Exploring User Behaviour on Etsy through Dominant Colors

The online realm has become a driving force in the retail marketplace. E-Commerce websites can provide a level of diversity and uniqueness that is impossible in the world of brick-and-mortar retail. Etsy is an online marketplace1 for artisans selling unique handcrafted goods, and vintage wares that couldn´t be found elsewhere. Etsy caters to the long tail of online retail [1]. Intuitively, online retail is a visual experience-shoppers have particular styles that they find appealing, often images are used as first order information when making shopping decisions. There are a variety of signals extracted from the images representing those items for sale by shoppers. Amongst these, color composition is an important cue for visual search and image ranking-often shoppers have a palette of favorite colors, or a mental image of what they´re looking for, partially determined by color. In this paper, we introduce a novel dataset for user behaviour prediction. We address the problem of inferring dominant color composition from the pixel-level color distribution of listed images on Etsy. We explore the dominant colors of favorited listings and investigate the entropy of colors distribution among Etsy users.