GEO Brand Question Generator

To be cited by ChatGPT, Perplexity and Gemini, your content has to answer the questions people actually ask them about your brand. This tool maps those questions across four intent stages — awareness, consideration, comparison and decision — so you know exactly what content to create.

Try:

Questions are grouped by the four stages of AI search intent. Use them as headings, FAQ entries and content topics.

Question coverage is one part of the picture. The full audit also scores AI model recall, crawler access, structured data and crawl budget in a single graded report.

Run the full audit

Prompt coverage reference

AI answers are generated per prompt, not per keyword. Ranking for "best CRM software" in Google does not mean a model mentions you when someone asks "which CRM should I use for a 5-person team". Generative engine optimisation works by mapping the prompts that matter and answering them explicitly on pages a crawler can read.

The four intent stages

Stage	User is asking	Where to answer
Awareness	Does this brand exist and what is it	Homepage, About, Organization schema
Consideration	How does it compare to alternatives	Comparison and alternatives pages
Evaluation	Pricing, limits, trust, integrations	Pricing page, docs, FAQPage schema
Decision	Is it right for my specific case	Use-case pages, customer stories

How prompts differ from keywords

Length — conversational prompts average far more words than search queries, and carry constraints ("for a small team", "without a credit card") that the answer must satisfy.
Comparative framing — a large share of commercial prompts name a competitor or ask for alternatives. If you have no comparison content, the model reasons from your competitor's page.
Single answer, not ten links — there is no position two worth having. Either the model names you or it does not.
Answer synthesis — models assemble responses from several sources, so a page that answers one prompt cleanly can be cited for many related ones.

Turning prompts into content

Use the exact question as an <h2> or <h3>. Models match headings to prompts.
Answer in the first two sentences beneath the heading, before any preamble. Extractive systems take the opening span.
Mark up question-answer pairs with FAQPage JSON-LD so the pairing is machine-readable, not just visual.
State facts plainly and with specifics. "Starts at $19/month for 60 reports" is quotable; "affordable pricing" is not.
Write the comparison pages. Being absent from a category comparison is how competitors get recommended by default.

Measuring whether it worked

Publishing answers does not guarantee recall. Model knowledge updates on training and index cycles, so the loop is: generate prompts here, publish answers, then re-run the visibility audit to see whether recall and sentiment actually moved.

Get a baseline before you write, so you can prove the content moved the needle.