Image QA Checklist for Marketing Teams
When to use this checklist
Use this page when a team member has produced an image with Pixelto and the asset is about to move into an ad account, landing page, PDP, social calendar, email campaign, or sales deck.
The objective is not to make every image look "perfect." The objective is to catch the most common production failures before a visual reaches customers.
Review in four passes
Pass 1: Factual integrity
Ask whether the image still represents reality closely enough for the channel.
- Products: color, material, silhouette, and logo placement still match the real item.
- Real estate: room layout, windows, doors, permanent fixtures, and dimensions are not altered.
- Food and menu photography: portion size and ingredients are not materially misrepresented.
- Portraits: identity, facial geometry, and contextual meaning are still accurate.
If the answer is no, reject the asset immediately. Cosmetic improvements are acceptable; deceptive changes are not.
Pass 2: Visual quality
Look for the failures AI systems introduce most often:
- warped fingers, limbs, utensils, or furniture edges
- duplicated objects in the background
- mismatched shadow direction
- texture smearing on hair, fabric, or product surfaces
- edge halos around masked objects
- unreadable or accidental text artifacts
Zoom in on the highest-risk zones instead of only reviewing the full-frame thumbnail.
Pass 3: Placement fitness
The same asset may pass visually but still fail its placement.
Check:
- safe space for headline or UI overlays
- crop resilience across target ratios
- mobile readability at small preview sizes
- background contrast behind UI or copy
- whether the focal subject still reads clearly after export compression
An image that only works at one size usually creates rework later.
Pass 4: Rights and policy
Before approval, confirm:
- the team owns or is licensed to edit the source image
- the prompt did not request restricted content
- the final asset does not create misleading claims
- the output channel allows the kind of edit you made
If any reviewer is unsure, route the asset to manual review instead of guessing.
Channel-specific checks
Paid ads
- Claims are still supportable.
- No fake discount labels, badges, or product certifications are introduced.
- Negative space exists for final ad copy.
- Variant naming is consistent for later performance analysis.
Product detail pages
- The product shape is unchanged.
- Packaging text is still accurate.
- Reflection, gloss, and material cues remain believable.
- The hero image still matches supporting gallery images.
Social media covers and thumbnails
- Subject identity remains stable after expansion or cropping.
- Background additions do not introduce unrelated or misleading objects.
- The composition is still readable at mobile preview size.
Restoration and archival projects
- Historical details are preserved where accuracy matters.
- Colorization decisions are plausible and documented.
- The restored version is stored separately from the archival master.
Approval workflow recommendation
Keep the workflow simple:
- Creator exports 3 to 4 variants at draft quality.
- Reviewer rejects obvious failures and keeps at most 2 candidates.
- Reviewer applies this checklist to the remaining candidates.
- Final asset is exported once, with prompt and source metadata stored together.
This keeps review cost low while preserving accountability.
Reject reasons worth standardizing
Teams move faster when they reuse the same reject labels. A basic set is enough:
factual-driftartifact-or-smearbad-cropunsafe-or-restrictedrights-unclearneeds-manual-retouch
These labels help later when you review where AI output is consistently failing.