Using intelligent automation and machine learning, leading companies deliver personalized, omnichannel, low-effort self-service for faster issue resolution. In fact, after implementing a virtual customer assistant (VCA), organizations report a reduction of up to 70 percent in call, chat and/or email inquiries, and 33 percent savings per voice engagement. In practice, AI supports three capabilities of a low-effort resolution process:
Guiding customers to the right service channel
For customer inquiries made through a call, an interactive voice response (IVR) system equipped with AI can recognize a customer’s intent, to provide answers, understanding requests that aren’t a part of a predetermined menu of options. IVR with AI can also intelligently route calls to reduce handling time or give callers the option of receiving either a callback, switch to chat, or SMS message from the next available agent, rather than wait in a queue. Similarly, AI-based chatbots, which have natural language understanding (NLU) capabilities, can complete more complex tasks to reduce escalation to a live agent. Today, companies have a number of platforms to choose from to provide the APIs, infrastructure, and tools needed to build intelligent bots. These platforms are commonly referred to as conversational AI platforms, and let you focus on building a bot experience that works for your users without worrying about the underlying capabilities or infrastructure.
Reducing uncertainty in the resolution process
Customers abandon self-service when they lose confidence in their ability to resolve an issue without the help of another person. More specifically, Gartner’s research found that the top three factors impacting customers’ confidence in self-service are:
- Clarity: how easy it is to understand or act on given information;
- Confirmation: assurance that indicates resolution,
- Credibility; the utility or relevance of information.
Voice assistants, built on AI, use automatic speech recognition (ASR) and NLU to accurately respond to customers with relevant answers. Unlike chatbots, conversational AI uses advanced algorithms to train itself from data inputs and subsequently improves at predicting questions. Conversational AI can complete tasks, including paying a bill, completing orders, and providing instructions to customers without channel switching. The adoption of voice assistants is set to triple over the next few years with 8 billion digital voice assistants in use by 2023, up from the 2.5 billion at the end of 2018. On-demand webinar: Keeping it Human: Bots, AI, and CX
Leveraging proactive alerts and notifications
People expect businesses to interact with them on their terms — at any time, and on any channel — whether it’s SMS, voice, social, or email. However, engaging across every channel all the time for every individual doesn’t work either. Seven in ten customers have penalized a business for using the wrong frequency and channel. Research has shown there are best practices for engaging with customers based on the content and urgency of a message. It’s critical to honor a person’s preferences for when and how they wish to receive alerts, notifications, and messages. Get the eGuide: Blueprint for Mobile Notifications.
The value of faster resolution times has a heightened effect during challenging times of uncertainty and disruption, for businesses and customers alike. When the contact center is a powerful tool for providing ease, comfort, and assurance to customers it can promote enduring customer goodwill.