Product content at scale
A store with two thousand products has two thousand descriptions, none of which anyone has time to improve. Generated from your specification data and edited, they can all be good.
It also fixes the duplicate-description problem that comes with using supplier copy, which has direct search consequences.
What to generate
- Descriptions from structured specification data
- Meta titles and descriptions per product
- Image alt text, reviewed before publishing
- Category page copy that is not thin
- Attribute extraction from supplier feeds into your filters
Attribute extraction is the underrated one. Filters that actually work drive conversion more than description quality does.
Support and returns
- Order status questions answered from live order data
- Returns eligibility checked against your policy and the order
- Product questions answered from specifications, not invented
- Sizing and compatibility questions, from your own data
All four are high volume and all four are currently answered by a person copying from an admin screen.
Be honest about personalisation
| Application | Traffic needed |
|---|---|
| Product content | Any |
| Support automation | Any |
| Search improvement | Moderate |
| Recommendations | High |
| Personalised pricing or ranking | Very high |
Recommendation engines need behavioural data at volume. Below that they perform worse than a well-curated manual selection.
Platform practicalities
Shopify has an excellent API and app ecosystem. WooCommerce has full database and REST access, which is more flexible and more your responsibility.
Either way, keep generated content in draft until reviewed. Publishing unreviewed product copy at scale is how stores acquire two thousand small errors.