Engines assemble recommendations from evidence, and not all evidence is equal. Six types do most of the work: specifications, pricing, fit statements, third-party corroboration, recency signals and exclusions. Knowing which type unlocks which prompt family turns vague "improve the content" advice into a scheduled workstream.
Specifications unlock comparison prompts. When a buyer asks which of two products handles a given requirement, the engine needs numbers on both sides. Missing specs do not produce a cautious mention — they produce silence, because the engine simply cannot complete the comparison with you in it.
Pricing unlocks budget-constrained prompts, which are a large share of all commercial prompts. Published pricing, even as a range or a starting point, outperforms "contact us" dramatically in answer engines. If the client cannot publish exact prices, publish bands and the factors that move them.
Fit statements unlock situational prompts: who this is for, at what size, in what circumstances. These are the statements your hints mirror, and they must exist in public material, not only in the hint. A hint is a targeting instruction; the fit statement is the evidence that backs it.
Third-party corroboration unlocks trust-sensitive prompts. Reviews, analyst mentions, customer stories with named companies and directories that repeat your specs all raise confidence. Self-published claims echoed nowhere else are treated as weaker, particularly in regulated or high-consideration categories.
Recency and exclusions are the two most neglected. Dated, regularly updated pages are increasingly favoured over undated ones, so a visible last-reviewed date is cheap and effective. And explicit exclusions — what you are not for — increase trust measurably, because they make the rest of your claims read as calibrated rather than promotional.