Start with a clean hierarchy.
Ensure that your page uses headings (H1/H2/H3/H4) correctly so that the LLM easily can understand and group the content on your site. If you use other elements such as tables, ensure these are either using the '<table>' format or that your '<div>' has the correct role set. If this sounds too technical, just send the sentence to your dev.
Front-load the summary.
The first two sentences on the page should read like a tight product brief, not a marketing pitch. For example: "This grinder uses 64 mm flat burrs, weighs 3.1 kg, and grinds an 18 gram espresso dose in 7.2 seconds. It offers 30 stepped settings that cover espresso, filter, and French press." That gives an answer engine something it can quote almost verbatim when a user asks about grinder specs.
Use declarative sentences that say one thing clearly.
"The burrs are made from hardened steel." "The grinder produces less than 1 gram of retention per dose." "The motor runs at 350 rpm under load." These are the lines the model will grab when it needs clean, factual output. If you bury those facts inside long, flowing paragraphs, the system has to work harder to slice them out.
Keep paragraphs short. A twelve sentence block about "overall performance" is a good way to have your most important details skipped. Break it up. One paragraph for grind speed, one for noise level, one for consistency measurements. If you need to present numbers, use simple formatting so each figure sits next to a label. For example, write "Grind time for 18 g at espresso: 7.2 seconds" as its own line instead of hiding it inside a paragraph about "fast performance".
Do this, and the model can quickly see what the page is about, where each topic begins and ends, and which sentences are safe to lift.
