E-commerce Product Listings With AI
Write accurate, clear product listings faster without inventing features
A taste of a lesson
AI described my cotton scarf as soft, breathable and eco friendly. Is that okay to publish?
Check each word against your facts. Soft is a fair, low risk description if customers agree. Breathable is reasonable for cotton but vague; say what it means, like light enough for spring. Eco friendly is the risky one: it is a claim you would need to back up, for example with certified organic cotton or a specific production detail, and green claims can be regulated. If you cannot prove it, cut it. Which facts do you actually have about how this scarf was made?
Written by the teacher as an example. In your lesson the tutor answers your own questions, and like any AI it can be wrong.
What you will be able to do
- Build a product data sheet that holds every fact a listing needs
- Write a reusable prompt that turns product data into titles, bullets and descriptions
- Catch invented claims and missing details with a checking step
- Write naturally for search without keyword stuffing
- Improve listings using returns and customer questions
Lesson plan
- 1 What buyers need from a listing Know which details help a buyer decide and reduce returns. Start
- 2 Building your product data sheet Create a spreadsheet of facts that every listing will be built from. Start
- 3 A prompt template that does not invent Write a reusable prompt that turns one row of data into a listing. Start
- 4 Titles, bullets and search words Write titles and bullets that read well and match what buyers search for. Start
- 5 Checking and risky claims Set up a review step that catches false or regulated claims before publishing. Start
- 6 Batch workflow and improving over time Run listings in batches and keep improving them from real feedback. Start
Try asking
About this tutor
For small online sellers on their own shop or a marketplace who have dozens or hundreds of products to describe. You will build a product data sheet, write a reusable prompt that turns that data into titles, bullet points and descriptions, and set up a checking step so nothing false slips through. The lessons cover what buyers need to decide (size, material, compatibility, care, what is in the box), how to write for search without stuffing, how to handle variants, and how to describe products honestly when AI tends to exaggerate. You also look at image alt text and returns data as a source of better descriptions. You finish with a small batch workflow you can repeat.
Reviews
4.3
3 ratingsSample
- Nadia F.Sample
I sell handmade jewellery and had 140 items with one line descriptions. The data sheet plus the MISSING rule stopped the AI inventing gemstones I do not use. Took a weekend to do the first batch.
- Oliver J.Sample
The returns lesson was the surprise. I added 'runs small' notes to three shoe listings and the questions dropped. Wish there had been more on marketplace specific rules, but it explained why it could not promise those.
- Mei L.Sample
Clear, practical, not flashy. My titles are much more readable now.
About the teacher
Practical AI for small businesses, founders and nonprofits with no time and a small budget
9 tutors 431 lessons taught Sample
I work with people who run small organisations: shop owners, solo operators, early founders and nonprofit teams. I have run small ventures myself and done the admin, the marketing and the customer emails at eleven at night, so I teach AI the way it actually fits into a crowded week. We start with the job you hate most, try one...
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