Your customers are starting to ask for Generative AI like ChatGPT instead of Google. In just 15 minutes, the AI search audit reveals what AI assistants say when users ask about your service, products, or industry-related queries. Whether your business is mentioned? Or do your competitors come into the recommendations? Makura Creations AI search audit takes the first step in Generative Engine Optimization (GEO) engagement to measure your AI visibility and identify opportunities to improve it, ensuring your business is recommended in AI searches.
Business owners must have one common concern today: is my business recommended by ChatGPT or an AI overview when a customer searches for queries and information related to the industry?
Yes, AI recommendations to your business matter. As traditional Google search results give ten blue link options where users can choose to navigate on their own, an AI answers in two or three and moves on. This means in an AI search, you are in the answer, or you don’t exist in that conversation.
But why don’t businesses check about their AI search visibility? The reason is it is harder to check than it seems to be. When you ask AI platforms like ChatGPT by mentioning your business name, you get cheerful answers as the AI gives detailed information about your business. However, this is not an audit, this is a question with a confident answer attached. The only meaningful test to check whether AI mentions your business in searches is asking questions like your customers ask without mentioning your business name.
That’s what this prompt does. It’s the same audit we run at the beginning of every Generative Engine Optimization (GEO) engagement. We analyze and evaluate your business’s visibility in AI-generated recommendations before making any recommendations or proposing strategies.
Businesses running this AI search audit discover they are invisible in AI search. This is common, as AI recommends businesses based on information they gather from the internet. If your business doesn’t have published clear or optimized content and information, AI fails to learn from your business. Being invisible in the AI searches can be fixed, but believing you are visible when you are not is the risky part.
Replace anything in [BRACKETS] with your own business details. Leave everything else exactly as written. The instructions and constraints at the end of the prompt ensure the AI evaluates your visibility the same way a real customer would, giving you an accurate picture of how your business appears in AI search.
You are a generative search analyst. Your job is to show me, honestly, how a business appears when a potential customer asks an AI assistant for a recommendation and to diagnose why it does or doesn't get named. THE BUSINESS - Name: BUSINESS NAME - Website: URL - What we sell: ONE PLAIN SENTENCE — no marketing language - Where we sell it: CITY / REGION / COUNTRY - Who buys it: CUSTOMER TYPE, e.g. "operations managers at mid-size builders" - Our three biggest competitors: COMPETITOR A, COMPETITOR B, COMPETITOR C METHOD — follow these steps in order. Do not skip ahead or summarise. STEP 1 — Build the question set. Write 12 questions a real buyer would type into an AI assistant when they are ready to spend money but do not yet know BUSINESS NAME exists. Rules: - Never include our brand name in a question. That defeats the entire test. - Mix them: 4 "best / who should I use" questions, 4 problem-first questions (the customer describes a symptom, not a solution), 2 head-to-head comparisons, 2 with a real constraint (budget, deadline, location). - Use the words a customer would use, not the words our industry uses. Show me all 12 and stop. Wait for me to approve them. STEP 2 — Answer each question cold. Answer all 12 exactly as you would for a stranger who asked with no other context. Name specific real businesses where you would name them. Critical: if you do not actually know enough to name anyone for a question, say so plainly. Do NOT invent plausible-sounding businesses to fill out a list. I would much rather see "I don't know of anyone" than a confident guess. STEP 3 — Score it. Build a table with one row per question: | # | The question | Did you name us? | Who you named instead | What earned them the mention | STEP 4 — Diagnose, bluntly. For every question where we were not named, tell me which of these is true: (a) You have no knowledge of this business at all. (b) You know of us, but not in connection with this particular need. (c) We are genuinely the wrong fit and should not be named here. (d) A competitor has published something on this topic that we haven't. Do not soften it. STEP 5 — The fix list. Give me the five things most likely to get us named for these questions. Order by leverage, not by how easy they are. For each one state: - what specifically to publish or earn - where it needs to live - which of the 12 questions it targets - what would count as proof it worked CONSTRAINTS - Do not browse the web for this run unless I explicitly say so. I want your baseline knowledge first, because that is what most users see. - Do not flatter me. If we are invisible, say we are invisible in the first line. - Never assume a fact about our business that I have not given you. Ask instead. - If you are uncertain whether something is true, mark it uncertain.
A good prompt is only half the process. The other half is running it correctly. Even the best prompt can give misleading results if it's used in the wrong context.
Begin the conversation in a new context where AI doesn't know about your business. The main objective is to check what AI knows about you, not what it has learned from earlier in your conversation.
Use a simple and natural tone that reflects how the customer really describes your business. Avoid using technical jargon or marketing slang. Instead of writing “we deliver end-to-end integrated solutions," which AI has nothing to learn about, you can write, “We fix commercial refrigerators in Adelaide, usually same-day."
Before running the audit, clearly review 12 prompt questions by replacing technical jargon with real questions that the general customer uses. You are testing real-world searches, not industry terminology.
AI searches sometimes suggest fictional businesses or recommend companies that never existed. Search and verify every business before you act or go to a conclusion.
Run the audit multiple times, as these systems are probabilistic. Use different AI models like ChatGPT, Claude, or Gemini and run two fresh sessions for every model. This provides a consistent and predictable result that can determine your AI visibility.
Run the same prompt again but with enabling web browsing mode to compare the results. If AI mentions your business only with browsing, your website is discoverable, but its overall authority is limited. In case your business is not visible in search, AI has no idea about your business, which highlights a clear requirement to improve your AI visibility.
