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Variant-Level Image Editing Support for a Fashion Marketplace Seller
Service:
Image Editing & Catalog Image Standardization
Engagement Type:
Monthly Retainer
Client Type:
Fashion & Lifestyle Marketplace Seller
Geography:
United States
Hiring Focus:
1,400 SKUs
Demand Pattern:
5–8 images per SKU (variant-heavy catalog)
Client Background
The client is a UK-based fashion and lifestyle seller operating across:
- A proprietary marketplace platform
- Third-party retail marketplaces
Key operating characteristics:
- High SKU and variant volume (size, color, style)
- Frequent seasonal launches and refreshes
- Strong emphasis on visual consistency across variants
- Lean internal merchandising and operations team
Image editing was handled inconsistently across vendors and freelancers, leading to quality drift.
The Challenge
As the catalog expanded, the client faced variant-level image consistency and scalability challenges, including:
- Inconsistent lighting and color tones across product variants
- Misaligned cropping and framing between sizes and colors
- High revision cycles due to subjective editing standards
- Slow turnaround during seasonal collection launches
- Difficulty enforcing uniform visual guidelines across contributors
These issues resulted in:
- Poor visual consistency on category pages
- Increased internal QA effort
- Delays in publishing seasonal collections
- Reduced customer confidence during browsing
Objectives
The client needed a centralized image editing partner who could:
- Enforce strict visual consistency across variants
- Handle large batch volumes during seasonal peaks
- Reduce revision cycles
- Improve speed-to-market for new collections
- Operate within clear, repeatable editing standards
Our Engagement Model
Outsure Global was engaged on a monthly retainer, providing dedicated image editing capacity aligned to the client’s seasonal and ongoing catalog needs.
The engagement focused on:
- Variant-level standardization
- High-volume batch execution
- Predictable delivery timelines
Our Approach
Variant Image Audit & Baseline Definition
We conducted:
- Review of existing product images across categories
- Identification of inconsistencies in lighting, color balance, and framing
- Comparison of variant sets within the same product group
Deliverables:
- Variant-level image style guide
- Cropping and framing reference templates
- Color and exposure benchmarks
Editing SOPs for Fashion Catalogs
We defined SOPs specifically for fashion products, covering:
- Neutral background consistency
- Fabric texture preservation
- Color accuracy across variants
- Shadow placement and depth consistency
This reduced subjectivity and ensured repeatable results.
Production-Scale Image Editing
Execution included:
- Background cleanup and replacement
- Fabric wrinkle and dust removal
- Color correction to ensure variant accuracy
- Consistent cropping and alignment across variants
- Subtle shadow and depth enhancement
Tools used:
- Adobe Photoshop
- Adobe Lightroom
- Camera RAW processing
- Batch actions and presets
Variant Consistency Checks
Special focus was placed on:
- Side-by-side variant comparison
- Color consistency across size and color options
- Framing alignment across all images of a product
This significantly reduced downstream revision requests.
QA & Structured Delivery
QA process included:
- SOP-based visual checklist
- Cross-variant comparison reviews
- Randomized spot checks across batches
Delivery
- Product- and variant-wise folder structure
- Naming conventions aligned to SKU and variant IDs
- Platform-ready image sets
Scope of Work
- Fashion product image editing
- Variant-level consistency management
- Background cleanup and retouching
- Color correction and exposure balancing
- Cropping and resizing
- Bulk seasonal batch processing
Results Achieved (First 60–90 Days)
- Improved visual consistency across variants
- Reduced revision cycles during seasonal launches
- Faster turnaround for new collections
- Lower internal QA workload
The agency was able to:
- Launch seasonal catalogs on schedule
- Maintain brand consistency across platforms
- Scale image operations without additional internal resources
