Product information for AI shopping: answer the buying constraint
A buying question combines constraints. “Will this fit my space and arrive within budget?” needs dimensions, availability, and total-cost context on a usable page.
Help shoppers resolve fit, compatibility, stock, delivery, and recurring cost. Begin with the buying constraint, then check that the page and the next interaction preserve the same facts.
12 guides
A buying question combines constraints. “Will this fit my space and arrive within budget?” needs dimensions, availability, and total-cost context on a usable page.
Structured product data gives machines explicit fields for product facts. Its usefulness depends on matching what a visitor can actually see and select.
Shipping can turn a suitable product into an unsuitable purchase. Explain what is known before checkout and which details require a destination.
Consider a checkout that accepts an order just before the connection drops. The agent sees a timeout. Retrying should recover the result without creating another order.
Agent Friendly’s negotiation experience is a sandbox for exploring business rules. A simulated offer is not a live merchant price, accepted order, or completed payment.
A product’s size or color can change its price, availability, and identity. Make the selected variant explicit so an agent does not combine one option’s photograph with another option’s offer.
An unavailable product page should state what cannot be bought and what useful options remain. Keeping the product identity visible helps a shopper distinguish an unavailable item from a missing page or loading failure.
A useful return policy makes eligibility, timing, cost, and exclusions easy to find. Put the conditions that change a buying decision near the product instead of forcing every reader through a long general policy.
Dispatch time and arrival time describe different parts of delivery. An agent helping with a deadline needs to know whether a promise covers warehouse handling, carrier transit, or arrival at the destination.
Publish dimensions with units and a clear explanation of what was measured. A buyer deciding whether something fits needs assembled size, usable space, and clearance where relevant—not an unlabeled string of numbers.
Compatibility information should identify the exact device, model, connector, or version supported. “Works with most devices” leaves an agent unable to distinguish a supported pairing from a guess.
An introductory subscription price is only part of the cost. A useful offer explains the initial period, renewal amount, billing interval, and cancellation route before the customer commits.
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Agent Friendly publishes these guides with AI assistance, using the product’s documented behavior and linked primary sources. Practical checks are our editorial suggestions. Examples are illustrative, not customer case studies. Each guide links its evidence and shows its publication and revision dates.
We distinguish discovery, citations, task completion, and payments. We do not claim measured search demand, ranking gains, or AI citations without a recorded baseline. Found a mistake? Send the exact page and correction.