Etsy Titles, Descriptions and Tags That Actually Sell: My ChatGPT Workflow (Without Making Anything Up)
Etsy gives you three blocks of text to win a sale: a title, a description, and 13 tags. Most sellers I know write all three in the same sitting, in the same tired mood, and it shows — keyword-stuffed titles nobody would say out loud, descriptions that repeat the title, and tags that copy both. ChatGPT can draft all three in minutes. But there's a trap, and it's not the one people usually warn…
Etsy provides sellers with three blocks of text to persuade customers to make a purchase: a title, a description, and 13 tags. Many sellers write these elements in one go, but ChatGPT can generate these in minutes, but there is a trap. The trap is that an AI asked to write product copy will happily invent details about the product such as materials, dimensions, and burn times, which can lead to refunds, bad reviews, and policy strikes.
This tutorial explains a workflow to generate product copy swiftly without making up any facts. The process consists of three steps: creating a fact sheet, writing a title, a description, and finally, 13 tags. The first step involves writing a five-line fact sheet containing specific details about the product. The fact sheet is then used as input for the next steps.
The second step involves writing a title for the product that is no more than 140 characters long. The title should contain the strongest buyer search phrase and make sense on its own. The prompt for generating titles includes rules about the length of the title, the use of facts from the fact sheet, and avoiding repetition or ALL CAPS words.
The third step involves writing a description for the product that includes an opening, benefits, a clean spec list, and a "good to know" section. The prompt for generating the description includes rules about the structure, length, and honesty. The final step involves generating 13 tags that are no more than 55 characters long.
The tags should be unique and add new ground. The prompt for generating tags includes rules about length, uniqueness, and adding new information not already present in the fact sheet. Throughout the process, the AI writes words, but never invents facts. Any missing details are marked as "[ADD: detail needed]" in the output, which needs to be filled in by the user.
The final step involves reading the output aloud to ensure it sounds natural and does not contain any keyword salad.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.