Home · Business · Marketing & Content · Paid ads

YES

As of 13 August 2026, AI can write Google Shopping product descriptions.

This still needs a person who signs their name to it.

Can you do it?

5 minutesto a draft.

30 minutesto something you’d act on.

Cost, all in£0

Skill neededchat-fluent

Who has to check ityou

What the alternative costsHypotenuse AI is a purpose-built product-description and ecommerce-content tool, but no price is provided here for a human copywriting alternative.

If this goes wrong: unsupported or poorly matched claims enter your feed, and listings may be rejected or attract the wrong customers.

What to actually do

  1. Hand it to a person

    The route this page recommends

    A person who owns the outcome does this end to end, worth it when the failure is dear.

  2. Use a tool built for this

    Second choice
  3. Do it yourself

    The distant third

    A chat interface, chat-fluent skill, and roughly 30 minutes until you can act on the result.

    How to actually do it

    1. Open your product catalogue or feed export and gather each product ID, name, category, specifications, materials, dimensions, approved claims, variant details and intended use.
    2. Open your brand guidance and current Google Merchant Centre feed rules, then note the required character limit, prohibited claims, spelling preferences and tone.
    3. Paste the catalogue data, brand guidance and rules into the prompt, replacing the bracketed fields with your actual requirements.
    4. Ask the model to produce the table and separate factual claims from missing information instead of filling gaps.
    5. Compare every drafted description and claim against the current product catalogue, technical documents, packaging and approved claims list.
    6. Remove any unsupported wording, resolve every NEEDS MORE DATA item, and ask the model to revise only the affected descriptions.
    7. Export the checked descriptions into your feed, run your normal Merchant Centre diagnostics, and publish only after resolving feed errors or policy warnings.

    Prompt

    Write Google Shopping product descriptions from the catalogue data below.
    
    Use only facts stated in the data. Do not invent materials, dimensions, performance, certifications, delivery promises, discounts, stock information or customer benefits. Do not make medical, environmental or comparative claims unless they are explicitly supported by the supplied data. Keep the language clear, specific and suitable for a UK retailer. Avoid hype, keyword stuffing, repeated product names and calls to action. Preserve the product's intended use and important distinctions between variants.
    
    For each product, return a table with these columns: product ID, drafted description, factual claims used, missing information to confirm, and any wording that may need a policy or legal check. If a product lacks enough information for a reliable description, write "NEEDS MORE DATA" rather than guessing. Keep each description within [INSERT YOUR REQUIRED CHARACTER LIMIT] characters. Match this brand tone: [INSERT BRAND TONE]. Apply these additional catalogue rules: [INSERT BRAND OR CATEGORY RULES].
    
    Catalogue data:
    [PASTE PRODUCT DATA HERE]

    Open it prefilled in ChatGPT or Claude, or copy it into Gemini, which takes no prefill link.

What it gets wrong

  • AI cannot know whether a product claim has been approved by your legal, compliance or merchandising team.
  • AI cannot reliably infer the commercial priority between variants, customer groups and profit margins unless you state it.
  • AI can produce descriptions that are factually correct but bland, repetitive or unlike the brand.
  • AI cannot take responsibility for rejected listings, misleading claims or the commercial effect of publishing the feed.
  • Checking a large catalogue line by line remains human work, especially where specifications or claims are ambiguous.

Even on a YES, the friction has a name: judgement under ambiguity, verification cost and stakes of error.

How we scored this

Five axes, each scored nought to two by hand: ten means AI carries the task cleanly, and the thresholds that turn a total into YES, PARTLY or NO are published in the methodology. Each axis name links to its definition.

AxisScore (0–2)
Output2
Inputs2
Verification1
Liability1
Effort delta2
Total8 / 10

FAQ

Can ChatGPT write Google Shopping product descriptions?
Yes. Give it structured product facts and strict instructions not to invent claims, and it can draft descriptions in a consistent format. You still need to compare every claim with your current catalogue and check the finished feed.
How do I use AI to write product descriptions for Google Shopping?
Provide the product data, brand rules, required character limit and approved claims, then ask for a description plus a list of missing information and claims to check. Revise the flagged lines and run the completed feed through your usual Merchant Centre diagnostics before publishing.
Will AI-generated Google Shopping descriptions get approved?
There is no guarantee. Approval depends on the accuracy of the product data, your claims, the feed and current Google requirements, so check warnings and rejected items in Merchant Centre rather than trusting the draft.
Is it safe to use AI for ecommerce product descriptions?
It is suitable for drafting when the model is restricted to verified product information. The risk is publishing an invented specification, unsupported benefit or misleading comparison, so a person must check the text against the source data.

Nearby answers

Assessed by gpt-5.6-luna (gpt-5.6-luna) on 2026-08-13, second-checked by an independent model. Wrong somewhere? Email [email protected] and it gets re-checked.

The newsletter

AI news, new answers and product picks, straight to your inbox.