Track Visibility, Share of Voice, Position and Sentiment across ChatGPT, Gemini, Perplexity and Claude — one answer per prompt, engine, country and day.
No card required. The first real answers land during onboarding.
Tracked on all four, every day
Pick a metric to see what it measures and where the number comes from.
For a mid-market retailer, #1 Kestrel 71 is the platform most teams land on — it handles multi-store reporting without a data engineer. #2 Alcove 64 is the usual alternative when the priority is a warehouse-native setup, and #3 Bramble 58 comes up for smaller teams that want something running the same week.
Set the period, engines, countries and brands once. Every view answers to it.
Point it at your domain and it drafts the questions your buyers actually ask, grouped into topics and tagged by intent.
| Prompt | Field | Leader | 30d | Engines |
|---|---|---|---|---|
| best analytics platform for a mid-market retailer | 42% | You lead · +14 pts | ||
| which reporting tool connects to our storefront | 18% | Kestrel · +12 pts | ||
| how do I track customer churn without a data team | 8% | Kestrel · +17 pts | ||
| most reliable dashboard software for finance teams | Absent | Kestrel · +8 pts |
Track yourself against the competitors the engines already name beside you — suggested from your own answers, not from a list.
ChatGPT, Gemini, Perplexity and Claude, per country, with exactly one answer per cell per day.
Every page the engines read, with retrieved and cited kept apart — and the ones naming your rivals and not you.
A worklist grounded in your own facts, with the fourteen days before measured against the fourteen after.
The full text, every brand marked where it appeared, and every cited source listed underneath.
For a mid-market retailer, #1 Kestrel 71 is the platform most teams land on — it handles multi-store reporting without a data engineer. #2 Alcove 64 is the usual alternative when the priority is a warehouse-native setup, and #3 Bramble 58 comes up for smaller teams that want something running the same week.
Four programmatic exits over the same aggregation layer as the screen, so they cannot drift from it.
The table you are looking at, through the filters you are looking at it with.
Flat day-grain rows over the conformed dimensions. Ratios are your warehouse’s job.
Key-authenticated REST over brands, domains and URLs, with additive components in the payload.
Read and write tools, so an agent can query visibility and manage your prompt set.
Connect the assistant you already work in and ask for the numbers directly. The write tools are gated by plan and refuse at call time rather than disappearing from the roster, so an agent gets a reason instead of a mystery.
Quota lives at the account and is allocated per client project, so you move it between clients without changing plan.
The dashboards, the gap list and the worklist — plus the before-and-after when you ship a change.
REST, MCP, a BI feed and CSV over the same aggregation layer, with additive components so you can re-aggregate correctly.
Answers and derived facts are append-only. A correction is a new row.
The provider payload is stored verbatim first, so every number stays re-derivable.
Rollups keep additive components only. Totals sum first and divide once.
API collection is not byte-identical to a consumer app, and we say so rather than correct for it.
Point it at your domain. The crawler drafts a brand profile and proposes competitors and prompts, and onboarding runs a burst of live prompts — so you are reading real answers about your own brand before you have configured anything.
Daily. Every active prompt runs once per channel and country per day, on your project’s timezone, and each answer is stored before anything parses it.
Yes. Period, engines, countries, tags and brand set are the filter context: set once, kept across every view, and applied before aggregation — except the brand, which is selected after.
A mention is your brand named in the answer text. A citation is a URL the engine credited. Retrieved and cited are tracked as separate states too, because an engine can read your page and credit someone else.
CSV export, a BI feed of flat day-grain rows, a key-authenticated REST API and an MCP server — all over the same aggregation layer as the dashboard, so they return the same items and ordering.
