Start with the buying situation
Write down what the person wants, their scale, constraints and criteria. The question ‘Which service can help me check website citations without a dedicated analytics team?’ is more useful than a string of words such as ‘best GEO AI website.’ The first establishes a selection scenario; the second poorly defines the answer needed. Use customer conversations and inquiries when they genuinely exist; otherwise call the formulations working hypotheses. A generated set of questions does not become a history of buyer inquiries.
Separate discovery from recognition
A neutral question tests whether the assistant suggests the company among suitable solutions. ‘Is AURA GEO suitable for my website?’ already supplies the brand and is useful for checking how its capabilities are explained. It cannot count as independent product discovery. In a small panel, include several selection tasks, one question about a suitable workflow and a separate group of branded clarifications. Before running it, record why each question matters to the business's actual offering.
A sample panel, not demand statistics
An educational example for a small agency might cover choosing a monitoring tool, examining competitor sources, measuring referrals and discussing work with its own agent. These are four different decisions, not four variations of one keyword. Do not add your platform name to each question or ask ‘make sure you recommend us.’ Preserve the original wording and language so the next check answers the same question rather than a more convenient reformulation.
Organizing questions in AURA GEO
The project list lives under ‘Visibility → Customer questions.’ Through MCP, an agent can read it, add questions and pause unnecessary ones within its granted permissions. Use neutral checks as monitoring and leave writing ideas for content. To check business context, save the exact name, category and acceptable spelling variants: a similar-sounding word does not necessarily mean your company. Auri helps work with the available context but does not replace knowledge about actual buyers.
What the preparation should produce
A good panel has a clear purpose and a next step for every question. If answers select solutions by price, the website needs verifiable terms; if they compare integrations, it needs a specific explanation of setup. First record baseline answers, then improve the relevant pages. The question list itself does not submit a website to an index, reveal global query volumes or prove that all ChatGPT users ask that way.
Conditions and limitations
- A project's sample does not represent all AI users' questions and answers.
Explore the details
A verifiable conclusion and next step tied to an actual question, answer or event, with no guarantee of indexing or citation.
Build the project's question set