By Phil Dance, Alter Agents
Over that last several years, hyper-personalization has become a necessity for brands and retailers. This level of personalization uses data to provide more personalized and targeted products, services and content. Retailers that are embracing the rapidly advancing artificial intelligence, automated personalization technologies and machine learning are positioning themselves for the future. These technologies do more than allow retailers to react to customer demand; they help them predict this demand and create magnetic moments among their customers.
Retailers who have been using algorithms and machine learning to do things, such as stock items in stores or allocate staff and resources based on peak times, are well-positioned to use these same technologies to better understand their customers and deliver a better, more personalized experience. These technologies can be used to dynamically recommend products and create experiences that appeal to individual consumers in the context of his or her own routines.
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In our years of research, one thing we have learned is that every customer is unique and each customer journey is different. This can be a very daunting reality for retailers. Our research has shown that shoppers choose very different channels and products based on how they prioritize brand, features and price for a given purchase. Their decisions can also change due to a number of different environmental factors. Modelling how shoppers choose their purchase channel and how this interacts with other shopper needs and priorities allows for much more specific, channel-focused marketing efforts that align with the needs of customers in those channels.
However, customers are giving us unprecedented access to their behavioral data with their ubiquitous use of connected devices — smartphones, apps, loyalty cards, etc. The use of these mediums allows savvy retailers the opportunity to collect this data and then use it to provide customers with experiences and in-moment product recommendations that were previously only available in an online environment.
Several years ago, Target famously used algorithms that, according to a Forbes article, figured out how to “data-mine its way into your womb.” The retail leader analyzed customer purchase data coupled with those signing up for a baby registry to detect when women from their database were pregnant and how far along they were in their pregnancy. The algorithm became so good at detecting this major life-change that by the time Target was sending out their personalized shopping ads, some of these women hadn’t even told their significant others the news.
To say that these technologies and advances in machine learning have improved even in just the past few years is an understatement. Retailers will need to bring much of a shopper’s online experience into their brick-and-mortar experience. Think about walking down an aisle in a grocery store and being recommended products that complement other items already in your cart; or recipes based on items you typically purchase; or even your experience being adapted to the type of trip you are on — is it a quick trip on the way to or from work or your weekly shopping visit? This is when retailers really start to drill down into hyper-personalization techniques like we already see in places like Amazon.com.
Retailers need to start thinking much more like the tech companies that are constantly disrupting the retail landscape. They need to leverage the vast amounts of behavioral data they have on their consumers and use it to generate delightful in-context moments for their shoppers, and be willing to constantly innovate within their space. True innovation grounded in insight generated from consumers and their needs is happening. The real question is who will lead the innovation — the tech companies and start-ups popping up everywhere or those already within the industry?
Phil Dance is co-founder and Chief Insights Officer of Alter Agents, a respected Los Angeles-based market research firm. He has more than 15 years of experience in the research industry, using consumer insights to help brands think from the outside in.
