Technology Perspective
As contact center agents gain access to personal data and behavioral insight about customers, a one-size-fits-all, scripted approach to handling live customer issues becomes obsolete. Every problem requires individual detail and background about customer interactions, intentions, and needs; personalization is a must-have. Without this attention to detail, agents risk getting these interactions completely wrong and leaving customers without right solutions to their problems.
In fact, the recent Help Scout study revealed that customer service agents failed to provide adequate answers for customer questions 50% of the time. This signals a disconnect in the technology in use or the need for new technologies that help agents more quickly understand customers and solve problems.
Businesses can resolve this disconnect simply by giving agents access to customer-centric technology that provides pertinent customer information in real time. Here are three of the most beneficial types of technology for today's customer experience agent.
Virtual Customer Assistants
By 2020, Gartner reports that 25% of customer service and support operations will integrate virtual customer assistant (VCA) technology across engagement channels, up from less than 2% in 2015.
A VCA is a practical business application that simulates a conversation in order to deliver information and, if advanced, take action on behalf of the customer to perform transactions. A standard use case for VCAs involves responding to customer questions by pulling answers from a company's structured content libraries. In state-of-the-art deployments, VCAs can analyze the characteristics of an individual customer, use machine-learning techniques, provide contextual and personalized responses, and even trigger actions on the customer's behalf.
From an experience perspective, VCAs allow customers to engage and problem solve before even connecting to live agents. More important, effective use of a VCA can divert customer engagements away from the more expensive phone channel. In fact, after implementing a VCA, organizations report a reduction of up to 70% in call, chat, and email inquiries, an increase in customer satisfaction, and a 33% savings per voice engagement.
For example, an online retailer can use a chatbot to alleviate the need for customer calls inquiring about product information, shipping status, or return policies. The chatbot creates an engagement channel that allows assistance throughout the online interaction, and can even aid in processing transactions on behalf of the customer.
The VCA experience should:
Automation Through Enhanced IVRs
Shifts in consumer behavior -- due to the diversity and access of digital mediums -- have put a spotlight on the use of automation in customer experience centers. Currently, interactive voice response (IVR) systems, which prompt callers to answer a series of questions -- most often "yes" or "no" -- in order to send them to specific agents are the most common automation solutions in use today within the contact center.
Recently, we've been seeing improvements in traditional IVR systems by way of artificial intelligence (AI). Advanced IVR systems leverage conversational AI capabilities such as natural language understanding and natural language processing to analyze a call path and predict next steps for the customer based on previous responses. This type of predictive resolution not only results in shorter live agent handle time, but also provides agents with detailed insight on customer needs before a conversation begins.
Of course, while IVR provides efficient consultation to the customer in real time, it's typically only useful when supplemented with human-to-human interaction. In the end, dissecting and reacting to customer needs is a task best performed by live agents.
Social Media Analytics
Social media channels have become a top destination for customers to air complaints, begin to problem solve, and gather information on a particular product or service. Naturally, as social media becomes a more predominant medium for customer contact, these channels have become a critical component within the contact center. As contact center platforms improve their data integration capabilities for social media, we expect agents will have immediate access to social media analytics that share a more thorough background of a customer's journey.
While today's agents have access to cutting-edge technologies that can connect them more immediately with a live customer, there is a developing need to skill up and train agents to work alongside technology to better manage emotional or high-complexity customer interactions.
