Customer churn is a serious problem for service providers.
While telecommunication and cable companies have made great progress in reducing churn over the last couple of decades, churn is once again on the rise. Even a single basis point increase in churn can mean more than $1M in customer value lost per month for large service providers. That’s a significant number. And the recent rise in churn isn’t because of a product or service offering (although those can occasionally be factors). It’s largely because of two things: poor customer service and ignoring insights that suggest a customer might be at risk.
Poor customer service drives subscriber churn.
According to a 2022 study by CCW Digital, 60 percent of consumers would consider switching to a competitor after two or fewer bad experiences. The same study found the 17 percent considered leaving after a single bad interaction. And the damage doesn’t end there. The White House Office of Consumer Affairs reports that unhappy customers will tell between 9 and 15 people about their experience, with 13 percent sharing their customer experience woes with more than 20 people. That means poor customer service doesn’t just fuel churn—it also impacts new subscriber acquisition and, consequently, profitability.
Consumers consider switching to a competitor after two or fewer bad interactions
Consumers consider leaving after a single bad interaction
Identifying churn risk customers with conversational insights and analytics
Is customer churn just a numbers game or can companies identify customers at risk of churning before they leave? With conversational intelligence, service providers can leverage behavioral insights and analytics to pinpoint risk factors. Perhaps a customer is out of contract or has had service issues or customer support issues or simply isn’t using their service as they have in the past. Identifying these (and other) risk factors can go a long way in preventing churn before it occurs. But only if companies take proactive action.
Proactive customer service can save subscribers at risk of churning.
Just because a customer has a bad customer experience, however, doesn’t mean the relationship is doomed. According to the SFDC State of the Connected Customer by Salesforce, 80 percent of customers will forgive a company for its mistakes after receiving excellent customer service. The key to rebounding from a bad experience—and reducing the risk of a customer churning—is responding with proactive care. As we discussed in an earlier article, proactive care happens when customer service looks beyond the initial interaction (or interactions) for opportunities to reconnect and re-engage with a customer. For at-risk customers, this means following up with possible solutions or remedies shortly after the negative experience. But how can companies respond before a customer defects? With the right technology.
Delivering proactive care with conversational AI and automation
Conversational AI delivers the conversational insights and analytics service providers need to target (and even predict) churn risks. Companies can then use this data to automate proactive service—and save the customer relationship before it’s too late. In fact, we’ve recently heard from a provider who reported that at-risk customers who were left untreated were eight times more likely to defect than those who received proactive treatment. That’s significant. But just how does conversational AI uncover the data needed to turn things around?
Combining natural language processing (NLP), artificial intelligence and machine learning, conversational AI analyzes customer conversations for valuable insights, captures relevant data and can even offer dynamic guidance to customer service representatives in real time. This includes flagging signs of dissatisfaction—including subscriber intent, sentiment and emotion—which would otherwise go unnoticed. Armed with this information, companies can then coach (or guide) agents at the moment of need or automate follow-up actions aimed at deescalating negatively charged interactions and recapturing customer loyalty.
How Uniphore helps service providers fight customer churn
Uniphore not only offers the industry’s premier platform for conversational AI, automation and interaction analytics, it fuses it with key APIs, like knowledge AI, automated speech recognition (ASR), NLP, behavior/sentiment analysis, tonal emotion and computer vision. This holistic approach allows service providers to unlock the full value of every customer conversation—in real-time and at scale. Now, providers can find the true pulse of their subscribers and take proactive steps toward turning the tide on customer churn.
But that’s only half the story. Our suite of AI-enabled tools—including U-Assist and U-Analyze —turn customer triage (i.e., churn reduction) into an opportunity to boost customer lifetime value (CLV). By analyzing both past and real-time interactions, U-Analyze can unearth actionable insights that can influence customer behavior—when the first signs of dissatisfaction appear. Drawing on this (and other) data, the real-time guidance in U-Assist can aid live agents on the next-best actions to take to resolve a customer’s issue and improve their brand relationship and, ultimately, loyalty. This process of transforming risk into opportunity offers massive value to service providers struggling with fluctuating CLV. And with the recent addition of behavioral science experts from Hexagone, these solutions will only become stronger and more accurate—exactly when companies need them the most.