How To Audit Whether AI Recommends Your Brand

Third, and least comfortable, reduce dependence on this one channel. Brands that were already visible through communities, direct relationships, email and their own reputation have absorbed the change far better than brands whose entire acquisition rested on informational search traffic.

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.

This is where the two disciplines meet. Work done to make pages quotable for assistants tends to help here as well, because the underlying problem is the same. A model is looking for a passage it can lift and attribute.

Save the document and the date. In three months you will run the same ten prompts again, and the comparison is the only thing that will tell you whether anything you did in between mattered. get recommended by ai

Set Up So You Do Not Fool Yourself Open a signed out session, or a fresh one with memory and personalisation disabled. This matters more than anything else in the method. An account that has spent the week researching your own company will show you a flattering picture that has nothing to do with what a stranger sees.

Nineteen properties can show a real trend and cannot support a confident statement about the market. When that number is repeated without its sample size, as it usually is, it stops being evidence and becomes a slogan.

One reframing helps when presenting this internally. Report the channel as influence rather than acquisition. Acquisition framing invites a comparison against paid media on cost per lead, which this channel will lose on the reported numbers even where it is working, because most of its effect never appears as a referral. Influence framing invites the right question, which is whether more of your market arrives already knowing who you are.

Connect It to Something in the Business Referral traffic from assistant domains should be segmented in analytics and tracked, with the understanding that it undercounts. Some assistants strip referrer data and some visits arrive looking direct.

One thing to establish in week one is where everything lives. The prompt set, the baseline archive, the raw answers and the correction log should sit somewhere you control from the beginning rather than in the agency's systems. Retrieving them later is a negotiation. Having them from the start is an administrative decision nobody objects to at the outset.

If you want your own figure, the segment worth building is narrower than most people set up. Compare assistant referrals against branded organic search rather than against all organic, over at least a quarter, and exclude any campaign traffic. It will be a small sample and it will be about your audience, which makes it more useful for your decisions than a published study about somebody else's.

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.

Log the conditions with every run, including which assistant, which mode, whether web access was enabled and the date. When a result moves sharply, the conditions log is usually what tells you whether the world changed or your setup did.

Being named in answers to prompts with buying intent, as opposed to definitional prompts nobody purchases from. Being described accurately, since a confident recommendation containing a wrong price or a service you discontinued costs more than absence. And being cited on the third party sources that appear repeatedly in your category's answers.

And read the raw text periodically rather than only the tallies. Changes in how you are described, from hedged to definite or from generic to specific, often precede changes in whether you appear at all, and no counting method will surface that. get recommended by ai

This frequently produces the first result of the engagement, because access failures are total and fixing them can change answers within days. It should also be short. A fifty page technical audit at this stage is usually padding drawn from a generic template.

What the Evidence Actually Is The figure quoted most often comes from Opollo, which reported assistant referred traffic converting at 14.2 percent against 2.8 percent from conventional search. The sample was 312 business to business brands, attributed through UTM parameters, covering the third quarter of 2024 through the first quarter of 2025.

What Should Not Have Happened Yet A large volume of new content. Twenty published articles by month three usually means the baseline was not used to direct the work, and the pages were commissioned before anyone knew which questions mattered.