Cross-sector · Merchandising
AI for catalogue and product content
Can AI write and translate our product data?
The challenge
Thousands of product records need descriptions, attributes and translations that nobody has capacity to write.
Prerequisites
- Clean supplier attribute feed
- A defined tone-of-voice reference
The approach
- Generate copy and structured attributes from supplier data and existing best-sellers
- Human review sampled by revenue contribution rather than uniformly
- Translate into target markets with a native reviewer on the top decile
- Measure against conversion and return rates, not word count
What makes it work
Review effort is concentrated where the revenue is, so quality control stays affordable.
What we would measure
Records enriched
Per week, at review standard
Conversion
On enriched versus control records
Return rate
Where description accuracy is the driver
Risk position — Limited risk. Synthetic content identifiable where required.
Baselines are established in your business during the assessment. We publish no borrowed benchmark numbers.
Assess this for our businessRelated use-cases