A consumer-centric landscape where consumers shop whenever, wherever and however they want is forcing traditional retailers to evolve. It’s a painful process that involves massive store closures and investments in technology to meet these new demands.
Meanwhile, brands are stepping up efforts to sell directly to the consumer — online and with physical stores.
When it comes to deploying technology, the footwear industry is, in many ways, far ahead of the fashion apparel and accessories segments — from 3-D printing to advanced automation in the supply chain.
But on the retail end of the business, the challenges include millennial shoppers, who change brand loyalty in a flash, a desire for a seam-less shopping experience (online and in stores) and an overall lack of product knowledge and service in department, mass and specialty stores.
The good news is that the industry is seeing a commercialization of technologies from machine learning and artificial intelligence to virtual and augmented reality that is redefining customer engagement via personalization and a shopping experience that consumers describe as “delightful.”
And while companies such as Nike, Adidas and Under Armour are leading the way by deploying these technologies, the commercialization and availability of these solutions is accessible to smaller niche brands and specialty footwear retailers as well.
In a recent blog post, Pehr Luedtke, SVP of business development for Valassis Digital, noted that artificial intelligence is increasingly being integrated into a variety of business settings. And in retail, AI-powered chatbots are a cost-effective way to eliminate redundancies and “cut down on many of the more menial tasks,” Luedtke stated.
But the real gem is using AI to improve the “consumer-business” relationship. “It might sound unusual, but chatbots can help drive purchases in-store — even for big-ticket items like a car,” he wrote in a column in sister publication WWD. “One might envision chatbots are best suited for small purchases or help desks, but with a well-organized strategy — including the integration of chatbot data into existing CRM systems — marketers can gain a broader, more robust profile of their core audiences. They can then use that data to create a more relevant, personalized customer experience that drives shoppers into a retail location.”
It’s important to note that when it comes to deploying technology — whether it is AI or a cloud-based e-commerce platform — there’s no single plug-and-play solution. Machine learning works hand in hand with CRM and e-commerce platforms.
Moreover, as AI and machine learning embed themselves into the footwear industry, the merchant and creative aspects of the market will not be replaced by robots and chatbots. Instead, these technologies will free up time by eliminating redundancies and allowing designers and merchants to do what they do best: create compelling products and an elevated shopping experience.
That was the theme of a recent panel discussion with Accenture and the Council of Fashion Designers of America Inc. The panelists included Vijay Subramanian, chief analytics officer at Rent the Runway; Marleen Vogelaar, founder and CEO of on-demand fashion brand Ziel; Ali Dalloul, GM of Ambient Intelligence at Microsoft; David Simchi-Levi, professor of engineering systems at MIT and chairman of Opalytics; Shyam Thyagaraj, managing director of Accenture’s technology advisory practice; and Courtney Spitz, managing director in the global retail consulting practice at Accenture.
The panelists said there’s no “silver bullet” technology that will transform a retailer or brand in this new age of retailing. Instead, they said companies should see AI as part of a larger ecosystem of technologies aimed at building a label’s overall capabilities. Retailers need to start slow and develop a strategy. They need to identify where automation can be deployed and then start investing.
And once the automation begins to generate savings, that money should be reinvested into additional AI technologies.
Spitz and Thyagaraj said in a report presented prior to the panel that the retail market has “left merchants frustrated with their jobs and feeling overwhelmed at time when retailers need them to be at their most innovative and inspired. But it does not have to be this way. By adopting a new model, we can shed the routine, math-intensive aspects of the merchants’ job and empower them to do more creative strategic work that can have a bigger impact on the consumer and ultimately the retailer.”
The anchors of the new model include using data and AI to create a “hyperlocalized and hyperpersonalized” experience for consumers. Simchi-Levi told FN that this new model is achievable, as brands and retailers have the capacity to generate the right kind of data, which can also be used for price point optimization.
Other goals include increasing conversions while building brand loyalty, which is why using AI to increase the level of personalization is so important.
For example, Snap+Style Business offers retailers and brands “discovery platforms” where consumers submit personalized styling requests via a widget and the companies respond by email with customized product selections based on the buyer’s needs. It’s a personal-shopper model that can increase sale conversion rates by 30 percent.
Raul Fernandez, chairman of Snap+Style Business, said his firm’s business product suite “allows consumers to visually discuss and dis-cover merchandise directly with sales associates or stylists. That meaningful and easy exchange leads to an experience that has increased average order value, units per transaction and lifetime customer value.”
Another element of building brand loyalty and increasing lifetime customer value is using content along with data. In a research report from Adobe, the authors noted that the “key to deepening brand loyalty is recognizing that content is most valuable if it’s personally relevant. It needs to reach the right individual at the right point in time and in the right context. That means you have to get good at understanding each customer.”
Adobe said one way to do this is by flattening the data and building a single profile view of the consumer “so you recognize each customer whenever they find you.” That requires gathering data from each point of interaction with the consumer to build a “centralized profile,” the researcher said.
“This kind of centralized information allows you to deliver personalized content based on their last interaction with you and potentially shorten the steps in their journey,” the authors said.
“Was the customer just searching for size 10 running shoes on his phone? Did he log a 20-mile run last week in his running app? With this kind of user information, you’re able to deliver highly targeted information to consider next time he knocks on your door — perhaps about a brand-new shoe specifically designed for long-distance runs.”
Adobe noted that a 360-degree view of each customer allows brands and retailers “to take your customer data to the next level and create content that’s more consistent, personal and memorable throughout the customer journey.”