The impact of artificial intelligence on customer experience

By Michael Schweidler, EMEA Content Marketing Manager

Published December 9, 2020
Last updated December 9, 2020

Artificial intelligence (AI) is the buzzword on everyone’s lips right now. It’s thrown carelessly about in headlines, on Twitter and in boardrooms around the world. Even CTOs themselves sometimes struggle to distinguish AI from machine learning (ML), which has been commonplace in the technology industry for many years.

It’s not surprising that everyone is talking about it. The word AI has gravitas – start-ups know they are much more likely to get funding if AI is written into their proposals. AI conjures up images of the humanoids from our favourite sci-fi movies in the ‘80s and ‘90s and drives fears of robots taking our jobs. And just like the power loom replaced workers in the industrial revolution, it’s inevitable that AI will replace some jobs in the coming years – replacing the mundane roles, speeding up companies to excel and freeing up humans to be more creative.

But beyond the buzzword, we are on the cusp of another revolution (call it what you will: The Digital Revolution, The Robot Revolution, The Intelligence Revolution – we’ve heard it all). This change in our working methods will be driven by technologies like AI and ML and it is critical businesses are not left behind, because with AI under the bonnet, their competitors will be speeding into the distance offering their customers an improved product or service at a fraction of the cost.

AI is supreme intelligence, yes, but it also offers convenience, ease, and time-saving. It is already having an impact on the majority of industries, from automotive, medicine and retail, all the way through to your living room embedded into Amazon’s Alexa and Netflix. And, of course, customer experience is a prime candidate to benefit from an AI overhaul. It’s an area which is crying out for personalisation and indeed, some companies are already upgrading their CX services to be powered by AI.

Benefits you can achieve today include:

  1. Encouraging self-service online – Using a combination of ML and natural language processing (NLP), chatbots can help online customers find answers to simple queries.
  2. More personalised content – Deep learning models can spot common words and phrases related to specific issues found in support tickets and make tactful recommendations for optimising help centre content.
  3. More efficient customer support agents – Using a similar method to personalising content, this technique can also help agents quickly find the answer to a customer’s problem.
  4. Data-driven suggestions and predictions – Data recorded from customer service interactions can be used to improve future interactions. Using information from previous support tickets an AI model can predict positive or negative CX outcomes and make suggestions to improve the interaction in real time.
  5. Freeing business time to innovate elsewhere – With the time they’ve saved through automatic ticket resolutions, companies can use their human workforce to innovate elsewhere in the business.

What about the future of CRM?

But we’re only at the beginning of this revolution, and AI will be a key part of CX going forward. According to Gartner, 70% of all customer interactions will involve tools like chatbots and ML by 2020, with the abundance of voice and Internet of Things technology in our homes already preparing customers for this change in communication.

While we’re all becoming used to calling across the room to a small inanimate object to inform us of the day’s news, set an alarm or play your favourite song, we expect this slick experience to keep improving in all other areas of our lives, especially when we speak to brands. And as we can see from the improvement to the gadgets in our homes and our pockets, this technology is constantly improving and CX will only continue to benefit.

70% of all customer interactions will involve tools like chatbots and ML by 2020, with the abundance of voice and Internet of Things technology in our homes already preparing customers for this change in communication.
Gartner’s 2020 Magic Quadrant for the CRM Customer Engagement Center

In the near future, the likelihood is that you will no longer have to suffer listening to repeating hold music on the phone as you wait to speak to an agent to solve a query. With a combination of advanced AI chat bots allowing customers to self-serve, or directing customers to the correct specialist call agent immediately, AI has the power to get rid of frustrating wait times.

The conversations themselves will also become more intuitive as personalisation improves. At the height of the pandemic, customers were having to rearrange travel plans left, right and centre, and queues to speak to travel companies were so long, many companies were so overwhelmed they had to cut off their phone lines. Having the intelligence and, more importantly, confidence in your data so you can proactively reach out to customers with rebooking options would have solved a lot of those frustrations. But this isn’t possible if you don’t know your customer. In the not-so-distant future companies will be able to truly understand their customers and, in turn, become more efficient at serving them.

But all this intelligent personalisation and customer understanding relies on data. And in order to truly take advantage of AI to improve CX, the most important thing you can do is collect customer data for the AI model to learn from, and extrapolate future behaviour.

Stay focused on your business goals, and while keeping a close eye on GDPR-guidelines use initiatives such as loyalty schemes, digital receipts and content-driven newsletters to encourage customers to share their data with you. Next use an intelligence CRM system to match in-store data with online data to create a true version of your customer. Once you have data that is as clean and accurate, your business will be prepped, ready to take on and thrive in the next revolution and satisfy your customers with personalised, data-driven interactions.