Fixed buyer questions
Keep the exact wording stable. Record engine, model label where available, date and market context for each run.
METHODOLOGY
Dambru Ads measures AI visibility with fixed buyer-prompt sets, recording brand presence, cited sources and market or engine variation. We calculate share of answer as valid runs where the brand appears divided by total valid runs, then report citations won, enquiries and booked meetings separately. Any sample scorecard is an illustrative format, never a client result.
What is in the scorecard
Keep the exact wording stable. Record engine, model label where available, date and market context for each run.
Share of answer = valid runs naming the brand ÷ total valid runs × 100. Count a brand at most once per answer. Report each engine, prompt group and market separately.
Report the citation URLs that support or describe the brand in observed answers. Distinguish a citation from an unlinked mention and keep the source list.
Count enquiries attributable to the agreed channels only when the business provides the relevant records and tracking context.
Report booked meetings separately from enquiries, using the client's calendar or CRM evidence where provided.
AI answers can vary by prompt, engine, model, date and market. A snapshot is not a universal ranking or a promise about future answers.
Illustrative format, not a client result
| Fixed buyer prompt | Brand named | Source cited | Next observation |
|---|---|---|---|
| “What is Dambru Ads?” | Example status | Example URL field | Check entity wording |
| “ChatGPT Ads agency Texas” | Example status | Example URL field | Confirm current market status |
| “GEO agency for small business” | Example status | Example URL field | Review supporting evidence |
This is an illustrative format, not a client result or measured score. No values, clients, results or performance metrics are represented.
FREE AI VISIBILITY AUDIT
The free audit provides the prompt-level starting point; ongoing reporting is scoped only after the audit.