Blog — Retail
If you sell products online or manage listings across multiple platforms, you know the grind: every item needs its own description, and writing dozens (or hundreds) of them well takes real time most small retailers don't have. Here's how to use AI to write descriptions that actually help sell the product, not just fill space.
Why Generic Descriptions Underperform
A description that just restates the product name and category ("Comfortable cotton t-shirt, great for everyday wear") doesn't give a customer any reason to choose your listing over a nearly identical one elsewhere. Specific, sensory, and practical detail is what actually influences a purchase decision.
What to Feed the AI for a Better Result
- Real material/construction details — fabric weight, finish, specific dimensions
- What makes this item different from similar products you or competitors sell
- Who it's ideal for — a specific use case or customer type
- Your brand's tone — playful, minimal, premium, practical
A Prompt Template for Product Descriptions
Something like: "Write a product description for [product name]. Details: [materials, dimensions, key features]. This is ideal for [specific use case/customer]. What makes it different: [1-2 unique points]. Tone: [your brand voice]. Keep it under 100 words, avoid generic phrases like 'perfect for any occasion.'" Naming the phrases to avoid pushes toward something more specific and useful.
Scaling Beyond a Handful of Products
This manual, one-at-a-time approach works well for a small catalog. Once you're managing hundreds of SKUs across multiple platforms, the practical fix is a system that pulls from your actual product data (specs, categories, existing photos) and generates descriptions in bulk — built around your specific catalog structure, not a generic template.
Frequently Asked Questions
Will AI-written product descriptions hurt my SEO?
Not inherently — what matters to search engines is whether the content is genuinely useful and not duplicated across many sites, not whether AI assisted in writing it. Avoid publishing generic, unedited output at scale; specific, accurate descriptions perform fine.
How much product detail do I need to provide?
More than you'd think — materials, dimensions, what makes this specific item different from similar ones, and who it's ideal for. Thin input produces thin, generic output.
Can this work for hundreds of products at once?
For a handful of products, doing this manually works fine. At real scale (hundreds of SKUs), a bulk, semi-automated process built around your actual product data is far more practical — see the note at the end.
Should every product get a unique description?
Ideally yes, especially for anything you want to rank in search or that customers might compare across retailers. Duplicate or templated descriptions rank and convert worse than specific ones.
Managing a large catalog? Let's talk about automating this properly.
