One of the key challenges for fashion brands before running ads is identifying which visuals are most likely to drive actual performance.
Traditional photo shoots are costly and time-consuming, making it difficult to experiment with multiple moods and contexts.
In this article, we highlight the case of the GGPX Loose-Fit Knit, using LaonGEN Fashion AI to generate pre-ad test cuts.
The process demonstrates how brands can evaluate conversion potential without a physical shoot, while gaining clear operational advantages in speed, cost, and scalability.
1) Objective & Context
We generated pre-ad “test cuts” with LaonGEN Fashion AI—without a studio shoot—and selected the most promising mood for conversion. We keep the information value of the original lookbook/editorial while optimizing scenes for ad contexts.
2) Task Definition
- Preserve silhouette/texture (brand consistency)
- Compare lifestyle scenes (café/street) vs. toned-down studio lighting
- Validate CTR, dwell time and add-to-cart via A/B/C sets
3) LaonGEN Workflow
- Garment onboarding (~1 hour)
- Generation (~2 minutes per cut) across multiple moods
- Ad formatting: thumbnails, copy overlays, price tags
- Metrics review: compare A/B/C and lock the best mood
LaonGEN minimizes garment distortion and varies only the mood for consistency.
4) Operational Gains
- Lead time: 20–30 alternative visuals in a day
- Cost: 80–90% lower than studio; reinvest in targeting and A/B tests
- Consistency & scalability across campaigns, product pages and social
5) Practical Notes
- High-CTR lookbook moods often transfer well to ads
- Repeat keywords (GGPX, loose-fit knit, LaonGEN, Fashion AI) in captions/alt text
- Keep at least three test sets (A/B/C) and log failures
For more cases and a free trial, visit the LaonGEN website.
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