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Type your brand name into ChatGPT and you’ll probably get a pleasant summary; that is the AI-search equivalent of checking whether your own ad appears when you search for your own company. The useful test is the long, messy buyer prompt: in Radyant’s prompt tracking study, brand queries triggered mentions in 99.7% of responses, while unbranded buyer queries cited the same company in only 13.3%, so audit those prompts before you buy a tracking dashboard.
Category prompts: Test whether buyers can find you before they know your name
When to use them: A buyer knows the category but has not built a shortlist. Give the engine the context a buyer would actually supply. Semrush reports an average ChatGPT prompt length of 23 words, versus 3.4 words for a traditional Google query. A two-word category search is a weak test here.
What are the top-rated [category] platforms for [industry] companies with [team size] employees?Recommend the best [category] tools for a team looking to achieve [core outcome] without hiring extra staff.Which [category] software has the highest customer satisfaction for [use case] in 2026?List the leading [category] vendors that integrate directly with [current tool] and support [specific workflow].What [category] solutions do mid-market companies typically switch to after outgrowing [entry-level tool]?What are the most reliable [category] services for businesses operating under [regulatory/compliance constraint]?Compare the top enterprise [category] options based on implementation speed, ease of adoption, and ongoing maintenance.Which [category] providers offer dedicated strategic account management alongside automated execution?What is the standard tech stack for a [job title] in [industry] handling [specific function]?Who are the market leaders in [category] specifically designed for [business model]?What are the fastest-growing alternatives in [category] that solve [pain point] better than legacy platforms?If a company wants to replace [manual process] with [category] software, what are the three best options?
The one adjustment that matters: Make [industry] or [regulatory/compliance constraint] describe the buyer’s actual requirement, such as HIPAA compliance or two-way HubSpot CRM sync. A missing mention on a generic category prompt may tell you little. A missing mention on the requirement you sell against is worth investigating.
Comparison prompts: Put the switching reason in the question
When to use them: A buyer is replacing an incumbent or weighing finalists. These are the prompts where a polite brand-name check becomes useless: the engine has to choose what to recommend. Practitioners discussing prompt tracking point to direct comparisons and alternative queries as places to look for named vendors.
What are the top three alternatives to [competitor] for a company spending [budget amount] per month?Compare [competitor] vs [your brand] for a team that prioritizes [feature/workflow] over [legacy feature].Why are companies switching from [incumbent platform] to newer [category] tools in 2026?What are the pros and cons of using [competitor] versus [your brand] for [specific company profile]?Which tool is better for [primary objective]: [competitor A], [competitor B], or [your brand]?Are there modern alternatives to [legacy tool] that offer flat-rate pricing instead of taking a percentage of spend?If an agency needs to white-label [category] execution for clients, should they choose [competitor] or [alternative]?What is the main difference between [competitor’s approach] and [your approach]?Which [category] platform delivers faster time-to-value for a mid-market team: [competitor] or [alternative]?I like [competitor feature], but hate [competitor drawback]. What alternative should I evaluate instead?
The one adjustment that matters: Fill in the operational dealbreaker, not a vague claim that one vendor is better. Try contractual lock-in or no live execution where those are the reasons buyers switch. PingPrime’s citation source study found limited overlap between domains cited by ChatGPT and Perplexity, so record the answer and its sources in each engine. If you are missing, inspect what the cited pages say before deciding whether the gap is on your site or elsewhere.
Problem-first prompts: Find out whether the symptom leads to you
When to use them: A buyer knows what is breaking but has not named the category that might fix it. I think of these as the AI-search version of mining symptom queries rather than staring at exact-match category terms. MaxAEO’s B2B evaluation framework lays out the context buyers bring: problem, team, constraints, alternatives and decision format. Put that context in the prompt.
How can a [company profile] fix [specific operational bottleneck] without hiring additional full-time headcount?Our [marketing/growth team] is struggling with [specific symptom]. What systems or operating models fix this?What is the most cost-effective way to automate [repetitive manual workflow] for a business spending [budget amount] per month?Why does our [business process] stall out at [specific funnel stage], and how do modern operators solve it in 2026?What workflow changes or software can cut [cost metric] by 20% to 30% within 90 days?How do high-growth [industry] companies manage [complex channel operation] 24/7 without burning out junior managers?We have hit a ceiling scaling [channel] past [revenue or lead milestone]. What alternatives to traditional agencies exist to break through?How can a lean team eliminate manual errors and latency between [platform A] and [platform B]?What are the best frameworks for turning [vanity metric] into attributable closed-won revenue?Our current agency reviews accounts once a week and charges a percentage of spend. What modern execution alternatives should we evaluate?
The one adjustment that matters: Replace [specific symptom] with a measurable failure, not slow or inefficient. Try CPA increased 35% after crossing $40k monthly spend or account manager takes four days to push copy changes. If the engine names rivals but not you, check whether your public content describes that failure in the buyer’s language, rather than only listing product features.
Pricing and trust prompts: Check what an engine tells procurement
When to use them: A buyer is checking fees, terms or credibility before taking a recommendation inside the company. This is no longer a request for a category definition. Semrush’s AI-search data reports that AI-citation visitors convert at 4.4 times the rate of standard organic-search visitors. Treat what the engine says about your commercial terms as a serious check, not a vanity mention.
