How to see which search intents you win in AI answers, without the heat-map squint
The heat-map ritual: platform, window, metric, intent drilldown, three rivals compared cell by cell. The lead/lag read is one sentence.
Before, the dashboard ritual
8 steps · 3 menus · 1 heat-map scan
- Open the AI Visibility dashboard
- Platform: ChatGPT
- Segment: AI Tracker
- Dates: last 4 weeks
- Metric: Share of Voice
- Drilldown → By Intent
- Add the 3 tracked rivals
- Scan the heat map row by row
After, one question
By intent, where do we lead in AI answers and where do competitors dominate?
Paste it into Claude, ChatGPT or Cursor with Quattr MCP connected. No tool names, no field names, routing is the assistant's job.
The answer
By intent, where do we lead in AI answers and where do competitors dominate?
Analysis plan, every step, resolved for you
- Routed to the governed workflow
aeo-audit - Scope resolved before filtering
segment: AI Tracker · Jul 5 to Aug 1, 2026 - 1 analysis queued
ai_visibility_drilldown - Honesty gates armed
scope echo · freshness
You lead 4 of 9 intents; one comparison intent belongs to a rival.
- Intents you lead
- 4 of 9
- Biggest gap intent
- Comparison pages crestrow.example leads by 11 pt
| Intent | Your citation rate | Leader | Gap |
|---|---|---|---|
| Getting started | 14.2% | acme.example | you lead |
| Integrations | 9.6% | northfield.example | −4.1 pt |
| Pricing | 4.3% | northfield.example | −8.8 pt |
| Troubleshooting | 11.8% | brightpath.example | −1.2 pt |
Jul 5 to Aug 1, 2026segment: AI Tracker
⚠ Observationalas of Aug 1, 2026IllustrativeOpen in Quattr ↗
Intent names come from your own taxonomy, the gaps map straight onto a content plan.
A simulated conversation on fictional data, composed from this workflow's scenario by the same director that renders every demo on this site, scope, freshness and the ⚠ Observational marker are attached automatically, not written by hand.