The term customer experience (CX) covers many areas of our interactions with businesses. How easy is it to access the products and services we want? How friendly and knowledgeable is the staff and are they able to answer any questions we have? Does the technology stack – payment processing services, for example, get in the way and cause difficulties? And if anything goes wrong, how quickly and efficiently is the business able to get things back on track and make sure we finish the process as happy customers? As customers, we will – either consciously or subconsciously - assess the interplay of all these factors and many more in order to determine whether a company provided us with a good, bad, or simply satisfactory customer experience!
As businesses, then – what can we do to ensure our customers score us highly in this regard? Well, one option that more and more companies are investing in is artificial intelligence (AI).
In business, when we talk about AI, we generally mean machine learning (ML). These are computer algorithms designed to carry out one task and become increasingly good at it as they repeat it again and again.
Some simple examples in the context of CX might include:
· An ML algorithm to understand a customer complaint and direct them to appropriate help, reducing the time they need to spend waiting for help (a chatbot).
· An ML algorithm to recommend the products and services a customer is most likely to find useful, reducing the time they need to spend searching on a website (a recommendation engine).
· An augmented reality (AR) application that lets you see how products from a retailer might look in your own home before you buy them or that lets you try on clothes in a "virtual dressing room."
These are all simple methods of using AI to create more streamlined and rewarding customer experiences that are used by thousands of businesses around the world. More advanced use cases are emerging by the day, so in this post, I want to look at how they are likely to affect us in the future. To help me develop an overview of the subject, I was lucky enough to get the chance to speak to Einat Weiss, CMO at NICE – CX experts who are firm believers in the value that AI and ML are bringing to the field.
What’s Driving the Adoption of AI in Customer Service and Experience?
Weiss told me that there are three main factors that are driving the ever-growing use of AI when it comes to building better customer service and CX operations.
Firstly, there's the fact that customers, in general, are becoming more digital in the way they live their lives, shop, do business and even socialize and hang out with friends. Increasingly, this is being done in online environments where everything we do leaves a “data footprint” that can be analyzed by businesses in order to understand intent, and find out the best ways of provide self-service as well as proactively reaching us in a more personal and accrate way.
Secondly, there's the widely discussed "skills shortage" – put simply, it's becoming harder for companies to find human workers, leaving many looking towards AI and automation to plug the gaps or to augment the skills of the workers they do have.
Thirdly, there’s the predicted economic downturn and the fact that many businesses are facing up to uncertain times. This leads to prioritization of operational efficiency, tech stack simplification and streamlining, with many companies looking towards tech-driven innovation in order to drive efficiency without damaging existing CX and customer loyalty.
Weiss tells me, "These are the three forces that are pushing AI forward, specifically in the world of CX … for many years, a lot of organizations that we work with have been trying to be able to provide service to their customers where they want to consume it and in a smart way … so creating an intelligent way to provide that throughout their journey is really what AI is for in CX.”
Will AI Replace Customer Service Workers?
AI certainly doesn’t mean the wholesale replacement of human workers in the field of customer service and CX, it is more so a power multiplier.
The fact is that there are still many situations where the human interaction that's required is simply too nuanced, complex, or subtle to be carried out by machines – and this is likely to be the case for some time yet!
Rather, forward-looking businesses should look towards ways that AI and ML can be used to relieve human workers of the more mundane and repetitive elements of their work. These are the elements that lead to workers becoming dissatisfied and leaving – and it’s a sore loss for a company when they lose a human agent who's great at dealing with complex, tricky cases because they are bored with the mundane work that a robot could easily have done for them.
As an example, Weiss points to one part of the role that she tells me is one of the least liked by customer service agents she speaks to. This is creating summaries of calls and interactions that document how cases were tackled, and customer issues were addressed.
Weiss tells me, "For many years, organizations had to train employees to adapt to the tech that they have in their technology stack; now the trend is to make sure tech works for the employee.
“ AI can understand the intent, the behavior and the personalities of both the customer and the agent to create an automated post-interaction summary. This not only makes them more productive because they can move straight to their next interaction but also takes something they absolutely hate off their plate.
"And AI is very objective – so from the organization's perspective, they really get what actually happened.”
During the call itself, AI will increasingly be used to guide the customer service agent through their interactions with the customer. This could be simple advice, such as pointing out they are talking too fast or have forgotten to pass on some important information, right up to sophisticated insights into the rapport that is developing based on analysis of language, and even body language.
How will AI Assist the Customer Service Agent of the Future?
As we’ve explored, the customer service agent of the future is likely to be augmented by AI, with a number of tools providing real-time assistance as they interact and engage. However, because AI will cover the simple, routine inquiries, they will need to have a high level of knowledge as well as emotional intelligence in order to deal with the difficult, human-driven questions that machines just aren’t good enough for.
Weiss suggests that in the case of, for example, an insurance company, this will include the difficult, distressed calls that can't be appropriately handed to a computer. "They need to have people on the other end of the line who are not just quick but also empathetic," she tells me.
They will also have to be able to bring themselves up to speed quickly to deal with being dropped into the middle of a conversation when the robotic systems get “stuck” and find they can’t provide the necessary help. This is another aspect of the role where AI will assist – by providing quick, up-to-the-minute summaries of everything that's been discussed to enable the human worker to seamlessly slot into the call.
“They need to be able to pick up from a certain point, and help to resolve the issue. This level of sophistication will just require a lot of tools that will be able to provide agents with nuggets of information that are relevant, consumable, and very, very timely."
It seems clear that AI and ML are already enabling companies to provide customers with smoother and ultimately better customer experiences. At the same time, these technologies are making the role of the customer service and customer experience agents more rewarding, freeing agents up to use their human skills to solve problems and create human connections. As customers increasingly base buying decisions on the standard of CX provided by organizations, this type of innovation is likely to become essential for organizations that want to stand out from the crowd.
To learn more about Nice, click here and to watch my webinar with Einat Weiss, CMO at NICE, where we cover many other aspects of artificial intelligence and customer experience, click here.