As of this summer, the fashion retailer is using machine learning to ensure it has the right stock, in the right place, at the right time. Techerati talked to eCommerce Expo speaker Simon Calvert about his role in helping the retailer intelligently pre-empt markdown
It has been a disruptive start to the century for traditional retailers as they grapple with the shift towards online shopping together with economic ups and downs that have made consumer habits unpredictable. Retailers have adapted by spreading business across multiple channels – incorporating offline brick-and-mortar stores and mobile apps and e-commerce sites – and of course, embracing new tech trends.
During this digital transition, data has been an invaluable tool to help retailers make better decisions and learn more about customers, enabling them to keep up with fast-moving currents with agility and speed. Although retailers have been buoyed by technology, the commercial focus remains the same, says Simon Calvert, former trading director at Bonmarché.
“The channel you’re selling on might have changed and continues to do so, and the possibilities may have become bigger in terms of what you can do and how you can learn in order to satisfy the customer. But at the end of the day, it’s still a customer-driven business,” Simon said.
“I got a phrase I borrowed off a knowledgeable, well-connected friend in retail: The traditions of retail may be dead but traditional retailing is alive and well,” he said.
Across the board, machine learning has breathed new life into long-standing industries. Retailers are no exception. Numerous household names are using algorithms to make accurate predictions about the future, enabling actionable business insights and innovations in marketing strategy, customer relationships and operations.
While other retailers were distracted by how the technology could be used to understand customers, Calvert saw the potential for machine learning to assist in allocation decisions.
“Using data to understand what customers want is great and machine learning can be used to make those decisions better,” he said. “But since putting the right stock, in the right place, at the right time is still as important to traditional retailing as it ever was. I thought maybe we should be using that technology in a more effective way to make those decisions.”
For middle to lower middle-market retailers, markdown is the single biggest cost to business – making effective stock replenishment and allocation vital. When stores are overstocked, not only are retailers forced to discount, but it means there are stores elsewhere that are understocked – transporting stock to another branch in order to sell it more effectively is costly and complex.