Big data and artificial intelligence have changed so much about how we do business, not only in terms of our techniques and best practices, but also for customer expectations.
It is natural to worry that new technologies will only increase the distance and alienation between customers and retailers, but in reality the opposite is true: By automating the minutiae of customer interactions, innovations can handle the busywork. This leaves employees free to maximize the value of their time with customers and the customers’ investment in the company.
Automating the Little Things
Data mining and machine learning have allowed technology to improve the customer experience dramatically by custom tailoring recommendations to suit each individual. Businesses like Netflix make recommendations to customers based on their tastes and shopping habits. And these digital concierges apparently know what they’re doing, as 80% of Netflix selections are driven by automated recommendations.
Not only do people feel so overwhelmed by the available choices that they’re happy to trust automated suggestions, but they also appreciate the way these intelligent systems reliably save them time. More and more, customers will rely on curated suggestions for their unimportant or routine shopping, leaving it up to companies to create meaningful interactions above and beyond the mechanical.
Customers are ultimately looking for personal interactions when they have a retail experience. Picking the recommended movie or product is simple but forgettable, whereas a memorable and satisfying sales encounter stays with a person and turns them into a lucrative repeat customer.
Luckily, machine learning also can enhance human-to-human contact points just by giving employees the same information an algorithm uses to make recommendations. An employee armed with the customer’s preferences and datamined information will be able to offer that customer a tailored and personalized experience. This creates a sense of connection and consideration, and helps the customer connect to the products they purchase and the business selling them.
Shopping by Appointment
Personal and datamined information can be quickly pulled up for walk-in customers, but employees can also prepare beforehand with appointment shopping. Appointment management software allows shoppers to sign up for a particular time to arrive at the store and have a designated meeting with the employee of their choosing.
When the customer signs up for an appointment, they can share information with the store staff, such as what they’re shopping for and their general preferences. This allows for a more personalized and tailored experience — shopping by appointment and by design, targeted to the individual. While a recommendation made by an algorithm is convenient and simple, a friendly employee using their personal rapport with the shopper alongside AI suggestions can enhance a computer’s precision with that ineffable human touch.
Digital queuing technology can be used to maximize both store attendance and customer engagement. Machine learning technology and IoT can track a person’s shopping habits and suggest ideal times to visit a store, and the shopper can choose which of the suggestions works best for them, creating a feeling of agency and control.
Meanwhile the software can use a first-come, first-served system to fill out the day with shopping appointments, creating a structured day for employees and giving them time to prepare for meaningful interactions with each customer.
Data Builds on Data
One great benefit about machine learning is that data builds on data. The more customers engage with a system, the more the AI learns about their engagement and the better it can predict their future behavior. Store owners use this ever-accumulating information to streamline in-store attendance to reduce congestion and crowding, and maximize one-on-one time with sales staff. An intelligent algorithm can predict when customers would prefer to be given active choices, such as when to arrive, which employees to work with, and what sorts of items they’d be interested in having suggested to them.
In an increasingly impersonal world, these tailored interactions are how businesses can make the shopping experience all about the customer. Retailers must be ready to leverage the power of AI and data to make their shoppers feel special and enjoy unique, memorable interactions with staff and the business itself.
Businesses that rely too much on automated suggestions get pushed into the emotional background, behind big brands who use automation but take up so much space in the zeitgeist. Businesses that don’t dominate their retail space should take advantage of new technologies to enhance the human factor, making customer interactions as memorable as possible.
Kevin Grauman is the president and CEO of QLess, a line management system used by retail, education and government industries.