Sep 18, 2023

“AI takes the guesswork out of analysis by efficiently connecting the dots for agents and identifying commonalities between customer behavior,” Haung said. Larsen with Kustomer said AI algorithms identify patterns in user engagement data to “infer” the level of interest and satisfaction with a product, feature, or piece of content. Streaming companies, for example, depend on AI to learn subscriber behavior and preferences from the “fully consented and actionable” data customers provide as they view content, according to Ted Sfikas, senior director of digital strategy and value engineering for the San Diego-based customer data platform Tealium . 4. AI in VoC Analytics Anania with Zendesk said CX teams are using AI to streamline and expand VoC data analysis processes. “Automation allows us to analyze data in real-time as opposed to having to wait weeks or months to gather insights,” Anania said. “Data mining does not need an army of data scientists to be accurate or efficient.” Huff with UserTesting said companies are implementing AI for predictive analytics to help “illuminate a path ahead, revealing opportunities and cautioning against pitfalls.” “We’re no longer just listeners but forecasters,” Huff said. CX teams are combining linguistic-based NLP, multi-channel data analytics and predictive analytics to categorize feedback, extract insights, and enhance customer feedback dashboards, identifying areas of improvement and customer preferences, according to Obafemi with EY. AI-driven dashboards and monitoring systems give companies real-time insights and trigger notifications based on predefined criteria, allowing them to respond “quickly and efficiently” to customer feedback and issues, said Larsen with Kustomer. Martin with Qualtrics said AI in customer experience is “transforming” customer segmentation based on patterns of real-world behaviors as well as automatically discovering and building customer segments based on common behaviors across a cohort of customers — and “not only simple demographics.” “Given the right data streams, AI can update these segments with every customer interaction in real-time, allowing organizations to stay ahead of trends and capitalize on opportunities faster than they ever could with manual analysis,” Martin said. 5. AI in VoC Action Obafemi with EY said companies are applying AI-based VoC insights to inform product design and service improvements, tailor feature development and market messages, optimize R&D, and reduce waste. CX teams employ AI to anticipate customer needs, preferences, and potential issues, allowing for proactive engagement, said Ho with SOCi. For instance, Ho said, organizations lean on AI-powered recommendation engines to suggest personalized solutions or offers to customers based on their feedback and preferences. AI also enables workflows that help automate follow-up actions, ensuring that customer issues are addressed “promptly and consistently,” she said. Larsen with Kustomer noted that AI performs root-cause analysis on negative feedback and low Net Promoter Scores, helping identify recurring issues or patterns in customer comments and complaints. Based on real-time feedback, companies are taking real-time actions through AI, identifying positive and negative sentiment and providing next action recommendations to human-assisted interactions, “leading to better outcomes,” said Ziv with Verint. He said CX teams are now looking to AI to help automate case management and “close the loop with customers faster.” Gaurav Jain, assistant professor of marketing at the Rensselaer Polytechnic Institute (RPI) Lally School of Management , added that AI in customer experience is “ensuring that every customer who takes the time to share their thoughts receives an immediate and appropriate response.” “It's not just about the efficiency that AI brings to VoC programs,” Jain said. “It's about the opportunity to deepen our connection with customers. “By truly understanding their words, their sentiments, and even their behaviors, we can craft experiences that resonate on a human level. And in a world that's increasingly digital, that human touch is what sets a brand apart.” About the Author Chris Ehrlich, an esteemed journalist with over 20 years' experience, specializes in AI, business and B2B technologies. His authoritative works have appeared in top-tier outlets such as Datamation and Enterprise Storage Forum. As a published author, he demonstrates deep industry knowledge and holds a B.A. from Denison University. Connect with Chris Ehrlich: