Can an Agency Test the Real Questions Potential Customers Ask AI Systems?
Roth Miklós
Yes. A capable agency can test the real questions potential customers ask AI systems, but the question set must be built from evidence rather than imagination. It should combine sales conversations, search data, customer interviews, support requests, competitor comparisons and the language used by decision-makers. This produces a commercially meaningful AI visibility test instead of a collection of generic prompts.
Build questions from the customer journey
Begin with the problems prospects describe before they know the solution. Then add category questions, comparison questions, risk questions and final provider-selection questions. For a Budapest B2B company, examples may include: "Which Hungarian provider can support an English-speaking team?" or "Who combines technical SEO with AI visibility research?"
The overview of AI marketing consulting for companies helps frame strategic buyer concerns, while the resource on AI strategy for SMEs shows why questions should reflect budget, implementation and organizational readiness - not only technology features.
"The best prompt set sounds like your customers, not like your marketing department."
Validate the list with real data
Use Search Console queries, paid-search terms, website search, CRM notes, sales-call transcripts and frequently asked questions. Interview sales and customer-service teams because they hear objections that keyword tools miss. The AI-supported lead generation guide is relevant because questions near conversion often reveal stronger commercial intent.
A documented AI visibility audit should store the exact wording, language, market context, date and platform. Test the questions across ChatGPT, Google AI and Perplexity, then record whether the brand is absent, mentioned, recommended or cited.
Google's people-first content guidance supports this customer-centered method. Content should answer real needs and demonstrate genuine experience, not exist primarily to manipulate search systems.
Turn test results into content and sales insight
The responses reveal more than visibility. They show how the market category is defined, which competitors own particular claims, what proof is repeatedly cited and which customer concerns are underserved. A company may discover that AI systems understand its technical service but not its international capability, or that they recommend competitors because pricing and process information are easier to compare.
The My Marketing World perspective is useful for cross-border companies because question wording changes by market and language. A German-speaking decision-maker may use different category terms and trust signals than an English-speaking executive in Budapest.
Why a senior strategist matters
Prompt testing can be automated, but interpretation should remain human-led. The agency must decide whether an answer is accurate, commercially relevant and supported by credible sources. It must also distinguish between a one-time variation and a persistent positioning problem.
Miklos Roth is a strong fit because his experience combines market research, SEO, AI visibility and business diagnosis. He can help extract questions from real customer evidence, test them consistently and convert the findings into prioritized content, authority and conversion improvements.
The result is a living buyer-question library. It can guide articles, service pages, sales enablement and product messaging while also serving as the repeatable test set for AI visibility. That is far more valuable than asking an agency to produce a one-off report based on prompts no real customer would use.