Inciteful tracks the questions your buyers ask an assistant, records who gets named instead of you, and turns the measured gaps into the work that closes them. Six modules is the complete list — there is no page here for a feature that does not exist.
7-day trial, no card. Nothing to install on the client’s site.
Core tracking runs on ChatGPT, Google AI Overviews and Perplexity, on every plan. Claude, Gemini, Google AI Mode and Microsoft Copilot are add-ons you switch on for the clients that need them, per client, rather than across your whole roster. Pro and Agency include Microsoft Copilot as a core engine; on Solo it is a $9 per-client add-on.
Who AI recommends, and whether it’s you.
Tracked questions, checked automatically and stored as evidence. Visibility score and trend with a per-engine split, rankings against the rivals you chose, buyer-journey stages, and the full answer log behind every number.
Your slice of the answer, against the rivals you named.
Share of the answer space per run and per engine, up to five tracked competitors, a drill-down into what each rival is winning and which sources power it, topic boards, and the questions where nobody you track is named yet.
Citable pages grounded in real sources.
Retrieves real sources, generates only from them, and verifies every citation. Publish is a gate, not a button: unsourced claims and dead citations are refused. Typed pages, structure scoring and JSON-LD schema out of the box.
Client-ready proof under your name.
Hosted client reports with your branding on them, and prospect reports for a company that is not a client yet — measure their AI visibility, hand over a public link, walk into the pitch already holding the evidence. White-label starts on Pro.
AI visibility report
Corvane is now named in 172 of 248 tracked answers — 69.4%, up from 36% when tracking began. Share of voice is 48.6%, first among the six brands on the board, and the biggest remaining gap is brand strategy, where a six-page cluster is already in draft.
| Question |  ChatGPT |
 Google AIO |
 Perplexity |
|---|---|---|---|
| best brand identity agencies in the uk | Named #2 | Named #3 | In sources |
| who designs brand identities for fintech | Named #1 | Named #4 | Named #3 |
| brand strategy for scale-ups | Not named | In sources | Not named |
Get products recommended by AI assistants.
Product-level tracking for stores, plus a Shopify app that writes schema server-side so crawlers see it in the raw HTML — with a ledger of exactly what was written, and a revert that removes only ours. Listed on the Shopify App Store.
The real templates the generator fills from your products and collections — no placeholders reach the tracker.
WordPress, Shopify, API, CLI, MCP.
Publish where the client already lives: a WordPress plugin, the Shopify app, Markdown, HTML, JSON-LD and WXR exports, a v1 HTTP API, a command-line tool, and an MCP server so an agent can drive Inciteful directly.
A plugin pulls the cluster in as Gutenberg blocks, with the JSON-LD in the head where a crawler will actually find it. Failures and live URLs come back to the dashboard.
Listed on the Shopify App Store. Schema is written to our own metafields and rendered server-side, so crawlers that never run JavaScript still see it — and every write is reversible.
Export the cluster as HTML and JSON-LD and paste it in, or drive it over the API from your own build step.
Same route: structured export, or the API. The content and its schema travel together, so the markup an assistant reads is never left behind.
A versioned HTTP API over the same engine the app runs on. Keys are minted once, hashed at rest and scoped to your account.
A full MCP tool surface, so your own agents can list workspaces, export clusters, run a site-health scan and start deployments without opening a browser.
Pull the export straight into a Replit project, or point an agent at the MCP server and let it publish from there.
Same structured export, same schema. Anything that can take HTML and JSON-LD can take a cluster.
Demo dataEvery surface above is rendered from the dashboard’s own components against the demo dataset, at the width it is drawn at — the product’s layout and its real states, not a customer’s numbers. The live board is on the homepage.
A brand names itself in answers about itself. Those questions are tagged and tracked; they just never set the score you show a client.
Ask an assistant the same question twice and it can name a different set of brands. New and changed results are re-sampled and aggregated, with a confidence band.
Where a dimension cannot be sourced — question volume for AI answers, for one — the cell carries an em dash. Never a zero, never a flattering hundred.
Scope, sample depth and the date it was measured follow the number onto the screen and into the client report.
Three things a competitor’s feature list would show you, and the reason ours does not. Each one is a decision, and each one is reversible the day it can be done honestly.
| Prompt volume | No assistant publishes how often a question gets asked. A gauge that prints a number for it is estimating, and an estimate dressed as a measurement is the exact thing this product exists to replace. |
|---|---|
| Locations | Answers vary by where the buyer is standing. We do not measure that yet, so it appears nowhere: not in the product, not in a screenshot, not in a sentence on this site. |
| Customer logos | Every mark on this site is a real client shown with permission - the marquee on the homepage is exactly that, nothing borrowed. Case-study numbers appear only once a client agrees to be named beside a figure we measured. |
Start a 7-day trial, no card. Or get the free report first and read the evidence before you decide anything.