This article is part of CMO.com’s March/April series about emerging technology. Click here for more.
Rapid digital disruption has sparked a wave of innovation, forcing organizations to drastically rethink how they operate and interact with customers.
Power, as we know, has officially shifted to the consumer, who expects seamless buying experiences across all platforms and devices. Pair that with the emergence of data-driven technologies, such as artificial intelligence (AI), and it’s clear that improving your business’ bottom line requires a data-centric approach—one that complements, augments, and ultimately drives consumer preference and decision-making.
In fact, an estimated 95% of customer interactions will be supported by AI technology by 2025. By applying data analytics to customer databases, CXOs can gain valuable insights into consumer purchasing habits, enhancing product marketing.
Here are three ways in which CXOs can use AI, which includes machine learning, predictive analytics, and big data as means to customize the customer journey for today’s digital era.
1. Anticipating Customer Needs
It’s no secret that the future of digital transformation will be rooted in customer experience. In fact, recent studies have shown that customers are more willing to buy an inferior product if the process is simple, intuitive, and enjoyable.
Because consumer technologies have made valuable customer metadata ubiquitous—and increasingly accessible to brands that are willing to leverage it—using data-driven methods to anticipate customers’ personal needs and desires is now table-stakes. New personalization techniques, such as digital retargeting and geofencing, for example, are helping brands predict the type of content and experiences consumers are most likely to engage with, and the best time to serve the experience.
In addition, industries ranging from banking to retail to telecommunications are using deep linking as a way to direct users to a specific piece of content or landing page, saving them time and circumventing potential confusion or hassles. Take, for instance, banks that allow customers to move money straight from their checking accounts to their savings accounts via a mobile app. With a deep link, customers are brought directly to the bank’s payment transfer screen.
Similarly, retailers are experimenting with deep linking and augmented reality to provide personalized offers based on shoppers’ unique profiles. For example, J.Crew’s Instagram channel allows consumers to shop through the app by integrating production information into its posts with special tags, which are then hyperlinked directly to that item on its website.
2. Simplifying Service, Support, And Communication
Customers expect fast, reliable, and helpful communication with brands, no matter what time or day. To stay ahead in the race, successful organizations are retooling to provide quicker responses across channels: Automated chatbots, voice control, in-app live chat, and videochat are all pushing the boundaries of what is possible.
For example, both Verizon and AT&T are using AI-powered chatbots to boost customer satisfaction, route problems, and, ultimately, detect and solve for issues before they even occur. But chatbot use goes beyond customer service. With the Verizon Fios chatbot, for example, users can search for TV programs, manage their DVRs, or add channels to their packages. In fact, Gartner estimates that by 2020, 85% of customer interactions with a company will be carried out without any human interaction at all.
In addition to chatbots, other self-discovery tools can be incorporated into the customer journey. These include self-help guides, interactive video tutorials, and adaptive FAQs—all powered by AI. These easily digestible tools provide customers with the solutions needed to make orders, learn more about the brand, or ask questions about a specific product.
3. Creating Long-Lasting Consumer Relationships
In today’s on-demand world, delivering personalized experiences is key to building long-lasting customer relationships across all industries. In fact, according to a recent study, 56% of consumers said that a personalized incentive would increase their likelihood of considering a particular company or brand.
When it comes to the retail sector, 41% of consumers have gone as far as to abandon a retailer over poor personalization. With AI, retailers can analyze a consumer’s past shopping behavior (browsing history, completed purchases, and even abandoned online carts) to make more targeted product recommendations down the line. When done correctly, via personalized discounts, special offers, or custom-tailored emails, retailers will reap tangible results: Those with personalized offerings are converting sales two to three times faster than those that do not. The reason: When delivering uniquely tailored experiences, consumers are more apt to make repeat purchases, recommend a brand to others, or purchase something more expensive than they’d originally planned.
The same goes for banking. By applying AI and machine learning, banks can analyze data from call centers, customer feedback, and even geo-locations to make future recommendations. Take, for example, if a customer goes to the same coffee shop every morning and makes a purchase on her credit card. Through an AI recommendation engine, the bank can then suggest other coffee shops in the same vicinity that provide cash-back discounts or perks. These types of scenarios not only deliver better customer experiences, but they also boost customer loyalty and generate incremental revenue for financial organizations.
At the same time CXOs are working to improve their customers’ journeys, they also need to observe their industry competitors’ digital advancements. Consider Amazon, which prides itself on leading in many elements of the customer journey, including intelligent recommendations based on previous or similar purchases, automatic reordering, one-touch product-specific buttons, and voice control. As these pioneering techniques become pervasive, customers will begin to demand them from all brands.
Today, for example, cable industries are competing with streaming services such as Netflix and Hulu, hotel industries are competing with online travel agencies like Airbnb, and traditional taxi companies are competing with ridesharing companies that include Uber and Lyft.
To stay agile, CXOs must consider which parts of their business can be digitally disrupted and fundamentally changed to enhance their customers’ journeys. Those CXOs who plan ahead by observing customers’ preferences and then adapting personalized experiences accordingly will gain an upper hand in today’s rapidly evolving digital landscape.