MIT Technology Review: “Successfully improving customer satisfaction through AI means becoming data-driven, prioritizing employee feedback and resources, and letting business goals guide technology deployment, says senior product marketing manager at NICE, Michele Carlson.In the bygone era of contact centers, the customer experience was tethered to a singular channel—the phone call. The journey began with a pre-recorded message prompting the customer to press a number corresponding to their query. Today’s contact centers have evolved from the confines of just traditional phone calls to multiple channels from emails to social media to chatbots. Customers have access to more business information than ever. But improving the quality of customer experiences means becoming more customer-centric and data-driven and scaling available human representatives for round-the-clock assistance. Enabling these improvements is no small feat for enterprises, though, says senior product marketing manager at NICE, Michele Carlson. With large data streams and the demand for personalized experiences, artificial intelligence has become the key enabler in fostering these better customer experiences. “There’s such an enormous amount of data available that without artificial intelligence as this driving force for better customer experiences, it would be impossible to meet customer’s expectations today.” Amid the many moving parts in a contact center from managing multiple incoming calls to taking accurate notes of each interaction to measuring success metrics, AI can help smooth friction. Sentiment analysis can help supervisors identify in real-time which calls require escalation or further support and AI tools can summarize calls and automate note-taking to free up agents to focus more closely on customer needs. These use cases not only improve customer and employee experiences but also save time and money. While the promises of AI have many enterprises making swift investments, Carlson cautions leaders to be goal-oriented first. Rather than deploy AI because it’s popular, AI-driven solutions need to be purpose-built to support and align with goals…”