Acquisition Marketing
Audience Segmentation
Customer 360
Identity
Journey Orchestration
Customer insights. Agent performance metrics. Compliance and QA data. Each offers a glimpse into the core components that drive the modern contact center. And while today’s analytics tools can drill down into the data further than ever before, they often fall short in one critical area: the big picture view. That’s because, until now, the focus of contact center analytics has been on zooming in, not out. Want to know which topics customers called the most about at a given time? Done. Want to learn which agent actions impacted those calls most favorably? That’s going to take some time—unless you have conversational intelligence.
The need for comprehensive conversational intelligence
The need for a “big picture” 360-view has been around almost as long as contact centers themselves. But, until recently, there was no way to unify all the various data points from every customer interaction into a single, searchable source. The technology simply didn’t exist. Instead, contact centers had to rely on a patchwork of solutions for gauging operational efficiencies and key performance indicators (KPIs).
Going from operational and performance data to insights was another task; one that typically involved manual sampling—a time-consuming and imprecise process. The “insights” produced were often a mix of cold data analysis and educated guesswork. What’s more, they were difficult to access, requiring rigid keyword lists to surface relevant information. Search the right keywords, and you could get a rough, semi-accurate assessment of your Quality Management (QM) or Voice of the Customer (VoC), for example. However, any conclusions or correlations you drew between the two would be entirely up to you. The technology didn’t, or rather couldn’t, connect the dots between the data points in a simple, cohesive way. As a result, contact centers couldn’t see the whole customer service forest for the trees.
Then came generative AI, and everything changed.
Generative AI is turning rigid analytics into actionable intelligence
With generative AI, enterprises can train AI applications and agents on enormous datasets and generate accurate, actionable insights in plain language. In the contact center space, where thousands of customer conversations are happening across multiple channels, GenAI-powered conversational intelligence is doing the impossible: analyzing every interaction, not only for content but also for contextual data, like sentiment and tone. And it’s connecting the dots in ways that were previously unfathomable, uncovering hidden trends and call drivers that are only visible by looking at the data with a wide lens and generating conversation summaries that are rich in connected, contextual information.
That’s a significant departure from the analytics tools of yore. By pulling insights from the whole fabric of customer data, this new breed of conversational intelligence software isn’t just optimizing a few outcomes, it’s reshaping the way contact centers think, plan and operate. Now, contact centers can see how a targeted action (whether good or bad) can cascade throughout the organization without juggling multiple tools or making logical leaps based on limited data.
Take Quality Assurance (QA), for example. In its 2024 report, “How to Evolve QA Into a Strategic Quality Intelligence Program,” Gartner outlined how contact centers could combine multiple streams of data—Quality Management (QM) data, Voice of the Customer (VoC) data, conversational analytics—into a single source of truth for service quality. Organizations could then use this centralized “quality intelligence,” as Gartner calls it, to improve core functions (i.e. agent coaching), predict future outcomes and support other systems, like customer data platforms (CDPs), that integrate and activate customer data for enterprise-wide use.
Getting the answers you need, just by asking
Clearly, generative AI is revolutionizing how contact centers consolidate and make sense of the vast amounts of data they generate. In fact, a 2024 Deloitte study found that one in six contact centers is currently deploying GenAI in some capacity. The study also found that service innovators—organizations identified as setting the standard with the most sophisticated capabilities in their service delivery—are 2.7 times more inclined to invest in analytics compared to those with less advanced capabilities. But what does the modern conversational intelligence s solution look like? It may be more familiar than you think.
That’s because today’s leading GenAI analytics tools are designed to be, first and foremost, intuitive. Think simple search fields and easy-to-read knowledge graphs. U-Discover, a groundbreaking GenAI-powered conversational analytics solution by Uniphore, enables users to scour troves of contact center data using plain language queries, for example. Instead of memorizing rigid keyword lists, users can simply ask, “What topics are customers calling in the most about?” and the program will generate a highly accurate, plain language answer culled from the entire corpus of contact center data. But that’s only the start.
Because it connects and analyzes data from across the contact center, U-Discover also surfaces relevant trends and correlations and generates actionable insights for improving operational efficiency and agent performance. Its advanced features include:
Topic discovery and drill down
Quickly identify and make sense of trending topics with Smart Search and word clouds
Automated quality monitoring and scoring
Contextually rich agent performance scoring that links to key moments during the conversation via transcript
Advanced sentiment and tonal analysis
Powered by emotion AI, this analysis provides added emotional context to help improve customer satisfaction and resolution rates
Personalized agent feedback
Targeted performance feedback delivered at key times during the call to accelerate agent development and coaching
Conclusion
GenAI-powered solutions, like U-Discover, are the next breed in conversational intelligence, enabling contact centers to see—and do—more by zooming out to the macro level. Armed with this 360-view, customer service leaders can make smarter, strategic decisions across the organization—from sharpening agent coaching to correcting pain points within the customer journey.
What’s more, there’s no need to update the natural language prompts to maintain their accuracy. U-Discover’s underlying fine-tuned LLM, for example, understands conversation context and the various ways people express the same thing. That’s a major improvement over key word-based business rules, which require users to periodically listen to conversations and update their key word lists based on new information.
With its ability to corral huge sums of data into a cohesive view and learn without user intervention, conversational intelligence is rewriting the future of customer service. And it couldn’t happen at a better time. As customer expectations continue to grow, contact centers need a better, easier way to understand, anticipate and proactively address the conversational and contextual drivers that impact every interaction. Now, they finally have a solution.
Is your contact center ready for conversational intelligence?
Contact our experts to learn if generative AI-powered conversational intelligence is right for you.