Customer Centricity in the Digital Age
AI is helping retailers customize their offerings, create personalized experiences, and make shopping more convenient.
Customer centricity — putting your customer at the center of your strategy — has long been considered the holy grail of retail marketing.
In the digital age, customer-centricity revolves around data and smart technologies like artificial intelligence (AI). With the help of AI, companies collect as much data as they can about their customers’ wants, needs, and preferences, and then apply it to customize their offerings, create personalized shopping experiences, and make the purchase process simpler and more convenient. An example of new tools available for understanding customer habits is the Personality Insights service made possible by IBM’s AI platform, Watson.
As we continue to see AI moving from the hype stage to actual implementation within organizations, retailers and marketers have new opportunities for gaining a competitive edge when it comes to customer centricity. Here are three applications of how retailers are using AI to transform their marketing strategies:
AI allows retailers to identify which customers to cultivate. A company’s marketing efforts are always at risk of being ignored. There’s a reason that John Wanamaker, the 19th-century marketing pioneer, once quipped: “Half the money I spend on advertising is wasted; the trouble is, I don’t know which half.”
But AI helps companies know which customers are more receptive to their message — and, just as important, which ones aren’t. Machine learning and deep learning via AI-powered tools can parse vast troves of customer data in seconds. This helps companies differentiate between their most loyal, revenue-driving customers (high value) and those who tend to buy the least expensive products or products with the smallest margins (low value), and then create targeted approaches for each.
Asos, the U.K.-based online fashion and cosmetics retailer, applies a machine learning algorithm to predict a customer’s future worth. The algorithm analyzes customer data — including information about a customer’s demographics, purchase patterns, and returns history — to make a determination about his or her value. The algorithm then assigns a “tag” to each customer, which sends a signal to the online retailer. Asos, for instance, might nurture the high-value customers by targeting them with increased advertising or promotions, and spend less time and marketing resources on the low-value customers.
AI helps retailers provide individualized product recommendations.