Create a Product Fact Sheet Before Using AI to Write

Before asking AI to write product copy, create a fact sheet that identifies the product, the source of each important detail and the conditions under which that detail applies. Keep missing information and conflicting statements visible. This gives the writer a reliable input and gives the reviewer a way to check the output without rereading every file from scratch.

The sheet can be a simple table. Its value comes from the relationship between claim and evidence, not its file format. A short, traceable sheet is more useful than a large folder in which nobody knows which specification is current.

Which materials should go into the first pass?

Choose one product and gather its current specification, approved commercial notes, product photographs and relevant customer questions. Record where each item came from and when it was checked. Keep different models separate until a product owner confirms that they share the same fact.

A supplier page can be a research input, but its price, minimum quantity or certification should not automatically become your company's promise. Similarly, a photograph can show a feature while providing no evidence of its measured performance. Use each source only for what it actually supports.

What should the fact sheet contain?

The following rows are fictional examples of record structure, not specifications or policies for a real machine.

For measured values, retain units, method or conditions when relevant. A bare number such as “200” cannot tell a reader whether it means units per minute, a maximum test result or a nominal value under particular conditions. If those details are absent, mark them as missing rather than letting the writer choose.

How should you handle conflicting sources?

Keep both statements and identify their sources. Ask the responsible person which version applies to this product and this use. Do not average conflicting figures, select the newest-looking PDF automatically or ask the model to vote on which answer seems more plausible.

Once the conflict is resolved, record the approved value and the reason for the decision. This preserves the path back to the source when a future operator finds the older file again. The same approach applies to differing delivery notes, scope descriptions and image labels.

What is a useful AI request?

Review the supplied materials for [exact product]. Create a fact table with the proposed fact, source, applicable conditions and review status. Keep missing information and conflicting statements in separate rows. Check that the images match this product. Do not write customer-facing promises until the relevant facts are confirmed.

This task produces an input document, not a product listing. You can then give the confirmed sheet to an Opsy product-content task, a human copywriter or a designer. The handoff should make clear which claims may be used and which remain questions.

How do you know the sheet is ready to use?

Pick several proposed statements and trace each one back to its source. Check one number, one commercial condition and one image. If the review depends on somebody remembering what a file “probably meant,” add that missing explanation before drafting.

Public suitability needs a separate check. An internal price calculation, a customer's drawing or a private quality incident may help the business make a decision without belonging in a public article. Record a usable public summary only when the responsible owner approves it. Removing a customer name alone may not make a document suitable for publication.

The Opsy product-draft walkthrough shows the next stage after facts are prepared. If you need help connecting product information to Shopify pages, see GRC's services and Discuss your project with one representative product and the specific information problem to solve.

Use the contact page if you prefer to describe the task and available materials in a form.