Resources · Guide
How to enrich product descriptions with AI
Enriching product descriptions with AI means automatically generating descriptions, attributes, translations, and SEO from the raw data in your catalog. You import the products, the AI writes copy in your brand voice, fills missing attributes, translates into every language, and optimizes for search, across thousands of products, in hours instead of weeks.
Why product pages matter
The product page is where a visitor decides to buy and where Google decides whether to show you. Thin descriptions, missing attributes, and no translations cost you sales and visibility. But writing them well by hand, across thousands of SKUs and several languages, doesn't scale. This is exactly where AI earns its place.
What the AI generates
- Descriptions in your brand voice, not generic copy.
- Missing attributes (material, fit, dimensions) inferred from the data you already have.
- Translations into every language of your markets.
- SEO: titles, meta, and copy optimized for search.
How it works, step by step
The flow is simpler than it sounds:
- Import your catalog from Shopify (or a file): the AI reads the raw data you already have.
- Set your brand voice and rules: tone, words to avoid, required attributes.
- The AI generates descriptions, attributes, translations, and SEO in bulk, across every product.
- You review and approve: nothing goes live without your sign-off.
- Publish to Shopify, and every change stays in sync.
SEO and GEO: two ways of being found
For years, optimising a product page meant one thing: getting found on Google. There are two surfaces now, and they reward different things. Google reads a title and a description and decides whether to put you in a list. An engine that answers, like ChatGPT, Perplexity or Google's AI answers, does not make a list: it builds an answer and cites the sources it finds complete enough to quote.
GEO stands for Generative Engine Optimization: optimising for the engines that answer rather than the ones that list. It is not a second job on top of SEO. It is the same page, written better.
What changes in practice on a product page:
- Structured data matters more than prose. Measurements, materials, compatibility, lead times, what is included. An engine quotes what it finds stated plainly, and an empty field never gets quoted by anyone.
- The real questions. A page that answers the questions your support team gets every day is the page an engine reaches for when somebody asks those same questions.
- The comparison. "What is the difference between this and that" is a question for an answer engine, not for a list of links. If the page does not contain the comparison, there is nothing to quote.
- The language of the market, not a translation. A translated page repeats an Italian page in German words, and it shows.
Then there is the economics, which decides whether the work happens at all. The top hundred products were already fixed by hand, and they are also the part that already ranks. The rest of the catalogue only gets written if the cost per product is close to zero. That is where the unclaimed demand is, and it is why bulk enrichment changes the outcome and rewriting by hand does not.
Mistakes to avoid
Three common traps: generating without a defined brand voice (you get flat, everyone-sounds-the-same copy), publishing without review (AI is fast, not infallible), and enriching only one language while forgetting your export markets. With an AI that sees the whole catalog these risks shrink, because every page inherits consistency from all the others.