Product / Conversations & Demand
How AI handles your buyers’ questions.
We run your buying questions as real multi-turn conversations on every major engine — does your brand make the first answer, does it survive “pick one”, and what do the engines hold against it. Beside them: the search demand behind each topic.
Conversation · ChatGPT · 3 turnsRUN BY RANKYOURBRAND
best running shoes for marathon training?
For that distance, Nike and Adidas are the strongest fits. Nike's carbon-plate racers…
which one is better for wide feet?
Brand mentioned turn 1 · recommendation held through follow-up
"best running shoes"
COMMERCIAL INTENT · in 2 watchlists
128K ↑12K
monthly searches · illustrative
01
No panel, no scraping
Nobody’s private conversation is involved. The questions are the ones you track, and we ask the engines ourselves.
02
Multi-turn coverage
Follow-ups change recommendations. See where you're dropped — and where you take the answer.
03
Demand behind the topics
Google search volume for the terms behind each tracked topic, with a year of history — set against how often AI answers name you.
Watchlist · Core category12 KEYWORDS · 486K/MO
KeywordIntentVolumeΔ 30d
best running shoesCOMMERCIAL128K↑ 12K
best training shoes for the gymCOMMERCIAL94K↑ 6K
nike vs adidasCOMPARISON41K↑ 9K
how to choose running shoesINFORMATIONAL76K↑ 3K
Demand
Search demand, next to your AI visibility
Monthly Google search volume for the short terms behind each topic, refreshed on request. A modelled estimate of AI questions sits beside it, labelled as modelled — nobody sells a count of what people type into an assistant, and we do not pretend to have one.
Included on Scale plans→
What we never do:
✓No panel
✓No private conversations
✓No session scraping
Read how we sample→
Build a prompt set that reflects buyers.