PROPOSED PROJECT
Product Shade Image Check
Catch the wrong lipstick, foundation, or other shade image on a product page. Compare product codes, visible labels, and approved photos before launch.
The Clay image is attached to the Berry product page. Check and correct the link before launch.
A good image can
show the wrong product.
A 24-shade lipstick launch includes Clay / LIP-08 and Berry / LIP-14. The approved Clay file, clay_08_v3, is attached to the Berry product page record. The audit should expose the identity conflict and prepare a correction for specialist review before release.
WHAT IS USUALLY DONE
A file library can check names and find duplicates. Someone still needs to check whether each image shows the product on the page where it will appear. Renaming the wrong image can make it look correct to a filename check.
WHAT SOVRUN CAN DO FOR YOU
Sovrun would check the images for one makeup range against the approved list of shades. The tool reads visible labels, compares reference photos, and checks product codes and file history. Reviewers see conflicting information side by side. Approved corrections become a file listing which image belongs on each product page.
See which image
belongs to each product.
Show the original image, correct shade, current product page, and suggested correction together. Reviewers need more than a filename to approve the change.
Approved product: LIP-08
Berry product page
Pending specialist approval
The right images,
ready for your store.
Your team receives confirmed image corrections, questions that still need checking, and a file listing the approved image for each product.
Check product list + photos
clay_08_v3
Reviewer sign-off required before import.
Needs an approved reference photo.
- Issue
- Visual color question
- Owner
- Product specialist
- Automatic change
- Blocked
How we’d make it happen.
Establish references
Join the approved register to source assets and identify which product page each export is intended for.
Find conflicts
Compare visible labels, reference similarity, and current attachments; present the evidence for each candidate mismatch.
Approve the changes
Export confirmed image assignments and retain unresolved identity or color questions in a separate release report.
Where AI helps
We compare AI tools that read labels and match images using your actual product photos, including very similar shades. A visual match is one clue; product codes and original files provide separate checks.
What people approve
A product specialist approves changes and checks unclear labels. Questions about the actual shade need photos taken under controlled lighting; screen colors alone cannot prove an exact color match.
What we’d need to start
- Approved list of shades and product codes
- Approved product photos and their earlier versions
- List of images attached to product pages and used in campaigns
How we’d test it
Test known swaps, renamed duplicates, correct mappings, and unreadable labels separately. Measure missed conflicts and false flags before expanding the collection.
Prepared for Beauty & personal care. We would agree on the work after reviewing your brief, materials, and requirements.
This is a proposed project, not completed client work. The visuals and numbers show example outputs, not measured results.
