How To Audit Whether AI Recommends Your Brand

Making Any Model Safe Four clauses do most of the protective work regardless of structure. The prompt set and baseline archive belong to you and leave with you. Raw answers ship with every report. Scope is stated in countable units. And there is a defined review point with agreed criteria before the contract auto renews.

The more useful signal is qualitative and free. Add one question to your enquiry form or your first sales call asking how the person came across you, and read the answers monthly. When people start saying an assistant recommended you, or start repeating a description of your business you did not write, something has changed in a way no dashboard captured.

What Honest Reporting Contains The prompt set, versioned and unchanged since last month. The raw answers, kept in full rather than summarised. Which competitors were named. Which sources were cited. What work was done. What moved, and the specific claim about which work caused it.

You can do this yourself in about half an hour, with no subscriptions and no technical knowledge. It will not be as thorough as a full engagement, and it is more than enough to establish whether you have a problem and roughly what kind.

Run each one across the assistants your customers use, and write down the answers verbatim. Do this from a signed out session so your own history does not colour the result. What you want at the end is a simple table: which prompts named you, which named competitors, and which sources got cited.

Watch the quality of enquiries as well as the count. A common early signal is that conversations start further along, with the prospect already aware of your price band, your typical timeline and what you do not do, because a machine told them before they arrived. That shows up in sales cycle length and in fewer wasted calls long before it shows up in any dashboard.

Turnaround times, dimensions, capacities, coverage areas, price ranges, compatibility lists and limits all get lifted directly. Pages built around them get cited well above their apparent sophistication, and a plain table frequently outperforms a beautifully written essay.

This applies to independent roundups, generative engine optimization alternatives pages and side by side tables alike. The consistent trait is that real options are named and weighed on concrete axes, rather than one option being argued for.

The problem is not that the tools are dishonest. It is that the vendor controls both the number and the prompt set that produces it, so the score can improve without anything happening to your business, and a client has no way to audit the difference.

Search marketing has a long history of reporting numbers that rise while the business does not. Impressions, rankings for terms nobody buys on, traffic to pages with no commercial intent. The new channel has arrived with its own version of this, and the version is worse, because there is no independent console to check the claims against.

There is a specific moment worth picturing. Somebody types a question into an assistant asking who they should use for the thing you sell. A short list comes back. If your name is not on it, you were never in the running, and unlike a search results page there is no second page for them to try.

Pricing in this field is unusually opaque, partly because the work is new and partly because the absence of an independent scoreboard makes it hard for a buyer to tell whether they are getting value. That combination invites vague scoping.

Start by Finding Out Where You Stand Before changing anything, establish what assistants currently say. Write out the questions a buyer would actually ask, in their words rather than yours. Include the category question, the problem question, the comparison question and the question that names your competitors directly.

One inversion is worth noticing in your own analytics. The pages that earn citations are frequently not the pages that earn traffic, and teams optimising purely for sessions will deprioritise exactly the specification and comparison content that this channel uses. Keeping a separate note of which pages appear in citation lists prevents a well performing asset being retired because its visit numbers looked unremarkable.

What to Do First Run five prompts describing a purchase your best customer would be making, from a signed out session, and see what gets named and cited. Then check whether your product data survives with scripts disabled, and whether your name and identifiers are consistent across every listing you can find.

This is why glossary style content and plainly written explainers appear so often. It is also why leading with the answer matters so much: a page that spends four paragraphs arriving at its definition contains nothing usable until the fifth.

The second is freshness. Because retrieval is live, current figures beat stale ones, and a competitor can displace you by updating a page you have left alone for two years. Dating your content honestly and revising the numbers rather than the timestamp is a small habit with a large effect.