AI (artificial intelligence) is one of the most hyped technologies around. No more so than in the customer experience, customer service, and contact centre spaces where it seemed to completely take over the agenda in 2018.
So, let’s take a step back and look at how AI is currently being used to help deliver great customer experiences, and what some of its applications will be as the technology matures.
An overview of AI
AI isn’t just chatbots and virtual assistants like Siri, Alexa and Google Home. AI is also the magic behind machine learning, advanced analytics (Big Data), speech recognition and Natural Language Processing, text-to-speech and speech-to-text, voice and image recognition, interaction routing, dynamic WFO, workflow and business process automation, speech and emotion analytics, intelligent assistants, web self-service, marketing automation, predictive behavioural analytics, and many others.
In short, AI touches upon almost all areas of business and is particularly prevalent in technologies to do with customer interactions via the contact centre, website, mobile apps, social media, and even face-to-face.
CX challenges are technology challenges
According to several recent reports, customer experience professionals see technology as the biggest barrier towards delivering the digital, omnichannel, proactive, and personalised experiences their customers increasingly demand.
The lack of integration of systems, both within and into and out of the contact centre, along with data silos, poor analytics, and the inability to deliver seamless service across multiple channels are all still big issues.
In its various guises, AI can help with all of these.
5 ways AI can help with customer experience
Despite some of the overblown stories in the popular press, implementing AI does not mean firing all our staff and replacing them with robots or self-service systems.
In most cases AI will be helping humans to better and more efficiently anticipate and meet customers’ needs with the aim of improving loyalty, reducing churn and improving acquisition results all while managing costs.
Here are five examples:
- Allow human staff to do what humans do well. Chatbots and other self-service systems (intelligent FAQs, IVR) can handle routine enquiries, leaving complex and emotional cases for humans to deal with. People are good at empathy and creative problem solving so a chatbot or IVR front-end can screen out simple queries and route complex ones to the appropriate team after some initial fact-finding. This has the added benefit of increasing employee engagement and satisfaction.
- Predicting what customers want and are about to do. Digitisation has brought companies masses and masses of data about customers and products. Machine learning and predictive analytics tools help companies use this data to predict customer behaviour with a high degree of certainty. Knowing which customers are about to churn, default, suffer a problem, renew, or upgrade before they do is important information. A company can take proactive action to nip issues in the bud before they become real problems or promote special offers to customers likely to defect.
- Increase efficiency all round. Routing and WFO software is now infused with AI in order to predict the type and volume of interactions the contact centre is likely to encounter on a given day, at given times, based on what else is happening in and around the company. Down to the individual customer level, routing software can decide exactly which channel or staff member is most likely to give the most satisfactory outcome for each customer, and route accordingly.
- Know your customers and processes better than ever. All sorts of new analytics are now possible with speech recognition and NLP as AI systems can now ‘understand’ not just the meaning of speech or writing but also the underlying subtleties. Is a customer delighted or annoyed? Where are customers being asked to repeat information? Where are the pauses in interactions, why do they abandon carts, and so on? This kind of detailed analysis allows you to look not just at outcomes – the customer purchases or doesn’t – but how and why the outcome was arrived at. If the outcome was negative what were the reasons for that? All this information allows you to know what your customers really want, eliminate their pain points, and streamline your processes to better meet their needs.
- Intelligent assistants for your staff. Flip AI round and you get IA for Intelligent Assistants. Rather than fire your staff you can get AI to help them to do their jobs much better. AI systems armed with the kind of knowledge about customers we’ve already talked about can provide agents with detailed insights in a timely, context-sensitive manner when handling a customer interaction. For example, an intelligent system might suggest an upsell offer or just point the agent in the direction of the correct process to solve the customer’s problem. Emotion and speech analytics can even be used during an interaction to suggest alternative courses of action to the agent which are liable to speed up issue resolution or improve satisfaction. New services are coming online that even provide agents with a total, pre-packaged response to a customer’s query. All the agent must do is check it over and approve it.
AI everywhere and nowhere
The ultimate fate of a successful technology is to disappear so completely into the background that we no longer even notice it. So it will be with AI.
We will soon take it for granted that a lot of the software, devices and organisations with which we interact are AI-assisted.
When it comes to the complex business of delivering the level of customer experience that consumers expect these days, AI is already deep in the mix of solutions that CX professionals need to draw upon. Most of these technologies are graduating to the plateau of productivity as we speak, and you need to ensure your organisation is making use of them now, because your competitors certainly will be.