How To Audit Whether AI Recommends Your Brand

What llms.txt Proposes It is a proposed convention: a file at your root offering a curated, plain text guide to your site for language model consumers, pointing at the documents you consider authoritative.

Decide What the Result Means Four outcomes, each pointing somewhere different. Absent everywhere with a clean robots file and no third party listings usually means an identity and coverage problem. Absent with a blocked crawler or an empty non-JavaScript page means a mechanical problem, which is the good news outcome because it is cheap.

Finally, pay attention to how they talk about their existing clients. Somebody who describes a client's category accurately, names the specific constraint that made the work difficult, and mentions something that did not work has actually done the job. Somebody who describes every engagement as a success in identical language has either been unusually lucky or is describing a template.

There is also a straightforward test that costs nothing and tends to end the debate internally. Ask an assistant the question your best customer would have asked before they found you, and read the answer out in the next management meeting. llm seo

What you are looking for is whether the questions sound like a buyer wrote them. If every prompt contains the client's category name phrased the way an internal marketing team would phrase it, they have tested how the brand talks rather than how customers ask.

The Blocks Nobody Chose Most blocking discovered during audits was never a decision. A disallow copied from a template. A staging rule that survived a migration. A security plugin with an aggressive default. A content delivery network setting labelled bot protection with a switch nobody has looked at since launch.

A frequently quoted comparison showing assistant referrals converting several times better than search came from a vendor selling the service, across 312 business to business brands. A widely shared claim about explosive referral growth rested on nineteen analytics properties. Both are legitimate observations and neither supports the confident generalisation usually attached to them.

Deciding Whether to Block Anything There is a legitimate argument for restricting training crawlers, particularly for publishers whose archive is the product. That is a commercial and editorial decision and it deserves a real discussion rather than a default.

Read the Source List Before the Prose Where citations are shown, list every domain and count how often each appears. This is the single most useful output of the whole exercise, and most people skip it because the prose is more interesting.

Those recurring domains are the pages your category's answers are being built from. Visit each one, look for yourself, and note whether you are absent, listed with stale details, or filed under the wrong category. That list is your task list, and you did not have to guess at it.

Ask What They Cannot Measure A competent practitioner will volunteer limitations before you ask. Assistant answers vary between sessions. Referral attribution is inconsistent. Some assistants cannot be measured reliably at all. Sample sizes in the published research are small.

Bring one other person from the business, ideally from sales. They will spot inaccuracies in how you are described that a marketing reader skims past, and they will tell you within minutes whether the prompts sound like real customers. That second opinion costs half an hour and prevents the most common flaw in a self run audit, which is a set of questions written in the company's own language.

One practical note on prioritising outreach. Sort your citation list by frequency and start at the top, not at the most prestigious name. A directory that appears in half your category's answers is worth more than a publication that impresses your board and has never been cited once. This is the point at which visibility work and conventional public relations objectives diverge, and it is worth saying out loud before the two budgets start competing.

Put someone's name against this. Crawler rules sit between marketing, development and whoever administers the content delivery network, which in most organisations means nobody checks them. The failures documented here are not difficult to find, they are simply nobody's job, and a quarterly review taking half an hour prevents the most complete form of invisibility available.

The practical result is that a claim appearing only on your website is treated as a claim, while the same claim appearing in a trade publication, a review platform and a forum thread starts being treated as a fact about the world.

What You Can Do Legitimately More than most teams assume. Claim every profile that allows it and complete it properly. Correct factual errors on platforms that accept corrections, which most do when you have evidence. Respond to reviews, including critical ones, since an unanswered complaint reads as inattention.