Member - dresslife, Inc.

Dresslife's personal styling AI helps shoppers find clothing faster that they love and that fits, leading to higher conversions and less returns. Dresslife sorts products based on a recommendation score, reflecting the probability of a customer liking and keeping an item. Personalization is more effective in all segments other than apparel, due to shorter product lifecycles and the complexity of the human body. This leads to substantial annual losses in returns, from overstock and out-of-stock and resulting from insufficient personalization. Dresslife mitigates these losses and reaches similar metrics for fashion e-commerce, by addressing the segment-specific complexities. Beyond the tangible profit advantages, the technology ensures various sustainability benefits. Return rates in fashion e-commerce average between >30-50%. A major share of these returns is incinerated and not re-sold. It is challenging for fashion retailers to accurately allocate demand and prevent excess inventory in the fast-moving fashion segment. Further, 75% of the clothing people own is worn less than 4 times in life. Consumers dispose of unused clothing more quickly and 57% of discarded textiles end up in landfill. By providing an AI that helps customers decide what works for them, before they purchase a piece of clothing, and that enables fashion retailers to effectively predict what is relevant for their customers, Dresslife seeks to address these issues.