A product description is easy to generate and surprisingly easy to get wrong. Give an AI only a product name and it may fill the gaps with features that sound reasonable. “Waterproof,” “recycled” and “machine washable” are useful selling points, but only when they’re true.
The time saving comes from getting a workable draft quickly. You still need someone who knows the product to decide what belongs on the page.
Start with a product record you trust
Before asking for copy, collect the details you can verify:
- Materials, dimensions and weight
- Variants and the differences between them
- Compatibility, capacity or fit
- Care instructions and known limitations
- What’s included and what must be bought separately
- Evidence for any performance or certification claim
Mark unknown fields as unknown. Ask the model to leave them out or flag them for review, rather than completing the record from a similar product.
Keep this source record separate from the finished copy. When a specification changes, you’ll know which descriptions need another look.
Show what your brand sounds like
“Make it premium” leaves a lot to interpretation. Two or three descriptions you’ve already edited are more useful.
Add a short note about your readers and how you speak to them. For example: explain the practical benefit first, use everyday language, and avoid calling every item a must-have. Include any words your brand uses differently from the industry.
Examples also need checking. If the sample describes a waterproof jacket, be explicit that its features must not carry into the description of a cotton overshirt.
Give the draft a clear brief
A useful brief might be:
Write a short opening that explains who this product suits, followed by a specification list. Use only the supplied product facts. Match the tone of the examples, but don’t copy their claims. Flag missing information separately.
Choose the length around the buying decision. A replacement part may need a compatibility table more than a story. A sofa may need a fuller explanation of dimensions, fabric and delivery.
When several variants share a description, tell the model which details change. Otherwise it can mix a feature from one version into another.
Edit for the customer, sentence by sentence
Read the draft beside the source record. Check numbers, materials, care instructions and every claim about what the product can do.
Then read it without the source record. Would a customer understand the difference between this product and the next one? Is there a clear reason to choose a particular size or version?
Cut phrases that could describe anything in the catalog. Replace “exceptional comfort” with the construction or fit detail that explains the comfort, if you have one. Remove an adjective when there isn’t a useful fact behind it.
Reading aloud helps catch awkward phrasing. It won’t catch a wrong measurement, which is why the factual check needs its own pass.
Try a small batch before scaling
Choose a handful of products with different needs: a simple item, several variants, a technical product and one with frequent returns. Draft and review those first.
Record the mistakes you find. If the model keeps inventing care advice or hiding size information, change the brief before generating hundreds more descriptions.
Give each batch a reviewer and a publication status. Keep the previous copy available so mistakes are easy to reverse. Bulk publishing unreviewed drafts only moves the editing work into customer support.
Put the copy in context
A good description won’t compensate for inaccurate photography, buried delivery terms or confusing variants. Review it inside the actual product page, especially on a phone.
The same factual discipline applies to AI-assisted product photography: the presentation can improve, but the product being promised must stay the same.
Use the saved writing time to answer questions the old page left open. That’s a more useful result than a larger catalog of polished-sounding paragraphs.