Making Your Site Legible To Machines And Humans

Your Pages Contain Nothing Quotable Look at your homepage and count the sentences that could be lifted, attributed to you and remain true and useful out of context. On most brand sites the count is close to zero, because the copy is written to persuade rather than to inform.

If you must change the prompt set, add new prompts as a separate cohort and keep the original series running unchanged. Editing the instrument retrospectively destroys the comparison you have been building.

A false trade off gets invented early in most of these projects. Somebody proposes stripping the design, flattening the copy and restructuring everything around what a crawler finds convenient, and somebody else correctly points out that this would make the site worse for customers.

Fragmented identity produces a specific symptom worth recognising: an assistant knows facts about you but attributes them vaguely, or confuses you with a similarly named business. The fix is dull consistency work across every place your name appears.

Which to Fix First Work in that order, because the sequence is roughly cheapest to most expensive and each step is wasted without the one before it. There is no value in earning press coverage if the crawler cannot reach the page it points at.

One Claim Per Sentence Compound sentences that bundle three ideas cannot be lifted without dragging in material that may not apply. A model faced with a passage where only part is relevant will often skip it in favour of a cleaner source.

Citation happens at the level of a passage, not a page. A model attaches a source to a specific claim it lifted, which means the real unit of work is a paragraph that stays true and useful once it has been removed from everything around it.

And read the raw text periodically rather than only the tallies. Changes in how you are described, from hedged to definite or from generic to specific, often precede changes in whether you appear at all, and no counting method will surface that. how to get recommended by AI assistants

The sustainable version is small and continuous: the prompt set run monthly, listings checked quarterly, a handful of pages updated rather than a burst of new ones, and someone who owns it. That costs less over a year than the three month push and holds its ground. how to get recommended by AI assistants

You asked it to recommend a supplier in your category. It named four companies, two of which you consider inferior to yours, and one you had never heard of. Your name did not come up, and it did not come up on the follow up question either.

Answer the Question That Was Asked Content briefs generated from keyword tools produce pages that orbit a topic without answering anything. A page titled around a question should contain a paragraph that answers that question directly, early, without conditions attached to reading further.

Log the conditions with every run, including which assistant, which mode, whether web access was enabled and the date. When a result moves sharply, the conditions log is usually what tells you whether the world changed or your setup did.

Keep It Current and Say So Because retrieval happens at answer time, freshness carries real weight. A page updated this month can be cited this month, and a competitor can displace you simply by revising a page you have left alone for two years.

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.

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.

It is also worth checking whether you are being confused with somebody else rather than ignored. Short names, generic names and names that begin with a number collide with other organisations more often than distinctive ones. Where that is happening, the answer will contain facts that are true about a different company, which reads as a hallucination and is usually an identity collision with a specific fixable cause.

A final error deserves separate mention because it undoes good work rather than merely wasting effort. Teams that get an early result frequently conclude they have found the mechanism and generalise from one change. A directory correction coincides with a mention appearing, and directory corrections become the strategy, when the actual cause was a rewritten page indexed the same week.

Testing too rarely means you find out about a problem a quarter after it started. Testing too often means drowning in variance that looks like signal and reacting to noise. Both failures are common and the second is more expensive, because it produces work.

The result is a content programme aimed at guesses. Sometimes it works by accident. Usually it produces pages nobody retrieves, and the diagnosis that would have directed the effort correctly costs a fraction of what the content did.