AI USE CASE
Virtual Try-On for Fashion Retail
Let shoppers visualise clothing and accessories on themselves before buying, reducing returns.
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Run the diagnostic →What it is
Computer vision and generative AI overlay garments, accessories, or makeup onto a live or uploaded customer image in real time. Retailers typically see return rates drop by 20-35% and conversion rates lift by 10-25% for try-on-enabled products. Implementation requires a mobile-ready camera interface and a well-tagged product catalogue with high-quality imagery. The experience can be embedded in an existing e-commerce storefront or delivered as a standalone app module.
Data you need
High-quality, standardised product images (multiple angles, transparent backgrounds) and a tagged product catalogue with size/colour metadata.
Required systems
- ecommerce platform
Why it works
- Invest upfront in a standardised photo production process that captures products at the angles and resolutions the AI model requires.
- Start with a high-traffic, high-return-rate product category (e.g. eyewear or tops) to demonstrate ROI quickly.
- Provide a clear, frictionless permissions flow and a transparent privacy policy to build camera trust.
- Partner with a vendor that offers SDK-level integration so the experience matches existing brand design guidelines.
How this goes wrong
- Poor product image quality or inconsistent angles make virtual overlays look unrealistic and damage brand perception.
- High mobile latency or limited device compatibility leads to low adoption and negative user feedback.
- Incomplete product catalogue coverage means only a fraction of the range benefits, limiting ROI.
- Privacy concerns around camera access reduce customer willingness to engage with the feature.
When NOT to do this
Do not launch virtual try-on if your product catalogue lacks consistent, high-resolution imagery, the AI output will look unconvincing and erode customer trust faster than no feature at all.
Vendors to consider
Sources
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