Chatbots in the future of customer service

Chatbots and generative AI are set to take centre stage in the future of customer service, but challenges remain to be addressed

With shifts in economic environments continuously influencing consumer shopping habits, brands are having to work harder than ever to earn customer loyalty. Recent research by ServiceNow shows that nearly two-thirds (58 per cent) of consumers in the UK aren’t as loyal to brands as they once were. But the sustainable solution to this problem isn’t a ‘race to the bottom’ on price point. Positive, simple and 24/7 customer interactions are a key driver to boosting loyalty. It’s why technologies like chatbots and generative AI are driving a paradigm shift in transforming customer service.

In fact, generative AI is predicted to boost the world economy by up to $7tn. For business leaders, this presents a once-in-a-lifetime opportunity to upgrade the service they deliver to users, to help retain and grow market share while building customer loyalty. Large language models, for example, offer huge potential both to upgrade the chatbot experience, and to empower human customer service agents.


The history of the chatbot: Where it was and where it’s goingThe history of chatbot software goes back decades, and now its application is making its mark on the enterprise.


A generative game changer

Customers often feel like they must jump over hurdles, trying different phrase combinations to explain what they need to get a rules-based chatbot — which is typically defined with existing mapped-out responses — to understand their request. Generative AI addresses this pain point, by continuously training and optimising chatbots to deliver a far more sophisticated, personalised level of customer support. Through conversational interactions, the technology can provide intelligent support for faster issue resolution while increasing self-solve rates to better streamline processes for the human agents.

Generative AI’s ability to formulate responses based on historical insights, such as past behaviour and user profile problems, is a key differentiator for business leaders looking to win customer loyalty. Considering the majority of customers (87 per cent) say it’s important organisations understand them, with 65 per cent wanting agents to resolve problems easily, it’s an impossible demand to meet without integrating intelligent solutions. Data-driven, predictive chatbots will enable companies to go beyond the average customer experience to anticipate user needs, make purchase recommendations, and offer personalised content, such as for birthdays or membership anniversaries.

For human agents, working in tandem with generative AI chatbots empowers them with the right tools they need to deliver exceptional customer service. AI-generated case summaries allow agents to prioritise cases with greater accuracy, quickly identify resolution options and even build internal knowledge base articles for future cases – all of which can save time and improve outcomes. It’s another tool to bring human agents up to speed rapidly, whether it’s a long-running issue, or taking over from a colleague.

Building in a seamless experience

Soaking up all this data enables the technology to generate knowledge-based articles and helpful information to ‘fill in the gaps’. More often than not, it means customers can self-serve and empower themselves to solve any issues that may arise during periods when an agent is offline. Customers want the path of least resistance, and chatbots can offer end-to-end support to minimise friction points.

Say a customer put in a mobile coffee order at a coffee shop but accidentally input the wrong location. Options are limited between foregoing the coffee and losing money or reaching out to the company for help. Often, people may choose the former, given the aforementioned pain point of not being understood when trying to pop in a quick request. But generative AI can make the latter the easier option.

By deploying and enhancing its self-service portal and its chat feature, users can ask open-ended questions, such as what can be done about ordering a coffee in the wrong location. The conversational AI can provide the most appropriate options which include a refund or diverting the order to the user’s preferred location. Once the customer has chosen, generative AI will act and prompt the system workflows to process the request in the back end. All without human intervention.


Transforming chatbot technology with GPT modelsTim Shepheard-Walwyn, technical director and associate partner at Sprint Reply, spoke to Information Age about how businesses can drive value from chatbot technology powered by GPT models.


Chatbots and the future

Generative AI must be an integral part of engagement strategies to help businesses achieve the scalability and agility that could only once be dreamed of. At a time when customers are tougher in defining where their loyalties lie, businesses need to take this opportunity to boost their customer lifetime value by providing exceptional customer experiences.

Gaining a better understanding of people want when dealing with a brand will allow businesses to empower employees to meet customers where they are and work in tandem with chatbots to complement their processes. Price fluctuates and can easily be forgotten, but an experience leaves a lasting impression. Delivering the service customers crave could be the difference for businesses in extremely tough conditions.

Jordi Ferrer is vice-president and general manager, UK & Ireland at ServiceNow.

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Jordi Ferrer

Jordi Ferrer is vice-president and general manager, UK & Ireland at ServiceNow.