Structured Data That AI Search Engines Actually Read
The same errors recur across companies of every size, and most of them are not technical. They are misjudgements about where the work lives, made early, and expensive to unwind because the budget has usually been spent by the time anyone notices.
These names go directly into the prompt set and into any comparison content, and getting them wrong sends the entire measurement effort in the wrong direction. If you lose to a low cost regional operator rather than to the market leader, say so.
Do this yourself at least once even if you intend to hire somebody. Reading twenty raw answers about your own market teaches you more about this channel in half an hour than any proposal will, and it makes you a considerably harder client to mislead. You will recognise immediately whether an agency's baseline resembles what you found.
Second, the questions have to keep coming from customers rather than from the content calendar. Within a few months the temptation appears to invent questions to fill a schedule, and invented questions produce exactly the marketing-in-disguise sections that get ignored.
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.
Absence is not disqualifying on its own, since their category is crowded and they may serve a niche. But they should have an interesting answer, and the answer should not be defensive. A practitioner who has run this test on themselves will have thought about it and will tell you what they found.
The defensible position is to spend an hour on it if you like, and to spend the rest of the week on the things every system already reads: accessible pages, accurate Organization markup, consistent identity and content a machine can quote.
Then load your most important page with JavaScript disabled in your browser settings. If what remains is a navigation bar and no substance, that is roughly what a retrieval system reads, and it explains a great deal on its own.
In most categories the pages that generate answers are review platforms, directories, forum threads, comparison articles and trade publications. Being absent or wrong on those explains far more absences than anything on a brand's own site, and correcting a listing costs an afternoon.
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.
A page asking how much something costs that says pricing depends on your requirements has answered nothing, and it will not be cited because there is nothing to cite. A range with the variables named is a real answer and gets quoted.
What to Do About llms.txt and Similar Files Proposals for machine readable files aimed specifically at language model consumers appear periodically. Adoption is inconsistent and support varies by provider, so treat these as low cost and speculative rather than as a requirement.
Starting With Content The most common and the most expensive. A brand decides to take this seriously and commissions twenty articles, without knowing which questions matter, which assistants answer them badly, or which sources those answers are built from.
Two asking who to hire or buy from for the thing you sell. Two describing the problem your product solves without naming the category. Two comparing named competitors. Two asking about a specific situation your best customers are in. One asking directly who your company is. One asking whether your company is any good.
Ask What Happens in Month One A proposal that opens with content production has skipped the diagnosis. There is no way to know what to write before you know which questions matter, which assistants answer them badly and which sources they draw on.
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. hire an ai seo agency that reports honestly
What Structured Data Is Doing Here Markup removes ambiguity. Prose says your company was founded in 2011 and operates in three counties, and a machine has to parse that from language. Structured data states it as a field, with no inference required.
Include the constraints too. The job size you turn down, the sector you do not serve, the situation where a competitor is genuinely the better answer. Those are the statements that get quoted, and an agency will not invent them for you.
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.