In a previous post, we discussed customer experience technology trends and how certain solutions are being used to better understand the customer, respond to their needs quickly and accurately, and deliver the kind of experience they demand. Intelligent, automated tools such as chatbots, Internet of Things devices, and advanced analytics are becoming essential as human interaction continues to make up a smaller and smaller portion of the customer experience. In fact, Gartner predicts that 85 percent of all interactions will be managed without humans by 2020.

“Intelligent” is the key word here as artificial intelligence (AI) is critical to improving and transforming the customer experience. For decades, the promise of AI was only fulfilled in movies in which robots were capable of thinking, reasoning, interacting and performing human-like tasks. Today, AI has a number of practical, strategic uses in the workplace and is widely viewed as a competitive differentiator.

AI is the ability of a machine to analyze large data sets in real time and use the insights gained to perform tasks, make decisions and simulate human behavior. The high-level goals of AI are to get things done more quickly, efficiently and accurately in order to produce better business outcomes without relying on human intervention.

Most of the customer experience now occurs online and through apps and mobile devices. AI is needed to take full advantage of the mountains of data produced through these channels, understand the needs and preferences of each customer, and optimize each interaction and the experience as a whole.

As we discussed in the last post, AI-based chatbots are becoming a standard business offering and customer expectation to streamline the customer service process. Virtual assistants in the mold of Alexa, Siri and Google Assistant use AI to listen to commands, perform tasks, and make recommendations. The more customer data an AI-enabled device absorbs, the more accurately it can predict the customer’s personal needs. With predictive personalization, the customer feels as if everything is tailored to their needs. They get exactly what they want, often without having to ask for it. Similarly, customer journey analytics makes it possible to process large, complex data sets to not only enhance existing customer interactions, but to find new opportunities.

Examples of AI use cases to support the customer experience include:

• In retail, AI is used to identify the ideal customer and personalize the experience accordingly, from personalized promotions and newsletters to user-specific web page layouts.
• Airlines and hotels are using AI to gain behavioral insights into customers, most of whom book online, and create a streamlined website experience that drives sales.
• Entertainment websites, which often fall victim to bots that automatically purchase large blocks of tickets, can use AI to distinguish between bots and legitimate buyers and dramatically reduce the number of scalped tickets.
• Self-service customer support offerings use AI to direct customers to helpful content, produce higher-quality articles, and automate self-service suggestions, using language that the customer understands. This not only improves self-service, but also allows live agents to operate more efficiently.

Due to the inherent complexity of AI, these tools can be difficult to evaluate, implement and manage. Let us help you understand your options and deploy solutions that enhance the customer experience and boost your bottom line.