Beyond the bot: why AI in customer service means more than just chatbots

Customer support operator
Image Credit: Pixabay (Image credit: Image Credit: / Pexels)

Today, customers expect highly personalised customer experiences, regardless the industry,  products or services they are interacting with. Being welcomed by a customer service agent of a company we are dealing with, who not only knows who we are before we speak, but also why we’re calling and what our last interaction with the company was, has no doubt become one the many ways to delight your customers, but also a basic customer’s expectation companies should be able to meet.

But from an operational perspective, how can this be done? Agent expertise and the widespread use of artificial intelligence (AI) are behind the scenes of modern contact centres who have their customer satisfaction at the heart and soul of their business. 

More than just bots

When we think of contact centres and AI, automated bots immediately come to mind. Powered by natural language processing (NLP), bots are the front-line of most modern customer service operations. They triage users, parse their queries and provide answers where they can, passing only those with the most complicated and personal queries through to customer service agents.

Bots are just one way in which AI is revolutionising the contact centre. Behind the scenes, companies are increasingly integrating artificial intelligence with their customer-relationship management (CRM) software. This allows for a degree of timeliness and personalisation that is revolutionising the customer experience.

Using solutions such as the Zendesk Suite, contact centres can identify repeat callers by their phone number, while the caller is still in the queue. Not only can the agent greet the customer by their name, AI-based platforms can also automatically display the customer’s CRM records, giving the agent an instant oversight of the customer’s recent interactions with the company, the products or services they have purchased, and any other relevant details.

These records encompass not just the customer’s call records, but critically details of all their interactions with the company no matter the channel, whether that be by phone, email, bot, social media, or any other. As soon as communication is opened, the systems start logging the details of that interaction and its outcome.

With these records instantly available to hand, from the moment the agent speaks the first word of greeting, the call is more personalised, more relevant and more helpful than it would have been without the integration of AI technology into the company’s CRM and contact-centre software.

Ensuring that the right information is collected and always instantly available to company representatives is merely one way in which AI can help transform the customer experience.

Image Credit: Pixabay

Image Credit: Pixabay (Image credit: Image Credit: Geralt / Pixabay)

AI-powered analytics

Another is through the power of prediction. With access to data collected across all channels, AI analytics engines are able to generate actionable and timely insights into the prediction of customer behaviour and anticipate their needs. They can identify patterns such as which customers are likely to be late paying bills or may have an issue with a certain product.

By running constant real-time analysis on contact centre data, companies can spot both issues and opportunities before they arise, and anticipate customer complaints before they happen. Artificial Intelligence can work hand-in-hand with human contact centre workers, sharing with them these predictions and insights, enabling the company to respond pre-emptively to customer needs and challenges. Whether it’s intercepting a delayed delivery or flagging planned service outages, identifying these issues before they escalate further can be an extremely powerful way of improving the customer experience.

The predictive power of AI is multiplied even further when combined with another emerging technology: the Internet of Things (IoT). Manufacturers are already embedding IoT sensors in devices such as cars and consumer appliances. Just this past month, for instance, Volkswagen announced the Volkswagen Automotive Cloud. From 2020, the company will produce 5 million connected cars a year; one of the attractions of IoT connectivity, such as this, is that it enables companies to push updates and product improvements on a rolling basis, much as software makers have been doing for some time and, critically, allows data to feed directly into customer management platforms, helping agents to build a wider and more in-depth understanding of customers and the issues they might be facing.

When this information is fed into the company’s AI analytics engines, the impact on the customer experience can be huge. At the most basic level, companies can spot usage or operational patterns that may indicate an imminent failure, allowing them to get a replacement to the consumer before the breakdown occurs. These insights can also be employed to identify patterns that may indicate the customer needs additional bespoke support, or perhaps even a discussion around additional products that may serve to improve a customer’s experience at home.

Image Credit: Shutterstock

Image Credit: Shutterstock (Image credit: Image Credit: Jirsak / Shutterstock)

Transforming the customer experience with AI

Chatbots have come a long way since they were first introduced. They’re now intelligent, connected across the enterprise and able to add much more to the customer experience than simply triaging customers in order to make the best use of the time of human workers. However, chatbots aren’t the only way in which AI can transform the customer experience. By integrating artificial intelligence into the back-end of contact centre and customer-relationship systems, companies can make their operations timelier, more intelligent, better at predicting customer needs and more personal. This can help to increase retention rates by up to 42%.

As the customer-experience revolution progresses, the digital transformation of customer-contact workflows is now spreading beyond the front line to every part of the enterprise. Those companies which embrace this change will be tomorrow’s leaders. 

Jason Maynard, VP Product and Machine Learning at Zendesk

Jason Maynard
Jason Maynard is the VP and GM of Guide and Data Products at Zendesk. He heads up a team that builds products designed to drive better customer experiences through self-service and automation.