Every instruction in this prompt is important for a reason, as it solves problems discovered while evaluating AI visibility of the business. It helps to generate useful, repeatable, and precise results.
The prompts don't ask AI regarding the business recommendation. It clearly focuses on measuring the behavior or recommendation of AI. Measuring behavior is evidence and reliable instead of self-explanation or own reasoning.
Mentioning your brand or business creates bias, as AI are trained to agree on user input. When you mention your brand, service, or business in search, AI gives an answer mentioning your business. For a real search reflecting the customer journey, you must ask genuine questions without mentioning your brand.
AI tends to answer your questions even if there is not relevant information. Allowing AI to admit it doesn't have an answer reduces the fabricated or fictional recommendations, giving an accurate overview of your industry’s AI visibility.
Instead of assigning a generic role, the prompt allows AI to make independent and realistic decisions to give accurate results. This gives evidence-based, careful, and reasonable recommendations
Running the audit with a web search shows the difference in what information the AI already has and what it can discover further on the web. This comparison shows whether your business or site has genuine authority or is found through your website.
The prompt allows you to determine if your business does not fit in the recommendation for certain queries. This helps in preventing forces and fictional recommendations, helping you to focus clearly on the area where you are best suited to serve.
Only replace your information in the [BRACKETS] mentioning your business details. Leave the remaining prompt exactly as it is. Every instruction and constraint in the prompt is to reduce bias, improve accuracy, and produce trustworthy results. Editing or removing the prompts can make the audit far less reliable.
| Variable | What good looks like | What breaks it |
|---|---|---|
[WHAT WE SELL] | The sentence a happy customer would use. “We fix commercial fridges in Adelaide, usually same-day.” | Anything with “solutions”, “end-to-end”, or “bespoke”. The model learns nothing and generates twelve useless questions. |
[WHO BUYS IT] | A specific role with a specific problem. “Venue managers who’ve just had a fridge fail on a Friday.” | “Businesses” or “everyone”. Vague buyers produce vague questions, and vague questions can’t be won. |
[COMPETITORS] | Who you actually lose deals to. Check their names come back in step 2 — if the model doesn’t know them either, your whole category is invisible. | The market leader you’ve never competed with. You’ll measure a race you’re not in. |
[WHERE] | How a customer describes it. “Adelaide” or “northern suburbs” — the words they’d type. | Service-area jargon like “SA metro region 4”. Nobody types that. |
| The 12-question rule | Keep 12. Enough to see a pattern, few enough to read properly in one sitting. | Asking for 50. You get generic filler questions and you won’t read them, so the audit gets worse as it gets bigger. |
| The “don’t invent names” line | Leave it exactly as written. It’s the single most important sentence in the prompt. | Removing it. You’ll get a tidy competitor list, half of it fictional, and you’ll benchmark against ghosts. |
| The “don’t flatter me” line | Leave it. Assistants default to encouraging, and encouraging is the enemy of an audit. | Removing it. Invisibility gets reported as “some room to grow”. |
The example below illustrates the sample AI search audit for a fictional commercial refrigeration repair business in Adelaide. It represents common patterns observed to illustrate insight and the format of the audit, not the result of clients' data.
| # | Named us? | Named instead | What earned them the mention |
|---|---|---|---|
| 4 | No | Two national chains + “your local emergency refrigeration service” | The chains publish emergency-callout pages that name the symptom and promise a response time. The generic phrase is a hedge — it means the model has no specific local knowledge. |
(a) — no knowledge of this business at all. Across 12 questions the business was named 0 times without browsing, and 2 times with browsing on. The category's local layer is essentially empty: for 7 of 12 questions the model reached for national chains or a generic placeholder, because nothing in Adelaide has published anything connecting a symptom to a name.
The result can be good news, as finding zero mentions might feel discouraging, but it is the best position to start. In most cases, your competitors are not recommended just because they are the best; it may be because they have great online visibility. When a model falls back to "your local emergency refrigeration service," it's telling you nobody owns that answer yet. In most situations, you don't require a high expense. You need specific content that fills the gaps your competitors have overlooked.
We have watched this happen within 10 minutes of the audit
Asking or mentioning your business creates bias and ruins the audit. It increases the chance of generating more information about your business. It is important to test what AI recommends without mentioning your business until the audit ends.
The result of the audit varies between sessions and models. Running just a single time is an anecdote. Instead, run the audit multiple times across different models to identify consistent patterns.
AI can give reasons for its recommendations, but those reasons can be hypothetical without proof. Instead of believing, always verify the result by reviewing competitors' websites and online presence.
Your business may not get mentioned by AI in its recommendation when you run the audit. This is not a problem, it indicates visibility or gaps in content, which can be fixed.
Almost everyone scores zero the first time. It doesn't mean your business is failing — it means nothing on the open internet explains what you do in the words your customers use. That's a content problem, and content problems are among the most fixable ones you have.
You ran the audit and got the result. But doing nothing after the result can be a costly mistake. To gain real value, you must identify opportunities from results and improve your content, authority, and online presence while also repeating the audit frequently.
At Makura Creations, we assist businesses across Nepal, Australia, and USA by performing AI search audits and implementing Generative Engine Optimization (GEO) strategies to help AI searches recommend your business. If you got a weak result after the audit, let's fix it. If the result is satisfactory, keep running the audit regularly, as AI search is evolving constantly and your competitors are too.
