AI and Customer Experience

AI for CX will be used to allow tailored interaction with the individual which would allow communication at all hours of the day and allow call centres to focus on difficult issues, vulnerable people and edge cases.

Customers are constantly seeking smoother and more rewarding experiences when it comes to customer service. Alongside quality and value, it's a key differentiator when we decide who we want to do business with. In fact, research suggests that it’s increasingly becoming the most important factor, as far as many of us are concerned.

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.