Agentic AI has remarkable potential to transform voice of the customer (VoC) programs.
Just consider the birth of behaviorally-focused large language models (LLMs). Powered by this technology, AI agents may analyze vast amounts of conversational data to identify tone, urgency, and even behavioral patterns.
From there, these agents may correlate that data with specific customer queries to drive deeper insight, which they can then democratize across the business.
As Liz Miller, VP and Principal Analyst at Constellation Research, told the Big CX News Update:
We can implement granular processes that continuously extract real-time insights from customer conversations, feeding directly into product development and operational decision-making.
That's far more insightful than a quarterly PowerPoint from customer service saying: "Customers hate this feature." Instead, CX leaders may gain real-time feedback as to why.
Already, generative AI is allowing businesses to ask questions of their customer feedback data, enabling various departments to unpack relevant issues quickly. Yet, agentic AI represents the next frontier.
Conversation Summaries Are Also Proving a Rich Source of VoC Data
One of the most popular use cases of generative AI in customer experience is auto-summarizing contact center conversations and funneling those summaries into the CRM.
By taking this away from human agents, contact centers not only accelerate customer interactions but also remove the risk of human bias creeping into these summaries.
Finbarr Begley, Senior Research Analyst at Cavell Group, noted this while appearing on the Big CX News Update. Yet, he also shared how these more accurate summaries are becoming a rich source of VoC data.
As this data improves, Begley noted that agentic AI may help correlate "a single customer’s sentiment with broader trends across all customer interactions, offering a more accurate and scalable approach to understanding customer needs."
That then opens up several other possibilities. For instance, imagine AI agents funneling that customer understanding into CPQ (Configure, Price, Quote) system to bolster its outputs. Sharing this possibility, Miller noted:
We used to theorize about this possibility. Now, AI can do it, eliminating the need for robotic process automation (RPA) workarounds.
Voice Data Will Become an Increasingly Crucial Source of VoC Insight
With AI agents generating new insight into a customer's tone, urgency, and behaviors, voice data will become an increasingly crucial source of VoC insights.
While some may worry that this data source may dry up with the expansion of AI and digital channels, Simon Harrison, Founder & CEO of Actionary, thinks that's unlikely.
He noted how voice remains the first place people turn when self-service and digital engagement fail.