When it comes to customer experience, artificial intelligence (AI) is making a big impact across the customer journey. It’s fully automating simple tasks like product purchasing and subscription renewals, blending interactions and information across websites and contact centers, and assisting agents with greater levels of intelligence to make offers at just the right moment.
That’s good news!
For years, the call center industry has strived to deliver a seamless customer experience across channels, interactions, and touchpoints. This means ensuring a customer can move from a website engagement to a call with a contact center agent, and all the information regarding the interaction moves along with the customer—no repeating info, no wasting time, and no frustrated customers.
However, just as many companies and customer experience professionals have successfully completed this difficult task, times have changed again. Today, the stakes are higher. Customers not only expect a seamless experience across channels, but also across more than one channel at a time. That’s right. If a customer is on the phone with a call center agent, chances are he or she is also on the company’s website or using the company’s mobile app. Additionally, customers expect companies to anticipate their needs and make it as easy as possible for them to do business with you.
Thankfully, AI is coming to the rescue. AI’s improvements to customer experience (CX) are often tied to better use of data. In fact, according to a recent Salesforce survey on Service Organization Use Cases for AI, gathering basic information for customers, pre-filling fields in an agent console, case classification and routing, and providing management with operations insights were all top data-driven AI uses cases in contact centers.
Whether it’s automating simple service tasks with self-service or handling complex interactions more efficiently by providing more information for agents, AI’s improvements to customer experience are undeniable. AI can even enable predictive analytics to better anticipate customer needs and help your employees engage customers with just the right offer at just the right time.
Below we look at three AI-powered customer service use cases, and the impact they’re having on the customer journey today:
1. Chat Bots:
Typically the first CX use case that comes to mind, chat bots are fast becoming the norm for customer engagement on company websites. Chat bots are powered by knowledge bases that leverage AI to conduct automated text or voice interactions with customers. While chat bots have grown in popularity, companies should reserve them for more simple tasks or steps in a customer journey, leaving more complex actions to be handled by agents.
2. Virtual Agents:
AI is helping create a new breed of interactive voice self-service systems by enabling natural language processing to power virtual customer service agents. In fact, Gartner predicts that, “25 percent of customer service operations will use virtual customer assistants by 2020”. Virtual agents powered by AI and natural language speech apps are better at meaningful interactions than previous systems, proving to be effective in completing a range of transactions with a good customer experience.
3. Agent Augmentation:
AI presents unique opportunities to augment the knowledge of agents during customer interactions. As we’ve stated here on the APEX many times before, while AI will replace some tasks, the real impact will be its ability to help people be better at their jobs. AI is doing just that for agents in the call center. AI not only provides agents with better business insights to solve customer problems, but it also helps them make more accurate predictions about customer needs, using predictive analytics technology. AI can even assist agents by helping them identify potential issues with customers, as well as establishing a caller’s intent and sentiment with voice biometrics.
Is AI making its way into your customer service organization?
To learn more, see how the Bank of Montreal automates customer workflows and connects all channels to all products and services across its business—read the case study.