At this point, retailers are well versed on the need to amass consumer data but few are realizing its full potential. By using data to enhance the entire shopping experience, stores can provide products and promotions that are relevant and therefore more engaging.
“Most retailers today are sitting on a goldmine of data, but it isn’t valuable the way they look at it,” said Raj Badarinath, vice president of marketing and ecosystems at personalization technology provider RichRelevance. Badarinath pointed to user reviews and product descriptions as information that’s often underutilized.
“If you think about the world of classic personalization, it’s either rules-based, built around pushing promotions or content, or behaviorally-based, centered around seeing what people are buying and returning,” said Badarinath. Next-gen hyper-personalization pulls from other sources. “Hyper personalization takes other assets, the unstructured data,” Badarinath said. “The things like product descriptions, product manuals, and review data, which you don’t plan for but which still exist in the system.”
By leveraging this wealth of unstructured data, retailers can create a better experience for shoppers, as RichRelevance’s retail partner Swim Outlet learned. “People were looking for an attribute that wasn’t specifically mentioned as a category: chlorine resistance,” Badarinath explained, “but it was in the product descriptions, and the reviews, so we were able to guide customers who were seeking that attribute to the products that had it.”
Related Stories
A website like Swim Outlet is conducive to detailed attribute searches in part because its inventory is largely homogenous. Users are more likely to be searching for specific attributes, like UV protection levels or texture descriptions, than broader terms. Larger retailers, like Walmart and Target, need to approach personalization slightly differently.
Meyar Sheik is president and chief commerce officer at Kibo. Sheik, who co-founded Certona, the all-in-one personalization suite that Kibo acquired in February, explained that bigger retailers can use personalization to optimize features like BOPIS that are meant to create a frictionless retail experience. “When you walk into a store to pick up an item you ordered online, do you receive a personalized notification, or is it just ‘your product will be at this location at this time’?” Sheik said. “Think about what can augment that experience.”
Rather then sending out cookie-cutter messages, Sheik said stores could provide personalized recommendations based on what shoppers are likely to purchase, incentives for looking at new arrivals or information on products in stock in store at high inventory levels. Features like these leverage a consumer’s history but also use mobile features like GPS and push notifications to carry a customized experience from online purchase to in-store pickup.
Offering a wide array of opportunities for personalization bridges many gaps in the retail pipeline, said Badarinath. “All brands wish there were a magic wand that could unify marketing, commerce, analytics and merchandising,” Badarinath said. “They usually have very different goals, but they’re all geared to creating the best possible customer experience.” For instance the same customer feedback can be used to enhance forecasting accuracy while also informing future marketing campaigns.
Integrating tools into the entire customer pipeline gives consumers a sense of continuity, Sheik said.
“We’re all consumers. We know when we’re getting spam or one-size-fits-all content. You don’t just want to personalize your website, but also email, push notifications, any kind of in-store messaging, clienteling or special kiosks,” he said, adding it’s vital that customers don’t feel like their buying journey is disjointed. Further, a fluid experience is more memorable, and more likely to generate positive word-of-mouth in consumers’ social circles.
As AI and predictive analytics become more vital to retail, personalization will become a long-term strategy for many retailers, said Sheik. According to Badarinath, that’s great news for retailers’ bottom lines—even if they’re already using advanced personalization techniques.
“I think about it as different buckets. One is retailers that haven’t done anything of this kind, and are embarking on a journey,” Badarinath explained. “Those companies can see anywhere from a 10 to 15 percent uplift in revenue from starting to use hyper-personalization tools.” He continued on to say that retailers that provide some tools towards personalization, but don’t integrate the data generated through features like advanced search and consumer content interactions, can see between 3 percent and 8 percent in annual increases. And that final bucket, billion-dollar major retailers that already have unified data and teams dedicated to hyper-personalization, can still see up to a 2 percent increase in revenues by consistently focusing on providing relevance. “A half-percentage increase might not seem significant,” Badarinath said, “but a half-percent increase on a billion-dollar revenue is excellent.”
Sheik said that cultural expectations around personalization are changing, on the consumer side and the retailer side. “Personalization isn’t a feature,” Sheik said. “It’s a strategy—a corporate strategy and also a customer experience strategy.”
Leaning into AI-driven personalization also gives brands the chance to build other aspects of their business by reallocating employee brainpower. “Humans are really smart, but they can’t scale,” Sheik explained. “A great merchandiser on a fashion site can probably outperform any engine if you only have a handful of shoppers and SKUs, but by automating that, your experts can handle higher-value tasks instead.”
Even if brands aren’t sure of the lifetime value of personalization, Sheik predicts the money- and time-saving benefits of AI-enabled relevance will drive retailers to the tools. “At that point,” Sheik said, “the improved customer experience, additional data and increased revenue are all gravy.”