Artificial intelligence (AI) makes our lives easier in so many ways.
Alexa tells us what the weather is on our way out the door. Siri makes sure we don’t forget anything during our trip to the grocery store. Waze lets us know when our morning commute is going to get a little dicey and suggests an alternate route.
But AI’s benefits aren’t limited to everyday life—they also have far-reaching implications for the business world. By leveraging AI strategically, customer service teams can predict needs before they arise, respond faster and more effectively to problems, and develop solutions that wouldn’t be possible with human innovation alone.
Here are four ways contact centers can use AI-enabled tools to improve the customer experience while balancing efficiency.
How AI Can Help Contact Centers Balance CX and Efficiency
Smart chatbots do more than follow a script
Chatbots are becoming increasingly sophisticated, able to assume a growing number of the repetitive tasks performed by live agents. Gone are the days of relying on scripted answers to a fixed set of questions; today’s AI-enabled chatbots are better classified as intelligent virtual assistants, and they’re pushing the envelope of what’s possible when it comes to customer engagement.
Intelligent virtual agents learn from their past experiences, building up an ever-growing knowledge base and getting smarter with time. They “speak” like humans and use conversational AI to discern meaning from a user’s words, enabling them to answer most questions. For questions they don’t have an answer to, they seamlessly hand off chats to human agents and learn from their responses, so the chatbot can better tackle the issue when it comes up again in the future.
The best chatbots don’t rely purely on AI alone. Instead, they use automation whenever possible and employ human interaction when necessary to deliver productive interactions that solve customer problems and reduce wait time.
Behavioral analytics predict future customer behaviors
Wouldn’t it be great if you could read your customer’s minds, anticipating their need for service before they even pick up the phone to call customer support? While AI doesn’t go quite that far—at least not yet—it comes surprisingly close.
With AI, CX leaders can use behavioral analytics to predict why a customer is calling based on their past needs and support interactions. Machines can draw meaning from a customer’s different touchpoints, like opening a particular email or using text message support. AI can gain insights from these touchpoints both individually and collectively in the context of their order and frequency.
Likewise, AI can use such customer data to predict future behavior using things like sentiment analysis to mine past interactions for patterns, like which product a customer is most likely to be interested in next for upselling and cross-selling opportunities.
For physical products that are used in the home, we can predict when a customer is running low and send a new shipment before they even have to add it to their shopping list. That’s getting pretty close to the mind-reading capabilities we touched on a moment ago, wouldn’t you say?
Though all of this predictive analysis can boost your bottom line, it’s not merely a self-serving pursuit in the name of profits. More personalized recommendations lead to increased customer satisfaction. In fact, the more accurate a personalized recommendation is, the more positively a customer views the interaction. When used in this way, AI-powered predictions help us do better for our customers and continue to get better at servicing them over time.
Real-time feedback helps agents provide better service
We can do some exciting things when we layer AI on top of text-to-speech (TTS) capabilities, which allow us to analyze a customer’s spoken or written responses in real-time.
By examining the customer’s word choice, inflection, tone, volume, phrasing, and more, machines can gain insight into how a customer is feeling much faster than a human agent could. We can use that insight to illuminate the caller’s frame of mind and make decisions about the best course to take with the interaction (solve the problem as quickly as possible? Recommend additional services? and so on).
Together with natural language processing, AI can also identify patterns in the customer journey based on their words, like flagging interactions that are similar to others that have been successfully resolved in the past. Contact center software can use these patterns to send agents suggested scripting for what to say next and even provide live coaching.
Powerful insights help you improve business performance
A recent study by the Institute for Corporate Productivity and the American Management Association had some pointed findings for businesses. Researchers found one thing in common among the companies that were the most profitable, enjoyed the greatest market share, and had the highest customer satisfaction ratings: all of them had a relentless focus on their customers.
We can use AI and machine learning to develop this relentless focus by zeroing in on the insights that will help us make meaningful changes that benefit the customer. For example, what behavior patterns are predictive of a customer that’s about to cancel their contract? What agent actions are the most successful in terms of recovering at-risk accounts? Which scripts are most likely to turn negative calls into positive resolutions?
Addressing any or all of these things—and related issues—will help you dramatically improve your service offering and deliver more effective, meaningful customer interactions.