Every ‘click here’ is a wasted signal. Anchor text, the visible words of a link, tells AI what the destination is about before it arrives. Descriptive anchors teach a machine the meaning of the page on the other end; vague ones teach it nothing, throwing away one of the easiest structural signals you have.
- Every “click here” is a wasted signal; anchor text, the visible words of a link, tells AI what the destination is about before it arrives.
- Links are promises: the anchor sets an expectation a machine carries to the target page.
- It compounds. Across a whole store, descriptive anchors build a map of what links to what, and why.
- Make it a habit: write the anchor as a short description of the destination, never “here” or “this page”.
A link does two jobs. It creates a path, and it makes a promise about where that path leads. Humans glance at the words and decide whether to click. Machines read those same words as a label for the destination, a preview of what the linked page is about. “Click here” and “read more” make the path but break the promise: they say nothing about the page they point to.
Links are promises
When you link to a product with the anchor “waterproof hiking boots for women,” you have told the machine what is on the other end before it follows the link. Multiply that across a store and your internal links become a running commentary on what each page means. Vague anchors waste every one of those opportunities.
Why it compounds
Anchor text is structural signal layered on top of your topology. Good topology gets the machine to the page; good anchor text tells it what the page is before it reads it. Together they turn a set of links into a map with labels. This is the wording discipline behind cross-linking your pages well.
| Anchor text | What AI learns about the destination |
|---|---|
| “click here” | Nothing |
| “this page” | Nothing |
| “our return policy” | The target is about returns |
| “waterproof hiking boots” | The target is about waterproof hiking boots |
The habit
Make the linked words describe the destination. Never “click here”; always the actual subject. It is a small editing habit that quietly upgrades every internal link into a teaching moment for the machine. Part of making your store one a machine can follow and understand.
A scan is a snapshot. Legibility drifts
Descriptive anchor text is never settled. A redesign reshuffles the menu, an app changes URL patterns, a bulk edit orphans a page, and the structure a crawler follows regresses silently while the storefront still looks perfect to you. Your catalog and navigation change weekly, so a clean, followable structure is a moving target, not a one-time pass. That is why serious stores measure, fix, and re-measure, and why we re-scan our own store on a schedule, in public.
Questions people actually ask
What is anchor text and why does it matter for AI?
Anchor text is the visible, clickable words of a link. A machine reads those words as a label describing the destination, so descriptive anchors tell it what the linked page is about before it arrives, while vague ones convey nothing.
What's wrong with 'click here' as a link?
It creates a path but makes no promise about where the path leads. The words say nothing about the destination, so a machine learns nothing from them. Replacing them with words that describe the linked page turns a wasted link into a useful signal.
How should I write internal link anchors?
Make the linked words describe the destination in plain terms, such as the product or topic name, rather than generic phrases like click here or read more. Done consistently, this upgrades every internal link into a small label that teaches a machine about your store.
See what a machine sees
You can't tell from your browser whether AI can read your store. You can find out in a few minutes. Run a free scan and see the exact layer the machine reads, and where you're losing the shortlist.
Sources: 2026 industry compilations on AI-search visibility; OpenAI (early 2026) on ChatGPT shopping queries; Adobe Analytics (2026) on AI retail traffic; Gartner (2024) on traditional search. Figures are third-party and current as of mid-2026; we publish our own benchmark data as our scan volume grows.