Product descriptions that AI shopping assistants can actually use
AI assistants answer shoppers' questions from what your product data says — and say nothing when it's missing. Write descriptions that state who it's for, what's in it, how to use it and how it compares, in plain facts, and put the key specs in structured fields too. Never add a claim your product page doesn't back up.
Why descriptions decide AI answers
When someone asks "Is this serum OK for sensitive skin?" or "Does this vacuum have a local warranty?", the assistant looks for that fact in your product data. If your description only says "lightweight and powerful", there's nothing to quote, so it hedges or picks a product whose data does answer.
- Google: Shopping, AI Mode and Gemini read your Merchant Center data. Google also added conversational attributes for AI Mode, such as
question_and_answer(up to 30 Q&A pairs). - ChatGPT: shopping results come from product information ChatGPT finds, including structured data and product feeds.
Start from the questions shoppers ask
Before rewriting, list 5–10 questions a real customer asks before buying. They usually fall into the same groups:
| Question type | Example | What the data needs |
|---|---|---|
| Who it's for | Is it OK for sensitive skin? For a toddler? | Suitable / not suitable for |
| What's in it | What's the material? Does it contain fragrance? | Materials, ingredients, size, weight |
| How to use it | Can I machine-wash it? How long does it last? | Use, care and capacity facts |
| Compare | How is it different from the cheaper model? | What's upgraded, what's included |
| Trust | Warranty? Certified? Official stock? | Warranty, certifications, origin |
How to write each field
- Title (≤150 characters): brand + product type + the key attribute (size, model, variant). No "free shipping" or ALL CAPS.
- Description (≤5,000 characters, plain text): open with what it is and who it's for, then facts — materials, specs, use, care, what's in the box. One fact per sentence beats adjectives.
- Brand, category, size, color, material: fill the structured fields, not just the text. AI and filters read them directly.
- Product highlights: 2–100 short points (≤150 characters each) for the facts people decide on.
- Q&A (AI Mode): answer the real pre-purchase questions in
question_and_answer.
Only write what your product page or the manufacturer states. A spec AI repeats that turns out wrong costs more trust than a missing one.
Before and after
| Before | After | |
|---|---|---|
| Title | 【Hot Sale】Super Vacuum!! | Brand X5 Cordless Vacuum, 60-min Battery |
| Description | Powerful and light, perfect for your home. | Cordless stick vacuum for apartments and homes with pets. 1.4 kg, 60-minute battery, washable filter. Includes 3 heads and a wall mount. 2-year manufacturer warranty. |
| Question it can answer | — | Is it good for pet hair? How long does it run? Warranty? |
Check it the way AI would
- Ask ChatGPT or Gemini your list of shopper questions about the product.
- Note which answers are missing, vague or wrong.
- Add the missing facts to the description and structured fields, from your own sources.
- Re-check after Merchant Center has fetched the update.
AI Catalog automates this: it tests shopper questions against your whole catalog, shows which ones AI can't answer, and drafts fixes from your own product text for you to approve. Try it on your store.
Questions
How long should a product description be?
Google allows up to 5,000 characters of plain text. Length matters less than covering the facts shoppers ask about: who it's for, materials, specs, use and care.
Should I write descriptions for SEO keywords or for AI?
Write clear facts for people. Keyword stuffing doesn't help an assistant answer "is this right for me?"; specific, sourced details do.
Can I use AI to write product descriptions?
Yes, if every fact comes from your own product information and you review it. Invented specs are the main risk.
Where do AI shopping assistants read product data?
Google's AI Mode and Gemini read Merchant Center data; ChatGPT uses product information it finds, including structured data and feeds.