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Boost Customer Engagement By Using Analytics

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Sheila McGee-Smith, president and principal analyst, McGee-Smith Analytics and No Jitter contributor, recently spoke with Abby Monaco, senior product marketing manager, NICE CXone, during a NICE Talk titled “How to Surprise Your Customers: Analytics in the World of Digital Engagement” (available on demand). The talk encompassed why businesses are increasing their data and analytics use, how data and analytics can improve customers' digital experiences, and how both helped an employee-screening company drive results.
Data Use Expansion: Why Now?
Artificial intelligence (AI) and analytics increasingly support automation, self-service, and digital engagement. AI-powered tools also managed high volumes of unemployment applications in 2020 and combated fraudulent unemployment claims, McGee-Smith described as she cited the 4 million people a month quitting their jobs. She explained why government employment offices are “great examples” of a vertical industry without much innovation. You wouldn’t have expected massive artificial intelligence self-service applications in government, local, and federal [sectors], she described. But faced with millions of citizens filing unemployment claims, local governments rushed to improve self-service solutions and needed data to do that.
Adding to what she refers to as the post-pandemic effect, McGee-Smith explained that it threw organizations contemplating or thinking about proofs-of-concept into a position where they had to take immediate action. “Liberty Mutual is a great example of that,” McGee-Smith said. She explained that the insurance company, with tens of thousands of agents using on-premises-based systems pre-pandemic, pivoted quickly to add conversational AI.
McGee-Smith says that conversational AI is not about offering an alternative to interactive voice response (IVR), “it’s about using data we have about a customer or a situation—like a hurricane in a geographic area—to say, ‘this group of customers has this specific intent, let’s send them to a resource—perhaps more quickly in self-service mode—than we could with a live agent.’”
McGee-Smith added that when combining data and analytics, "you can make sure your agents are serving the right people and offering the right people that automation."
How Analytics Improve Digital Experiences
During the talk, McGee-Smith presented Salesforce data demonstrating that customers are becoming more familiar with AI. “More than half of customers now point to an example of AI they use every day—like voice assistants or generated playlists,” she said. These use cases raise concerns for contact centers that want to use AI ethically and without bias. “But at the end of the day, consumers are ready and open to the use of AI to improve their experiences.”
We've all been frustrated customers, and McGee-Smith emphasized why sentiment analysis has real value for contact centers looking to reduce customer frustration. The frustration on customers' part when they feel as if contact center agents are speaking too quickly or not taking ownership of their complex queries.
McGee-Smith explained that contact center managers must arm virtual and live agents with a single-knowledge base—a collection of well-organized information that users can access via browse and search functions. As customers, we’ve all experienced the issue where what information a company may have on its website, but it's not the same as what an agent says during a call. Or sometimes, McGee-Smith elaborated, a customer doesn't like the contact center agent's response, so they hang up and call again. “As a consumer, we’re using those tactics because companies aren’t coming up with consistent ways of offering knowledge, she added. “Using analytics to deliver a better digital experience is one common knowledge base.”
Customer Example: HireRight Achieves Results with Analytics
Before wrapping up the conversation, Monaco shared a customer example with the crowd. To reach goals of improving its service and customer satisfaction (CSAT) score, HireRight, an employee-screening company, used the voice of the customer (VoC), collected customer feedback and acted on that data. Monaco jumped in and described how the company was able to understand that people are satisfied or unsatisfied, but “you can judge what they’re saying and take action in a meaningful way.”
By doing that, the company saw a 36% increase in its net promoter score (NPS), 55% increase in agent satisfaction, 45% increase in agent professionalism, and 32% improvement in issue resolution.
This customer example demonstrates the direct link between data analysis and engaging customers in a satisfactory transaction. The talk intended to cut through the industry jargon and present what real-world analytics application looks like for businesses.