where your company genuinely belongs, an improving visibility score can create false confidence.

Start with the buyer.

Listen to how they describe the problem. Understand what changes as they move from learning to evaluating to choosing. Identify the constraints that genuinely affect their decision. Separate questions about your brand from questions where the buyer has not discovered you yet.

Then decide what deserves to be measured and optimized.

Xeo’s free  ⁠AEO Strategy Starter Kit for AI Startups includes a Buyer Prompt Map and prioritization worksheet designed for exactly this process. Use it to identify the questions that matter before investing more time in improving the answers.

About Xeo Marketing

Xeo Marketing is a Toronto-based digital strategy and innovation agency specializing in AI Engine Optimization (AEO), helping B2B service businesses adapt to AI-powered search and discovery. The AI Visibility Score is the first module in AOME (AI Orchestrated Marketing Engine), launching throughout 2025.

Learn more at xeo.marketing