How to Tell If Your AI SEO Agency Is Working
Testing too rarely means you find out about a problem a quarter after it started. Testing too often means drowning in variance that looks like signal and reacting to noise. Both failures are common and the second is more expensive, because it produces work.
The defensible version states the mechanism, cites the available evidence with its sample sizes, presents your own segmented data however thin, and is explicit that most of the channel's value is not measurable through referrals at all.
Category Costs Rise as Coverage Fills In Influencing the third party sources assistants cite is easiest while those sources are thin. A category with two mediocre comparison articles is inexpensive to influence. The same category in three years, once somebody has built the definitive resource that every assistant settles on quoting, is not.
What It Should Not Cost This is a defined piece of work with a defined output, and it should be priced that way. Be cautious about audits bundled inescapably into a twelve month retainer, since that structure gives the diagnosis a commercial interest in the treatment.
The test is simple. If somebody on your sales team reads a question and does not recognise it, delete it. The value of this entire approach rests on the questions being real, and a set half filled with invented ones is barely better than a keyword list. brand mentions in ai answers
One check is worth running independently once a quarter, without telling anyone. Take ten prompts from the agreed set, run them yourself in a signed out session, and compare what you find against the most recent report. Broad agreement is reassuring. A consistent gap in the agency's favour is the single most informative finding available to you, and it is not something a report will ever surface.
Distinguish between a supplier who is failing and one who is reporting badly, because the remedies differ entirely. Ask for the raw answers and read them yourself before deciding. It is not unusual to find that sound work has been buried under a dashboard nobody understands, and fixing the reporting is far cheaper and less disruptive than replacing a team that is actually doing the job.
This means a single answer is a sample. Being absent once is not evidence of a problem and being named once is not evidence of success, and treating either as a result is the most common analytical error in this field.
An agency doing the work sends these the same day, because they already exist as a by-product of the measurement. One that does not will explain that the platform does not export in that format, or that the data is summarised in the dashboard.
If you must change the prompt set, add new prompts as a separate cohort and keep the original series running unchanged. Editing the instrument retrospectively destroys the comparison you have been building.
The specific damage is that somebody sees a dip, rewrites a page, sees the number recover for unrelated reasons, and concludes the rewrite worked. That false lesson then gets applied elsewhere. A slower cadence with more runs per prompt is more informative than a faster one with fewer.
The Cheapest Fixes Have a Deadline That Already Passed Audits routinely surface mechanical problems that have been quietly costing visibility for months. Crawlers blocked in robots.txt. A bot management product returning challenges to legitimate retrieval agents. Key content rendering only after JavaScript executes. Specifications trapped in a PDF.
Ask sales to note the question asked on every call for a month, in the prospect's words rather than paraphrased. Export support tickets and sort by frequency. Pull the query report from Search Console. And read the first message from inbound enquiries before anyone has reshaped it.
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. brand mentions in ai answers
Keeping It Honest Two disciplines keep this from decaying. First, the answers have to be checked by somebody who knows the business, because a writer working from notes will approximate a figure and an approximation published as fact is a liability you carry rather than they do.
Why the Direction Is Plausible Anyway Set the numbers aside and the mechanism is straightforward. Somebody arriving from an assistant has already had their question answered, has already seen a comparison, and has been given your name as a recommendation.
Ask what was done, not what happened. If listings were corrected, pages rewritten and outreach attempted, and the numbers are still flat, that is information about the market. If none of it happened, the numbers were never going to move.
Where to Put Them Individual pages for questions with real volume and commercial weight, grouped sections for the smaller ones. Both work, and the decision should follow how much there is to say rather than a rule.
The defensible version states the mechanism, cites the available evidence with its sample sizes, presents your own segmented data however thin, and is explicit that most of the channel's value is not measurable through referrals at all.
Category Costs Rise as Coverage Fills In Influencing the third party sources assistants cite is easiest while those sources are thin. A category with two mediocre comparison articles is inexpensive to influence. The same category in three years, once somebody has built the definitive resource that every assistant settles on quoting, is not.
What It Should Not Cost This is a defined piece of work with a defined output, and it should be priced that way. Be cautious about audits bundled inescapably into a twelve month retainer, since that structure gives the diagnosis a commercial interest in the treatment.
The test is simple. If somebody on your sales team reads a question and does not recognise it, delete it. The value of this entire approach rests on the questions being real, and a set half filled with invented ones is barely better than a keyword list. brand mentions in ai answers
One check is worth running independently once a quarter, without telling anyone. Take ten prompts from the agreed set, run them yourself in a signed out session, and compare what you find against the most recent report. Broad agreement is reassuring. A consistent gap in the agency's favour is the single most informative finding available to you, and it is not something a report will ever surface.
Distinguish between a supplier who is failing and one who is reporting badly, because the remedies differ entirely. Ask for the raw answers and read them yourself before deciding. It is not unusual to find that sound work has been buried under a dashboard nobody understands, and fixing the reporting is far cheaper and less disruptive than replacing a team that is actually doing the job.
This means a single answer is a sample. Being absent once is not evidence of a problem and being named once is not evidence of success, and treating either as a result is the most common analytical error in this field.
An agency doing the work sends these the same day, because they already exist as a by-product of the measurement. One that does not will explain that the platform does not export in that format, or that the data is summarised in the dashboard.
If you must change the prompt set, add new prompts as a separate cohort and keep the original series running unchanged. Editing the instrument retrospectively destroys the comparison you have been building.
The specific damage is that somebody sees a dip, rewrites a page, sees the number recover for unrelated reasons, and concludes the rewrite worked. That false lesson then gets applied elsewhere. A slower cadence with more runs per prompt is more informative than a faster one with fewer.
The Cheapest Fixes Have a Deadline That Already Passed Audits routinely surface mechanical problems that have been quietly costing visibility for months. Crawlers blocked in robots.txt. A bot management product returning challenges to legitimate retrieval agents. Key content rendering only after JavaScript executes. Specifications trapped in a PDF.
Ask sales to note the question asked on every call for a month, in the prospect's words rather than paraphrased. Export support tickets and sort by frequency. Pull the query report from Search Console. And read the first message from inbound enquiries before anyone has reshaped it.
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. brand mentions in ai answers
Keeping It Honest Two disciplines keep this from decaying. First, the answers have to be checked by somebody who knows the business, because a writer working from notes will approximate a figure and an approximation published as fact is a liability you carry rather than they do.
Why the Direction Is Plausible Anyway Set the numbers aside and the mechanism is straightforward. Somebody arriving from an assistant has already had their question answered, has already seen a comparison, and has been given your name as a recommendation.
Ask what was done, not what happened. If listings were corrected, pages rewritten and outreach attempted, and the numbers are still flat, that is information about the market. If none of it happened, the numbers were never going to move.
Where to Put Them Individual pages for questions with real volume and commercial weight, grouped sections for the smaller ones. Both work, and the decision should follow how much there is to say rather than a rule.
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