Structured Data That AI Search Engines Actually Read

Make Sure the Crawlers Can Actually Read You A surprising number of brands are invisible for the dullest possible reason. Their robots.txt blocks the crawlers that feed AI systems, or their content only appears after JavaScript executes, or their key pages sit behind a form.

Marketing copy does not get quoted. A paragraph of adjectives about your commitment to excellence contains nothing a model can attribute, so it is skipped in favour of a competitor who wrote a plain answer. Write the plain answer. ai visibility agency

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.

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.

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.

What Ranking Does and Does Not Buy You Ranking still helps, because the retrieval step usually starts with a search. But it buys far less than people assume. Ahrefs examined 15,000 long-tail prompts across four assistants in July 2025 and found roughly 80 percent of cited pages did not rank for the original query at all, with about 12 percent in the top ten.

One thing worth deciding before you start is who inside the business will answer factual questions. This work generates a steady trickle of small queries about lead times, price ranges and what you will and will not take on, and an agency that cannot get answers will either stall or guess. Naming one person and giving them twenty minutes a week removes the most common cause of these projects drifting.

Search marketing has a long history of reporting numbers that rise while the business does not. Impressions, rankings for terms nobody buys on, traffic to pages with no commercial intent. The new channel has arrived with its own version of this, and the version is worse, because there is no independent console to check the claims against.

Track three things over time: how often you are named, which sources get cited when you are, and which competitors appear alongside you. Movement in the second of those usually predicts movement in the first.

Getting onto that list is not luck and it is not a trick. It is a sequence of fairly unglamorous steps that make it easy for a model to find you, understand you and feel safe naming you. This is what that sequence looks like in practice. ai visibility agency

The Types That Rarely Earn Their Keep Elaborate breadcrumb hierarchies, speakable markup, deeply nested item lists and most of the specialised types outside their intended vertical produce little observable difference in how a brand is understood or recommended.

This is a plan rather than an explanation. It assumes you have already accepted that some of your buyers are asking an assistant for recommendations before they contact anybody, and that you would prefer to be named.

Give the Machine a Stable Identity to Attach To Models build a picture of your company from scattered mentions. That picture holds together only if the details are consistent. Your legal name, trading name, founding year, location, leadership and product names should read the same on your website, your structured data, your social profiles and every directory that lists you.

Then Measure Again, and Keep Measuring A single snapshot tells you very little. Assistants vary their answers between sessions, between accounts and between model versions, so one run is a sample and not a verdict. Re-run the same prompt set on a fixed schedule and watch the trend rather than any individual answer.

The more useful signal is qualitative and free. Add one question to your enquiry form or your first sales call asking how the person came across you, and read the answers monthly. When people start saying an assistant recommended you, or start repeating a description of your business you did not write, something has changed in a way no dashboard captured.

Ahrefs measured this in July 2025 across 15,000 long-tail prompts and four assistants, finding roughly 80 percent of cited pages did not rank for the original query, with about 12 percent in the top ten. The overlap is real but partial, which is the worst case for planning: you cannot ignore your rankings and you cannot rely on them either.

Statistics without sources. This field circulates figures faster than it checks them, and a number arriving without a publisher, a sample size and a date should be discounted rather than repeated to your board.