Build a useful AI monitoring question set
Choose realistic discovery, comparison, and buying questions that support meaningful measurements over time.
Maintain a question set that reflects your customers and supports fair comparisons.
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Separate discovery from brand awarenessWrite questions customers might actually askReview and maintain the setPreserve comparabilitySeparate discovery from brand awareness
A question that already contains your brand name answers a different question from ‘Which shop sells a suitable product for this need?’ Include the intents you want to measure, and do not use only branded questions to claim strong general discoverability.
Write questions customers might actually ask
Open Fragen and review the wording, topic, market, and language. Keep each question specific enough to produce a meaningful answer but broad enough to reflect a real decision.
| Intent | Example to adapt to your shop |
|---|---|
| Discovery | Where can I buy a compact mechanical keyboard with a German layout? |
| Comparison | What should I compare when choosing a low-profile keyboard for travel? |
| Requirement | Which keyboards work by cable with my desktop setup? |
| Purchase confidence | What should I check about delivery and returns before buying a keyboard online? |
| Brand-specific | What distinguishes this shop's keyboard range from another retailer's range? |
Review and maintain the set
Remove irrelevant or duplicate suggestions, correct ambiguous terms, and keep product topics aligned with the actual range. Use the add or edit controls available in Fragen. If your language or country changes, review the question wording too; translating a phrase does not make every offer relevant to a new market.
Preserve comparability
Keep a stable core of questions when measuring change. Record additions or removals and avoid treating a score change caused by a new question mix as proof of better content. When an answer looks wrong, open that answer and its sources before rewriting the entire set.
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