Fashion tech startup helps retailers brace for record sales of £28bn this Christmas
In the wake of recent retail closures across the UK, fashion technology startups are delivering much-needed innovation to help merchants maximise online sales and optimise unprecedented digital demand this Christmas. Retail data platform uSizy, is among the emerging startups poised to help UK retailers leverage technology to cope with record sales expected to reach £28bn, by first tackling archaic sizing guides.
uSizy entered the complex eCommerce space in 2016 with the goal of revolutionising traditional size guides. Four years on, with a growing database of over 400 global brands and 200 eCommerce partnerships, the startup has built technology that requires just 2 lines of code and a product feed to integrate, streamlining the entire workflow process across sizing, stock, pricing, and logistics to transform the heart of retail.
As UK retailers prepare for record online demand, uSizy warns of the unseen but inevitable expenses caused by outdated sizing guides and generous return policies, the latter of which has become an industry norm. According to uSizy data, clothing will account for 75% and footwear for 25% of online Christmas returns, with sizing errors cited as the main culprit. By tackling size issues with custom sizing technology, such as the uSizy Size Adviser, online retailers with an average of 1 million monthly sessions can generate an additional £150,000 in net sales, not to mention the additional savings gained from significant reductions in costly returns.
"Presenting the right sizes to users with the Size Adviser, a machine learning technology, is increasing overall conversion rates by 25% and reducing returns rate by 29% on average for over 400 online brands,” explained Iñaki García, CEO and Founder of uSizy.
In 2018, up to £71bn worth of goods were returned post-holiday worldwide, and with the mammoth consumer shift to online shopping in 2020, uSizy forecasts losses to reach record highs for sellers lacking the technology to predict, prevent and optimise their returns. Amid a thinning retail landscape, the remaining key players will be those ready to embrace the digital solutions that are reshaping the future of retail with a 'user-first' approach.
Customised solutions not only capture data points for retailers to understand the current demand of their customers in terms of fit, but remove user hesitation and establish trust while eradicating the costs, frustrations and inefficiencies caused by sizing. Existing sizing guides fail to consider many aspects of the user experience, perhaps most blatantly, that shoppers often don’t know their own measurements. Amid the progress made in refining online shopping experiences, it seems obsolete that traditional size guides remain commonplace when retailers risk losing their customers at the most critical point in the online shopping process: size selection.
“Our Size Adviser increases overall conversion by 25% on average, and when compared directly with size guides, the increase in conversion is 300%. By addressing customers with a bespoke, personalised size recommender, online retailers can boost repeat sales by 10% to reinforce customer loyalty,” continued García. “With increased confidence in the purchasing process, the buying decision time of users also decreases by 20% and the average cart size increases by 10%. These are game-changing improvements as the eCommerce landscape becomes increasingly competitive.”
Through multi-brand and single-brand eCommerce selling to consumers in over 200 countries, uSizy serves top global fashion, footwear and sportswear companies along with UK brands including Dr.Martens, Fitflop, Sigma Sports, Mountain Warehouse, UK Soccer Shop, Wildcountry, Zone 3, Craghoppers, Beulah, Hi-Tec and Huub. Following unprecedented consumer demand and at the request of its cycling clients, the startup has this year launched the Size Adviser for bikes, enabling users to purchase the right size bike model based on recreational versus competitive cycling and other user preferences.