Shifting the service strategy in healthcare with conversational AI

Conversations are the foundation of customer experience, but customer preferences are changing. Not only do customers expect to engage with brands at any time across multiple touchpoints, but these interactions need to deliver value and be in line with their preferences and schedules.

It is important to be aware that every time your customers interact with your brand, they bring a purpose, problem, need or question. They also come with expectations for how quickly or easily a resolution will be reached. The challenge for a medical device company such as  Align Technology, is how to connect and respond to customers’ new and often unmet needs, so they can achieve their desired outcomes?

Rethinking the conversation

Getting closer to customers and widening the circle of “customer obsession” requires a foundation of data. It’s only when you have the right data that you can start to truly understand your customer base, tailor your solutions and leverage tools such as artificial intelligence (AI) and machine learning to improve their experience and meet expectations. This is where conversational AI comes into the picture.  

It's an effective tool for understanding the context of a conversation and reacting in a natural way. While there is still value in picking up the phone and talking to someone, conversational AI makes communication available 24/7 and gives customers the convenience of quick and constant support. What is more, conversation AI chatbots are constantly learning, improving language skills and understanding customer needs with every interaction.

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Striking the right balance

Of course, we’ve all had experiences where chatbots fall short. When they don’t give you the guidance or solution you are looking for and you end up frustrated and jumping on the phone. That’s what we want to avoid at all costs, and it usually happens when the experience is designed around the organisation, not the needs and preferences of the customer.

Rather, our focus must be on developing a conversational AI-driven experience that is empathetic and allows the organization to give the right answer for each customer, making recommendations based on their preferences. Ideally, the experience would offer easy and natural self-service for the most common requests, such as placing orders or asking product related questions, whilst keeping the discussion succinct and avoiding unnecessary steps.

When implementing chatbots in highly regulated industries, like healthcare and dental, where data privacy and security are top concerns, it’s critical to ensure privacy and regulatory compliance. Organizations need to have complete control over their data and the flexibility to enforce security, privacy and compliance policies.

Additionally, it needs to be obvious to the customer that the entity they are having a conversation with is a virtual assistant. This is particularly important, as research shows that AI with increasingly human-like features can be problematic, especially when people are unsure if they are communicating with a computer or a human.

Ultimately, the experience for the customer needs to be quick and painless, while the chatbot reads between the lines to provide an empathetic and personalised interaction that makes the customer feel valued and heard.

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Making the first move

Customer service will always require human interaction. The goal of conversational AI isn’t to replace people, but rather, to allow customer service teams to take on high-priority activities and deliver better service. Ultimately, the aim of tools like conversational AI is to help customer service teams to be more strategic, personalised and pre-emptive in their approach than ever before.

Customers value positive customer service encounters. In fact, more than 80 percent of customers reported that receiving value during a service experience makes them more likely to repurchase, even when given a chance to switch to a competitor. Going one step further, we are beginning to explore how AI can transition the customer service model from being reactive to proactive.

Here, the strategy shifts and instead of waiting for customers to reach out with a query or problem, companies are investing in predictive models, anticipating customer needs and fixing problems even before customers know they have them. 

At Align, we are experimenting in this area and using AI to help us anticipate the needs of our customers to surprise and delight them. For example, our doctors will regularly need to order replacement sleeves for their iTero intraoral scanners.

By analysing data patterns, our customer service team can be proactive and helpful in their approach, reaching out to doctors and asking if they need to reorder before they run out.

Here, AI is helping us to free capacity, and enable the team to spend more time on proactive, value creation activities.

The future is pre-emptive and proactive

Customer-centric organisations are redefining what it is to offer exceptional service. By finding the right balance between personalisation and efficiency, it is possible to give customers an experience they keep coming back for. Conversational AI has already demonstrated how valuable it can be in assisting organisations to go above and beyond customer expectations and give customer service teams the space to listen to customers and find ways to solve their problems before they become problems.

This proactive approach to customer service is a way of building customer advocacy and developing loyalty. Customers are at the core of all that we do. Through personalized recommendations and interactions, customers feel valued and special while customer service teams are empowered to proactively look for ways to deliver a better, more satisfying experience.

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