Bottle or jar
Scenes: studio background, lifestyle surface, paid social crop
Failure risk: label drift, reflection drift, cap or lid deformation
Benchmark before comparison
AI product photography benchmark template for ecommerce.
Run a small product truth test before claiming an AI product photography tool is good enough for store, marketplace, landing page, or ad use.
Direct answer: A useful AI product photography benchmark tests multiple product categories, multiple scene types, and product truth failures, then records publish, repair, or reject decisions.
Test matrix
Test five product categories across three scene types.
Box or pouch
Scenes: marketplace image, seasonal background, landing page hero
Failure risk: package geometry, typography, fake badges
Transparent or glossy product
Scenes: white background, dark surface, shelf-style scene
Failure risk: transparency, material finish, contact shadow
Apparel or soft goods
Scenes: flat lay, model-free lifestyle, ad variant
Failure risk: fabric texture, scale, color and pattern drift
Accessory or small object
Scenes: macro crop, bundle image, comparison layout
Failure risk: scale, edges, missing parts, invented accessories
Scoring
Score product truth before judging visual quality.
Pretty outputs are not enough. Each image receives a product truth score before the team decides whether the output can be used commercially.
Identity and variant preserved
Label, logo, and claim text preserved
Material and color truth preserved
Geometry, scale, shadow, and contact points believable
No unsupported badges, discounts, ratings, endorsements, or platform logos
Benchmark decision rules
18-20: publish after final channel review
14-17: repair failed details before publishing
0-13: reject or regenerate with narrower edit scope