Is artificial intelligence the future of customer experience?

Artificial Intelligence (AI) has caught everyone's attention in recent years, mainly because of its disrupting nature which gives it enormous potential with countless applications.

Among the many possibilities that AI promises, customer experience (CX) is an area that offers immense opportunity for organisations to differentiate.

Welcome to the experience economy
Consumers today have more choice than ever before. They’re more empowered, and they have much higher expectations of the organisations that they do business with.  Welcome to the experience economy where the biggest differentiator for success is no longer about having the best product or the lowest price – it’s all about the customer experience.

Today's consumers compare products and services with the best service they ever received – from any company or person. That’s why we’re seeing industry disrupters, like Netflix, Uber and AirBnB forcing organisations to adopt new business models and digitally transform themselves to meet changing customer expectations.

To deliver the personalised and relevant experiences that today’s consumers have come to expect, brands need to process and analyse the vast amounts of data now available to them. And they must act on the insights in a timely and cost-effective way to impact customer experience while also managing costs and resources.

It's no surprise then that organisations are increasingly looking to AI to help address this challenge and create more meaningful customer experiences.

Revolutionising the customer journey with AI
Customer journey mapping and optimisation is a common challenge in today's omnichannel environment. Marketers need to guide customers along the journey with the right ‘next best action’ content message or offer at any point. But traditional marketing automation and journey orchestration solutions are hitting a wall with the many permutations of paths in any single customer journey, and the myriad different actions, content, messages or offers to select from. The scale and complexity of this challenge is a perfect opportunity for the application of AI in the shape of reinforcement learning.

Reinforcement learning is a type of machine learning, and at its core is the concept that the optimal behaviour or action is reinforced by a positive reward, which allows the algorithm to learn on its own very quickly.

Here’s an analogy: Think of a toddler learning how to walk. On the first try, she might take a big step and fall over. On her next attempt, she adjusts her step, making it smaller to see if that's the secret to staying upright. If that works, she tries another small step. And so the toddler continues learning and adjusting until she can walk confidently. Staying upright is the reward that helps the toddler reach their goal.

Reinforcement learning takes the manual guess work out of marketing and optimises the customer journey by continually looking for the next best action to deliver the best outcomes. It continuously tries different actions to work out which will deliver the best outcome in the long term.  In time, the system learns which action will deliver the best outcome – but every now and then it performs a random action just to be sure that the model is still fresh and up to date.

This is an exciting step forward for marketers searching for the holy grail of customer journey optimisation and ensuring next best action across every touchpoint. And it’s just one example of how AI is helping improve customer experience. In my next post, I’ll share how personalized recommendations are getting better and better with help from AI.

Tiffany Carpenter is Head of Customer Intelligence, SAS UK & Ireland.