Before paying for an AI-visibility project aimed at a specific channel, someone has to read that channel’s inclusion rules. That sounds obvious, and it is easy to skip, because the rules sit on a help page and the project sits in a proposal. Reading the page takes minutes. The method below keeps the reading disciplined, and it uses Shopify’s Catalog requirements page as the working example because the page is public and specific.
Begin by finding the platform’s own page. Search the platform’s help or documentation site for its eligibility or requirements page, and prefer that to a summary written by someone else. A third-party summary may be accurate, but it may also describe an earlier version of the rules or leave out an exclusion. Save the link, and note the page title exactly.
Then date it, twice. First, record the day you read it. Second, record whether the page shows a date of its own. Shopify’s Catalog requirements page does not show one, so a reader has no way to tell when its rules were written or last revised. That does not make the page unreliable, and it is the primary source. It does mean the date you read it is the only date you have, and it is worth writing down. The page also says eligibility is reviewed over time, and that the types of products that are ineligible can change at Shopify’s discretion. A rule read in November may not be the rule in force in January.
Next, sort what the page says into three kinds. Requirements are things a store must have: a title and an image on each product, a price above zero, an identifiable product URL, verified accounts. Exclusions are things that keep a store or product out: stores restricted to B2B customers, services and product add-ons, private or password-protected stores, and a list of product categories. Operating history is a third kind, covering genuine sales to real customers, orders fulfilled accurately and chargebacks kept low. Pages often blend these together, and separating them shows what kind of work each item calls for.
Sorting by who can change an item is the most useful step. A missing product image is a setting. A B2B-only restriction is a fact about how the business sells. An operating history is something that builds over time. A content project can address the first, may touch the second only by changing the business itself, and cannot create the third. The question to ask of every line is what it would take to satisfy it, and whether that is a content task at all.
If the platform offers its own eligibility view, use it as a cross-check. Shopify announced on October 28 a new admin view that, according to Shopify, shows whether a store qualifies for Catalog and links to fixes for anything blocking eligibility. That is a vendor statement, and whether the view is available to every store is not established here. Still, a view built into the admin reflects the platform’s own current assessment of the specific store, which a general help page cannot.
Write down what the page does not say. It may not say how many stores are in the catalog, how often AI agents use it, or whether inclusion leads to anyone seeing a product. Shopify says AI agents get product information from Catalog. That is a statement of how the platform describes its own system, and from outside, no one can see which assistant used which source in a given answer. ChatGPT, Claude, Gemini, and Perplexity may each draw on different information, and a rule about one catalog does not describe all of them.
A one-line record is enough. It might read: page title, link, read on a given date, page shows no date, stores restricted to B2B customers listed as ineligible, services listed as excluded. Kept in a shared note, that line lets someone else see what was checked and when, and it lets the team notice if a later reading differs from the first.
Finally, set a recheck date. Because the rules can change, an eligibility finding has a shelf life, and a reasonable team writes down when it will look again and what change would prompt an earlier look. That is also where WATCH becomes useful in our framework. If the evidence does not yet justify a project, noting the gap, setting a date to check and recording what would change the decision is a legitimate result, and often a cheaper one than a rewrite.
None of this requires an AI-visibility tool. It requires a page, a date, a pen and a willingness to treat a documented rule as a documented rule: useful, current as of a day, and not a measurement of anything a buyer saw. Eligibility is a different kind of fact from Mentioned, Cited, Recommended, and Chosen. It describes whether a channel can include a business, and the rest of the work begins after that question is answered.
FAQ
What should I record when I read a platform’s inclusion rules? Record the page title and link, the day you read it, and whether the page shows its own date. Note which items are requirements, exclusions and operating history, and which ones you can change.
Why does the date I read the page matter? Platforms can change their rules, and some pages show no date of their own. Shopify’s Catalog page says eligibility is reviewed over time and that ineligible product types can change at its discretion. Your read date is the only reliable date you have.
Can a platform’s eligibility view replace reading the rules? It is a useful cross-check, because it reflects the platform’s assessment of your specific store. It does not replace the rules page, which explains what each item means and what the platform does not say.
Does a platform’s rule tell me how ChatGPT, Claude, Gemini, or Perplexity will answer? No. A rule about one catalog describes that catalog. Which sources any assistant uses in a given answer is not observable from outside, so it should not be assumed.
What if I am not eligible? Decide whether entering that channel is worth it on its own merits, and avoid changing how the business sells only to satisfy one rule. Recording the finding and setting a recheck date is a legitimate outcome.
Is this article reporting a result from Axis Suite? No. It describes a method for reading a platform’s rules and reports no result for any specific brand.
About Axis Suite Axis Suite is the independent intelligence layer that tracks what AI says about your brand and the observable evidence behind it, retrieval, narrative, recommendation, and corroboration signals, across engines including ChatGPT, Claude, Gemini, and Perplexity. Built by TrendAxis, Axis Suite works from a framework that separates Mentioned, Cited, Recommended, and Chosen. Axis Suite is measurement infrastructure, not a marketing quick fix. Explore the Proof Center.