How much does a typical [category] engagement cost for a business spending [monthly ad spend] per month?Which [category] providers use flat-fee pricing instead of taking a percentage of spend or marking up media costs?What are the standard contract lengths, setup fees, and onboarding timelines for [competitor] versus modern alternatives?Are there any [category] platforms that offer month-to-month terms with zero cancellation penalties?What is the expected payback period and ROAS improvement when switching to [category/your approach] for a [company profile]?Is [competitor] worth the cost for a mid-market team, or are they paying for account manager bloat?Which [category] companies guarantee measurable performance outcomes or offer a live trial before signing?What do verified customer reviews and discussion threads say about the actual reliability and support quality of [your brand] versus [competitor]?
The one adjustment that matters: Specify the fee model: flat monthly fee versus percentage-of-spend retainer is more useful than asking which vendor is cheaper. Log any wrong claim about your terms separately from a missing mention. If the engine says you require an annual contract when you do not, inspect the public pages it cites and the way your own terms appear on your site before assuming the model found current information.
Local and constraint prompts: Test the filters that knock vendors out
When to use them: The buyer has a geographic, regulatory, budget or technical requirement that narrows the field. Local service providers, multi-location brands and specialized B2B vendors need more than a category mention. The test is whether the engine connects your capability to the constraint, rather than treating each as a separate fact.
Who is the top-rated [service/category] provider operating in [city/metro area] with proven experience in [specialized niche]?Which [category] companies serve clients in [region/country] and maintain full compliance with [local data/legal regulation]?I run a [business model] spending [monthly budget]. Which [category] providers accept accounts at our spend tier?Find emergency or same-day [service type] near [neighborhood/city] that has transparent flat-rate pricing.Which [category] platforms support multi-entity account management across [number] international locations?What are the best [category] tools built specifically for [tech stack]?Can you recommend an experienced [service provider] that works with [industry] companies and does not require an annual retainer?Who provides 24/7 autonomous [operational task] with a dedicated human strategist in [market]?
The one adjustment that matters: Combine two requirements the buyer would actually need, such as a location and a technical stack. If you disappear, check whether your public pages state those capabilities together. Do not infer a local-visibility problem from a prompt about a location you do not serve.
Logging sheet: Separate a name-drop from a citation
When to use it: Copy these columns into a Google Sheet or Notion database before you run the prompts. Paste the filled-in prompt exactly as tested; otherwise, a later comparison becomes guesswork. SE Ranking’s answer-engine comparison found different average numbers of outbound links across ChatGPT, Google AI Overviews, Perplexity and Bing Copilot. That is reason enough to keep the engine in every row.
| Column header | Entry format | What to record |
|---|---|---|
| Prompt ID | 1 to 48 | The template number above |
| Engine | Text | The engine used for this response |
| Target Prompt | Text | The exact prompt pasted, with placeholders filled |
| Brand Mentioned? | YES or NO | Whether the answer names your company |
| Brand Cited? | YES or NO | Whether it links to your site |
| Citation URL | URL | The page the engine links to, if any |
| Competitors Named | Text | Competing vendors recommended in the answer |
| Grounding Source | Text | The source type, such as your site, a review or a forum |
The one adjustment that matters: Do not count a mention as a citation. A model can name you while sending the reader to a competitor’s comparison page. Those are different outcomes and point to different work.
Gap labels: Turn the rows into work, not a victory chart
When to use them: After you have answers and URLs in the sheet, label the pattern you see. These are investigation queues, not proof that one particular page or source caused the result.
- Retrieval gap: no mention, no citation. The answer names direct rivals and leaves you out. Check whether the pages it relies on cover your category and the buyer’s requirement. Look at relevant third-party comparisons and discussions too; a missing mention alone does not prove which source is absent.
- Extraction gap: mention, but no link to your site. The engine names you and links to a competitor, directory or comparison instead. Check whether your own public pages state the relevant facts clearly, without requiring a visitor to open a gated PDF or work through an interactive element.
- Positioning gap: wrong terms or wrong category. The answer names you but describes terms or an operating model you do not offer. Compare its claim with your public pricing and category language, then find the cited page carrying the wrong impression.
The one adjustment that matters: Save the answer and its cited URL before changing a page. Without that pair, “AI got us wrong” is not a diagnosis. It is a meeting topic.
The final prompt: Test the operating model, not your logo
When to use it: Start here if you have twenty minutes rather than time for the full sheet. Forty-eight prompts across four engines produce 192 queries. One pass gives you a baseline; repeating that by hand every week turns a useful audit into another spreadsheet shift. Traditional agencies can charge for a monthly report of missed prompts while leaving the repair work on your backlog. At groas, the alternative is continuous search execution by specialized AI models within client guardrails, with a named human strategist accountable for direction and outcomes. A prompt report should lead to action, not become the deliverable.
Our current agency reviews accounts once a week and charges a percentage of spend. What modern execution alternatives should we evaluate?
The one adjustment that matters: Keep once a week and percentage of spend only if they describe the operating model you want to test against; otherwise, replace them with its real review cadence and fee structure. Prompt 32 is the most useful artefact in this file because it asks about the mechanics behind the purchase, not whether a model can repeat your homepage. It shows which alternatives a buyer sees when they are done paying for periodic, manual management.