As customer service has expanded into more channels, self-service has become key to scaling on-demand delivery in real-time. The traditional contact center operation model, largely based on a tiered approach to customer service, relies on agents fielding incoming calls to route customers to the appropriate department or representative to handle an issue. Today, technologies such as conversational interactive voice response (IVRs), virtual assistants, social media, and chatbots, deflect calls. In fact, by 2022, 85% of customer service interactions will start with self-service and 72% of customer interactions will involve an emerging technology, such as machine-learning applications, chatbots, or mobile messaging.
Thanks to the automation of repetitive and routine tasks, contact center agents now require more specialized knowledge and skills as they handle more complex cases and subsequently, collaborate more to troubleshoot. Some contact centers are already changing their compensation structure with payment based on team goals (NPS), rather than individual goals.
For more personalized case management that prioritizes delivery through the right channel instead of every channel, so-called intelligent automation (IA), the combination of artificial intelligence (AI) and automation, can route incoming inquiries to the most appropriate representative and recommend answers to agents for better, faster problem resolution.
This convergence of technologies can also help contact center agents maintain a comprehensive customer record of interaction history from across every channel. When asked what is most critical to the future of customer service, the #1 response was, “better agent engagement through the provision of a complete set of contextual data.”
Ultimately, AI is reinforcing—not replacing—the customer service expertise of live agents. And to keep up with these advances, contact centers of the future will continually inspect and improve operations, actively managing to improved organizational KPIs.
Aside from implementation, the other main challenge of AI technology is culture. The contact centers that leverage AI-powered tools most effectively and translate them into improved business metrics will spend at least 50% of their analytics budget on adoption-related activities and not the technology itself.