In our previous article, we explored a simple but important idea:
AI visibility starts with customer needs, not prompts.
Before a business thinks about which AI searches to test, which keywords to monitor or which content to create, it should first understand the situations that cause customers to look for help.
The prompt is not the starting point.
The prompt is simply the visible expression of an underlying need.
This raises an important question:
How does this approach apply to AI Visibility Testing itself?
After all, AIVT exists in a new and rapidly changing area. Businesses are not necessarily waking up thinking:
“I need an AI visibility test.”
That is the description of the solution.
The customer’s actual situation is usually something different.
They have a concern, a question or a problem they are trying to solve.
Understanding those situations is the first step.
The difference between a service and a customer need
Businesses naturally describe themselves by what they provide.
An AI visibility testing service might describe itself as offering:
- AI search testing;
- prompt monitoring;
- competitor analysis;
- visibility measurement;
- AI citation tracking.
Those are the tools and methods.
But a potential customer may be thinking:
- “Why have my website enquiries changed?”
- “Are customers still finding businesses through Google?”
- “Will AI search affect my business?”
- “Why does AI recommend my competitors?”
- “How do I know whether my business is visible in AI answers?”
The service exists because those situations exist.
The customer need comes first.
Customer situation 1: “My website traffic or enquiries have dropped”
One possible situation is a business owner noticing that something has changed.
Perhaps:
- website traffic has declined;
- organic search clicks have reduced;
- enquiries are slowing;
- previous marketing activity appears less effective.
The immediate question may be:
“What has happened?”
There could be many possible explanations.
It might relate to:
- changes in search behaviour;
- increased competition;
- website issues;
- changing customer preferences;
- AI-generated answers providing information without requiring a website visit.
The underlying need is not necessarily “AI visibility testing”.
The need is:
Understanding whether changes in how people discover information are affecting the business.
Possible questions they may ask AI include:
- “Why has my website traffic dropped?”
- “Are AI search results reducing website clicks?”
- “How is AI changing customer discovery?”
AI visibility testing can help investigate one part of that wider question.
Customer situation 2: “I keep hearing about AI search but do not know what it means for my business”
Many businesses are aware that AI search is developing but are unsure what action, if any, they should take.
They may have heard terms such as:
- AI Overviews;
- AI Mode;
- answer engines;
- AEO;
- GEO;
- LLM optimisation.
But they may not know:
- whether it matters for their industry;
- whether customers are already using AI tools;
- whether they need to change their marketing approach.
The underlying need is:
Reducing uncertainty about a changing digital landscape.
Possible questions include:
- “How will AI search affect small businesses?”
- “Do businesses need to optimise for AI search?”
- “How can I measure my AI visibility?”
Before deciding what action to take, the business needs understanding.
Customer situation 3: “I want to know what AI says about my business”
A business owner may simply want a baseline.
They may ask:
- Does ChatGPT know my business?
- What would AI say about my company?
- Would AI recommend my services?
- Are the descriptions accurate?
This is not necessarily about improving visibility.
It is about understanding current representation.
The underlying need is:
Knowing how the business is currently understood by AI systems.
This is why testing should not only look for mentions.
It should also consider:
- accuracy;
- context;
- positioning;
- sentiment;
- missing information.
A business could be mentioned frequently but represented incorrectly.
Customer situation 4: “My competitors appear in AI answers but I do not”
This is likely to become one of the most important AI visibility questions.
A business owner may ask an AI system about their industry and see competitors appearing.
They may wonder:
- Why are they being recommended?
- What information does AI associate with them?
- What are they communicating that we are not?
The underlying need is:
Understanding the visibility gap.
The answer is not necessarily “create more content”.
The business needs to understand:
- what customer needs competitors appear to address;
- what evidence AI systems have found;
- where gaps may exist.
Customer situation 5: “I do not know what questions my customers are asking AI”
This is a more advanced stage.
A business may understand that customers are no longer only searching using short keywords.
They may be asking detailed questions such as:
“I run a small manufacturing company using Xero. Which accountants understand stock control and management reporting?”
or:
“I have severe dental anxiety after a bad experience. Which dentists are experienced in helping nervous patients?”
The underlying need is:
Understanding customer questions and decision-making in an AI search environment.
This connects directly to the Need-First Framework.
The business should not start by guessing prompts.
It should understand customer situations and discover the questions those situations create.
Customer situation 6: “We create content but do not know whether it helps”
Many businesses invest time in:
- blog posts;
- guides;
- FAQs;
- resources.
But they may not know whether that content is helping them become more visible.
They may ask:
- Is AI understanding our expertise?
- Are our competitors being recognised instead?
- Are there important questions we have not answered?
The underlying need is:
Understanding whether their knowledge is being communicated effectively.
AI visibility testing provides a way to investigate this.
Customer situation 7: “We are an agency and need to understand AI visibility for clients”
The customer situation changes again when the audience is an agency.
Their needs may include:
- understanding the emerging market;
- developing a service offering;
- reporting results to clients;
- comparing competitors;
- creating a repeatable process.
Their questions may include:
- “How should agencies measure AI visibility?”
- “What should an AI visibility report include?”
- “How can I demonstrate value to clients?”
The underlying need is:
Developing capability in a changing marketing environment.
The same framework applies across every industry
The important point is that customer situations will differ.
A dentist, accountant, manufacturer, retailer and software company will not have the same needs.
That is why there cannot be one universal list of prompts that applies to every business.
The process is:
- Understand the customer situation.
- Identify the underlying need.
- Discover the questions that need answering.
- Translate those questions into AI prompts.
- Test whether AI systems understand and represent the business accurately.
The categories come from the customer’s world, not from the technology.
AI visibility testing is the final step, not the first step
AI visibility testing is valuable because it provides evidence.
It can help answer questions such as:
- Are we visible?
- How are we represented?
- Who appears instead?
- Where are opportunities or gaps?
But the testing only becomes meaningful when the business understands what it is testing for.
A random list of prompts may produce interesting data.
A carefully developed set of prompts based on genuine customer needs produces insight.
The difference is that one measures activity.
The other measures something connected to business reality.
The future of AI visibility starts with understanding people
AI systems are becoming increasingly involved in helping people make decisions.
They attempt to understand:
- what someone needs;
- what information is relevant;
- which solutions may help.
Businesses should approach AI visibility in the same way.
The most important question is not:
“How do we get AI to mention us?”
It is:
“What problems are our customers trying to solve, and have we clearly demonstrated how we can help?”
Because businesses do not create value by being visible.
They create value by solving problems.
Visibility simply helps the right people discover that solution.