Comparisons
AI Visibility and Editorial Planning: Reading the Features Page
RankAI's features page shows how named AI engines read a page. Here is how to turn that reading into a per-page sheet that drives editorial decisions, with a clear example of a page read differently by two engines.
To understand how a site is read by AI engines and to build an editorial plan, open one of your pages in RankAI's features page and look at how the named engines read it. From that reading you decide which content to strengthen, which to rewrite and which to leave alone. AI visibility, read this way, is not a score to chase; it is an observation that starts the editorial plan. A quick example: if the homepage comes across clearly to ChatGPT and more confusedly to Perplexity, the first editorial decision is to clarify the page's opening, not to add new articles.
What follows is RankAI's proposed way of reading the features page, not a verified description of the product. The public pages name ChatGPT, Perplexity, Gemini, Grok and Google AI. Claude and Grok are measured only after you connect them, so treat them as readers that join later, not as present from the start. Gemini and Google AI Overviews are not the same observation.
What you look at on the features page
In RankAI's proposed reading, the features page is where you observe how public pages are read by several engines. The frame is several readers, not one. The question it helps you answer is concrete: how is this page read? Not whether the site is visible in absolute terms. The difference matters for the editorial plan, because a page can be read well by one engine and poorly by another, and the plan has to account for both readings.
Keep the engines separate. Gemini and Google AI Overviews are two distinct observations, not a single Google judgment, and the reading of Google is not the same observation as the reading of the named AI engines. The plan should treat them as separate points of view.
An example of divergent reading
Take two pages on the same site. The first is a service page with a clear title and a linear description: on the features page it appears to be read in a similar way by ChatGPT and Perplexity. The second is a deep-dive page with many openings and few direct sentences: on the features page, ChatGPT's reading stays centered on the topic, while Perplexity's seems to latch onto a secondary passage. That divergence is the useful signal. The deep-dive page has an ambiguous reading, and the editorial plan can call for rewriting the opening before adding new content on the same topic.
Turning the observation into an editorial plan
The method below is RankAI's operational proposal, not a universal standard. Its purpose is to produce a new artifact: a reading sheet for each page, from which editorial decisions follow.
- Pick a sample page and note the reading for each engine. Test: for every engine named on the features page, write one sentence summarizing how that page is read. If two sentences are incompatible, you have found a divergence to handle.
- Separate the engines instead of averaging them. Test: the reading sheet must have one row per engine, not an average. If you catch yourself writing “in general the engines read…”, the sheet is not ready.
- Add Claude and Grok only when they are available. Test: on the sheet, the Claude and Grok column stays empty until the connection is active. Do not attribute a reading to them before that point.
- Turn the divergence into an editorial decision. Test: every divergence you note must have exactly one action attached (rewrite the opening, add a clarifying passage, move a piece of content to a dedicated page). If a divergence produces no action, remove it from the sheet.
This piece's contribution: the per-page reading sheet
In the reading we propose, the features page is not a ranking of engines but a reading sheet for each individual page. The practical contribution is this: for every page on the site that matters to the editorial plan, fill in a sheet with three columns — engine, reading sentence, editorial action. The reading sentence is a one-line summary of how that engine reads the page; the action is what you will do as a result. Fill in the sheet only with the engines you can actually observe at that moment: ChatGPT, Perplexity, Gemini, Grok and Google AI are named on the public pages, while Claude and Grok join only after you connect them. Keep Gemini and Google AI Overviews separate: they are two distinct observations and belong on two different rows. When a page produces two incompatible reading sentences, that page is a priority candidate for rewriting, before any new content. The sheet becomes the bridge between observation and editorial plan: it does not say whether the site is visible, it says where the reading is clear and where it is ambiguous, and therefore where to intervene first.
A limit to keep in mind
The features page observes how the named engines read pages, but it says nothing about search volumes, prices or ranking results, and it does not replace an external check. An API response is also not a person's screen: what you observe is an indication of reading, not proof of what a user will see on that page. Update the reading sheet when pages or connected engines change, and do not treat it as final data.
For the full picture on how to read the features page and connect it to the editorial plan, see the in-depth page.