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Ecommerce 8 September 2026 7 min read

Using AI to Write Product Descriptions That Do Not Sound Like AI

By The Velocity Wear Team

Ask a language model for a product description for a black hoodie and you will get something about elevating your everyday and effortless style that could describe any hoodie ever made. It is fluent, it is on-brand for nobody, and shoppers skip it. The problem is not the model. It is that you gave it nothing to work with.

Why generated apparel copy fails

A product description has one job: to answer the questions that stop someone buying. For clothing bought online those questions are always the same — how does it fit, what is it made of, how heavy is it, will the print last, and how do I care for it. Adjectives answer none of them.

When you prompt with "write a description for a black hoodie", the model has no specifications, so it fills the space with mood. That is the entire failure mode, and it is an input problem.

Feed it facts, not vibes

The same model produces genuinely useful copy when the prompt contains the things a customer needs to know.

  • **Fabric and weight.** "400 GSM brushed-back cotton-rich fleece" is a fact. "Premium heavyweight feel" is a claim.
  • **Fit and cut.** Relaxed, boxy, true to size, runs small. Include the measurements you actually have.
  • **Decoration method.** Screen printed, embroidered, DTF. Each implies a different durability story you can tell honestly.
  • **Care.** Wash cold, inside out, do not tumble. Care instructions in the description reduce returns and complaints.
  • **Who it is for.** A gym, a band, a corporate rollout. Specific audience produces specific language.

The four tells to edit out

Even with good inputs, generated copy has habits. These four are the ones customers register as "this was written by a machine", usually without being able to say why.

  1. 1**The rule of three everywhere.** "Comfortable, versatile and timeless." Once is fine. Three times in four sentences is a rhythm no human writes by accident.
  2. 2**Elevation language.** Elevate, effortless, curated, essential, must-have. These words have been used so heavily that they now signal filler.
  3. 3**Claims with no source.** "Loved by thousands" and "our bestselling piece" are inventions unless they are true. On top of reading as filler, publishing invented social proof is unlawful in the UK.
  4. 4**Symmetrical paragraphs.** Three paragraphs of near-identical length is a generated shape. Vary it. Real writing is lumpy.

A structure that works

One sentence on what it is and who it is for. Two or three on the specification, in plain language. One on the decoration and how it will wear. One on care. Then the practical detail — sizing, delivery, what happens if it is wrong.

That is a description a person can act on, and it is also the structure search engines can parse into a rich result, because every claim maps to a property rather than a mood.

The honest limit

AI is genuinely good at turning your specification into readable prose, at producing forty variations for forty SKUs, and at maintaining a consistent voice across a catalogue. It is bad at knowing anything about your product that you did not tell it. If you do not know the fabric weight of the garment you are selling, no prompt will rescue the copy — ask your manufacturer, and put the real number in.

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FAQ

Quick Answers

Common questions about ecommerce — answered.

Not because they were AI-written. Search engines target unhelpful, duplicated content regardless of how it was produced. Generic copy that could describe any garment performs badly; specific copy built on real specifications performs well.

Fabric and weight, fit and cut, decoration method, care instructions, sizing guidance and delivery expectations. Those answer the questions that actually stop people buying clothing online.

Put specifications in the prompt rather than adjectives, then edit out the four tells: triples, elevation language, unsourced claims, and paragraphs of identical length.

Only if it is true and you can evidence it. Publishing invented reviews or fabricated popularity claims is unlawful in the UK under the Digital Markets, Competition and Consumers Act 2024, and it risks a search penalty on top.

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