Striking a Balance: Four Benefits of Blending AI with Humanity

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Delivering positive customer experience (CX) is a key competitive differentiator for organizations, and artificial intelligence (AI) has emerged as a key catalyst for delivering the seamless experiences that customers expect. In fact, more than 75% of decision-makers believe advancements in AI and self-service technology are among the most important factors for CX and customer success.

Despite its potential, knowing where to start with AI can be hard. AI can proactively improve how agents engage with customers, predict trends in customer service requests that help organizations make better CX decisions, and more – but when considering how to adopt AI technology, organizations often forget that AI is only part of the overall CX equation.

That’s because over-automation has the potential to cause more harm than good. As a result of COVID-19, customers now seek the human connection more than ever before. AI-powered self-service options, like chatbots, are great, but some customers simply want to connect with a human, whether or not their issue could be solved some other way.

According to our research, 77% of consumers called customer support despite warnings of long wait times and encouragement from brands to use self-service channels, and nearly half (45%) of customers who switched providers during the pandemic said they would have stayed if brands delivered better CX by connecting with them on a human level.

That’s why the role of AI in CX must be to enhance human connections, not replace them entirely. When done right, connecting with customers on an emotion level can be the difference between customer churn and customer loyalty.

Here are four ways that AI can help humans deliver better CX:

Active Listening
The majority of organizations only ‘listen’ to a small fraction of their customer interactions, and even more fail to understand customers’ behavioral expressions that shape the ease, effectiveness and emotion of experiences. For AI to accurately understand and analyze context, it has to be trained on 100% of customer interactions, not just a portion of them. In doing this, machine learning technology can intelligently determine the intent, action and emotion of customer interactions and uncover conversational meaning.

From there, AI can be used to identify the areas where humans can improve CX across an entire customer base or offer next-best guidance for how customer service agents handle individual interactions as they’re happening. We all know how frustrating it is when a service agent tries to upsell a service after we’ve just called to complain — imagine if that agent could use real-time guidance to make more informed decisions about the solutions to offer a customer or when a call should be elevated to a supervisor. AI can help identify when and where those opportunities are most effective, helping agents deliver better outcomes and organizations to drive the highest level of customer satisfaction.

Detecting the Unexpected
Customer service agents are faced with new questions from customers every day, so it’s no surprise that there are times when agents simply don’t have every answer. AI has the power to uncover these ‘unexpected’ CX situations. Take, for example, one of our customers who was able to proactively identify an influx in questions at the very beginning of the pandemic related to COVID safety precautions. Using these insights, the organization was able to proactively arm agents with the correct responses to questions that had never been asked before, and in turn, better service customers.

By continually correlating conversational context with machine-learned insights, organizations can reveal unanticipated challenges and opportunities for agents to better support customers. Through this approach, organizations can create an optimal situation where agents feel prepared, customers are satisfied, and business decisions are improved.

Mastering the Human Connection
Despite the power of AI when it comes to chatbots and self-service, consumers aren’t ready to give up on human service — 86% of customers believe call centers should keep the option to transfer to a live person and another 42% prefer to direct all questions to human representatives. So, it’s imperative that organizations use AI to help employees master their CX skills — not replace them.

With AI, organizations can identify areas of improvement in real time or post-interaction, and help employees understand how and where they can improve their engagements with customers in a data-driven way. AI can also help supervisors identify performance trends individually or across an entire agent base that may not have been realized before, using that knowledge to improve training. When AI is used to help supervisors be better managers, as well as agents to perform better and more effectively over time, everyone wins.

Resolving Complexity
Today’s AI is great for handling simple customer interactions without human interaction, such as checking an account balance or changing a password, but there are still plenty of customer service scenarios that are too complex for AI to solve. While AI isn’t right for resolving every customer issue, it can be powerful in helping call agents understand and navigate the complexity of customers’ issues.

One example of complex issues that we’ve seen emerge, especially during the pandemic, is customer vulnerability – and the need for organizations to better serve those who are facing illness, financial hardships and more. But identifying those customers in real time can be really difficult. AI can not only help identify those customers based on keywords, acoustical indicators and more, it can also suggest appropriate guidance to agents based on historical and situational analyses. Ultimately, when used to its full potential, AI can help CX teams resolve complex customer issues and requests more efficiently and effectively.

While AI is an important enabler, on its own, it’s simply not enough for organizations looking to deliver the best CX. The greatest CX success stories are those that use AI to enhance — not eliminate — the human connection. Today’s customers demand human interaction. By using AI to uncover insights that lead to well-informed agents and supervisors, brands can increase customer loyalty and strengthen relationships.

Eric Williamson
As CallMiner’s Chief Marketing Officer, Eric oversees all global marketing functions from brand and events to demand generation. Eric’s marketing team works very closely with channel and sales to drive pipeline and CallMiner’s explosive growth. Eric has over 20 years of experience in both technology and consumer products marketing from both the vendor and agency side. During his career Eric has worked with a variety of B2C and B2B brands including Google, Microsoft, Intel, GEICO, Walmart, P&G, Pizza Hut, Acura, Royal Caribbean, and Hyatt.

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