Supplier data usually contains the facts a listing needs, but in the wrong format, the wrong voice and with gaps. Rewriting it by hand is slow, and inconsistent attributes make products hard to find. These four steps let AI do the first draft from the supplier’s own facts while a merchandiser keeps the final say.
Step 1 — Fix the attribute list and style
Goal: Agree what every listing must contain.
- List the required attributes for each product category.
- Write a short style guide with two or three approved example listings.
- List claims that always need checking, such as safety, health or performance.
- Name the merchandiser who approves each category.
You finish with: An attribute list, a style guide and approvers by category.
Step 2 — Map supplier data
Goal: Turn supplier formats into your attributes.
- Collect sample files from your main suppliers.
- Map each supplier field to your attribute list.
- Flag missing or unclear values instead of guessing them.
- Keep a link from every attribute to its source file.
You finish with: A mapping per supplier with gaps flagged.
Step 3 — Draft and approve
Goal: Produce listings a merchandiser trusts.
- Draft titles, descriptions and attributes using only facts from the supplier data.
- Check flagged claims against the supplier’s documents.
- Have a merchandiser edit and approve each listing.
- Publish only approved listings.
You finish with: Approved listings with complete attributes.
Step 4 — Measure and refine
Goal: Show faster listing and fewer edits.
- Track time from supplier data to published listing.
- Track the share of drafts approved with light edits.
- Track listings with complete required attributes.
- Update the style guide and mappings from common edits.
You finish with: Measured results and a better style guide.
Common pitfalls
- Letting drafts add facts the supplier data does not contain.
- Publishing without merchandiser approval.
- Skipping checks on safety, health or performance claims.
- No source link, so nobody can verify an attribute later.