UNTUCKit, Cuyana, ThredUp Are Driving Retail's Digital Transformation


Last week I attended WWD’s Retail 20/20 event in New York City. Karla Gallardo, co-founder and CEO of Cuyana said something that really resonated with me, “Retail isn’t dying; our imagination is.” This struck a chord with me because it perfectly tees up the challenge many retailers and brands are facing today. While the imagination of these organizations may be dying, the imagination of the consumer is not. Retailers and brands need to find a way to catch-up, and emerging technologies are a big piece of the equation.

However, when you think of AI, predictive analytics and Big Data, most of the time you’re not thinking about small retailers and brands. But as many of the big retailers struggle to digitally transform their businesses, small and midsize (SMB) retailers are finding their moxie, particularly because they live in a world where avoiding even one misstep can have significant upside for their business.

According to a recently study by Oxford Economics, SMB retailers and brands are investing heavily in mobile and Big Data and adopting emerging technologies—such as machine learning, AI, augmented reality, blockchain and more. Sixty-two percent of SMB retailers surveyed said digital transformation is important or critically important to the company’s survival, particularly as they work to meet consumer demands for personalized experiences, predict consumer preferences and streamline the supply chain.  

AI in particular is growing in retail and is projected to reach $27.2 billion by 2025 — a 38-fold increase from 2016 according to a recent report by market research firm The Insight Partners.

While all retailers can benefit from new data-driven technologies, SMB retailers and brands have a distinct size advantage that makes them more agile and able to adapt faster. Since their executives are closer to the product, they are more directly connected to the value of technology investments. Further, SMBs encounter less bureaucracy at the management level which means that change can happen quickly and more easily. 

UNTUCKit is one example, as the company recently announced its plans to collect data on merchandise that is being tried on in-store to optimize its merchandising mix based on what people try on versus what they buy. This will enable the company to adjust inventory levels in real time based on shopper behavior, reducing inventory cost and allowing the retailer to redirect its investments toward more popular SKUs and new offerings.

Similarly, Everlane is taking actions to capture customer data and gain insight into browsing behavior and buying patterns. Even ThredUp, which has a much different model of selling one-of-a-kind second-hand clothing, is implementing data-driven solutions that point buyers to similar items to those that may not be available.  

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Joan Guzman