What An AI SEO Agency Should Report Every Month
What Padding Looks Like Screenshots of favourable answers with no indication of how many runs produced them. Industry news summaries that could have been written without opening your account. A rising score with no methodology. Traffic charts from unrelated channels included to fill space.
The reasonable reading is that ranking gets a page considered while quotability and corroboration decide whether it is used. Treating a strong search position as an entitlement to appear in answers is the mistake that catches out established brands most often.
And in a fast moving category where competitors are actively publishing, monthly can miss a shift. Even then, keep the full set monthly and run a small subset more frequently rather than expanding everything.
Days Fifteen to Thirty: Fix the Plumbing Someone technical checks that the crawlers feeding AI systems can reach your site, that your bot protection is not silently blocking them, and that your important pages contain real content without JavaScript running.
The output is a spreadsheet and it is the most important document in the project. It tells you whether you are named, whether what is said about you is true, who is named instead, and which pages your category's answers are actually built from.
When to Test More Often Three situations justify a tighter loop. During an active campaign where you need to attribute a specific change, weekly runs on a subset of prompts are reasonable, provided you accept the variance.
Ask for one change and see what happens: request the raw answers and the run counts. An agency doing the work sends them the same day, since they already exist. One that does not will explain why the format makes that difficult. structured data for ai search
The practical response to that uncertainty is to work on the things that are robust to it. Accessible pages, coherent identity, quotable writing and honest third party coverage have helped under every configuration observed so far, and they are the parts you would want anyway. structured data for ai search
Refusals matter. A report that only contains successes is either describing a suspiciously easy month or omitting the parts that did not work, and the omitted parts are usually where the useful information is.
Work Completed, in Countable Units Listings claimed, with names. Errors corrected, with the source and what was wrong. Pages published or rewritten, with URLs. Technical changes made, with dates. Outreach attempted and its outcome, including refusals.
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.
Days Thirty to Sixty: Correct the Record Take the ranked list of cited sources from phase one and go through it. On each source, check whether you appear, whether the details are right and whether the platform accepts corrections.
What needs you: factual accuracy. Somebody inside the business has to confirm the numbers, limits and claims before publication, because you carry the consequence of anything untrue being published about your own products.
Nobody outside the labs has the full picture, and anyone claiming otherwise is guessing with confidence. What we do have is a large volume of observable behaviour, published research and the citations that several assistants display openly, and those three together support some reasonably firm conclusions.
Weeks One and Two: The Baseline You should receive a prompt set for review, built from your sales notes, support tickets and search queries rather than from your website copy. Read it and check that it sounds like your customers.
It is also worth asking for the report a day before the meeting rather than seeing it in the room. A document presented live is experienced as a narrative and approved on the strength of the delivery. The same document read beforehand is experienced as evidence, and the questions that occur to you reading it alone are usually the ones worth asking.
This explains the most common frustration brands report, which is watching a competitor with a worse website get recommended instead. That competitor is usually not better optimised. They are more written about, and the system is weighing the difference.
We also know the picture is unstable. Retrieval strategies are revised without announcement, and a method that explained answers well six months ago may explain them poorly today. Anyone selling certainty here is selling something they do not have.
Watch the source list as closely as the mention rate, because it usually moves first. New citations from a directory you corrected are a leading indicator, and they typically appear a month or two before any change in whether you are recommended.