Improving the customer experience (CX) is a high priority for many organizations, and rightly so. Poor service costs businesses around $4.7 trillion a year worldwide, and more than half of consumers state that they would leave a brand after just one or two negative support experiences. Empowering service agents is central to any CX strategy, but many organizations aren’t equipping their customer-facing teams with the tools they need to succeed. This is leading them to feel deflated, frustrated and burned out.
Increasing enquiry volumes, rising complexity and a lack of talent are just a few of the challenges unlikely to be solved at scale without artificial intelligence (AI) and data analytics. While the use of AI in customer experience scenarios isn’t new, the technology has been thrust into the spotlight of late. Companies are investing billions into bringing the technology to the mainstream via tools such as OpenAI’s ChatGPT, sparking fresh debates around the impact AI will have on our everyday lives.
Businesses looking to take a consumer-first approach need to understand the benefits AI and data analytics can bring to the company, and to the staff working at the heart of it. As conversations around AI have progressed in recent months, so have discussions around the impacts - both positive and negative - that it will have on our jobs. To alleviate the worry for customer service agents, it’s important that they understand what AI can bring to the world of customer service, and how it can have a positive effect on their performance to deliver a higher level of service.
AI and the customer service industry
In customer service, AI-powered support enables businesses to develop deeper insights and build a better user experience. Chatbots are one of the most popular approaches to AI in customer service, undertaking various activities such as reminding customers to check out during the purchasing process or to write reviews. Chatbots also provide 24/7 support – something we, as demanding consumers, have come to expect. Other technologies such as machine learning (ML) and interactive voice response systems are creating a new paradigm for how agents can deliver customer service.
Central to these AI models is data – they are only as good as the data they are being fed. Businesses have a huge amount of customer data at their fingertips that can be utilized to deliver a more personalized, effective experience for every consumer. By using technology to analyze this data and inform AI models, organizations can boost operational efficiency and identify opportunities, thus delivering impact at scale. Not only will this improve the employee experience, but it will elevate their service to boost the customer lifetime value (CLV).
Mahesh Ram is the Head of Digital Customer Experience at Zoom.
Empowering customer service agents with AI
It’s likely that customer service agents are already seeing the impact AI will have on their role. As a next step, they should recognize how to be empowered by it, rather than feel intimidated by the potential of the technology. This means they need to be comfortable with using AI tools and understand how the data they already possess can feed, train and make the models more accurate. Businesses should ensure they are securing buy-in from the very beginning and make the processes of implementing the technology clear.
Firstly, agents should be consulted on the intended purpose of any AI solution – whether that’s responding to consumers via a chatbot, or analyzing the data using ML to segment customers and develop predictions. Agents are at the coalface, so will know where there are gaps in their customer service strategy and how they can best be supported.
Once this is established, the primary channels need to be determined. For chatbots, for example, there is a whole range of options, from websites to social media and mobile applications. Crucially, companies shouldn’t adopt AI for the sake of it. They should only implement tools to suit their specific needs. Finally, businesses can adapt the models by training and testing. The process of training involves uploading data, such as text or images, to the AI model. The machine will improve in precision and accuracy over time – the more data it is provided, the more precise the predictions will be.
Once an agent understands how the model works and how they can improve it, they can then put it into action. At first, it’s important to ensure operations aren’t too complex – businesses can’t throw everything at the model and hope it sticks. Many customer agents know there are various repetitive aspects to their jobs which AI can take over - think of it as ‘AI in the front, human in the back’. When a customer first contacts a company for support, they’ll be met with standard qualifying questions to be answered to understand the situation and adhere to security regulations. When implemented well, AI can act as the front line, providing low-cost support while reserving the more expensive, creative, human-powered support for second-tier escalations or more sensitive topics.
By using AI to solve basic mundane queries, it will build the foundational knowledge to ensure it is learning from the initial interactions. As it continues to train, businesses can test it out to see how it meets the needs of their customers, while agents simultaneously build rapport and digital empathy to elevate the quality of service.
Advantages of AI-powered customer service
According to Accenture, 64% of consumers wish companies would respond faster to meet their changing needs, but 88% of executives think their customers are changing faster than their business can keep up. Implementing AI models gives organizations the power to be one step ahead. By its very nature, AI can handle and process large amounts of data in seconds. As a result, businesses are delivered key insights about their customers and can use this to offer a more personalized level of service or pinpoint the most common issues or complaints. With this data, organizations can also predict future trends, such as optimal staffing levels during busy periods or whether or not a new product will be successful.
Customers are becoming increasingly empowered by their self-service experience with accessibility at the touch of their fingertips, and their first AI-powered encounter with a business will set the tone for the rest of their customer journey. AI can help businesses reduce average handling times, as they can answer basic enquiries and requests immediately, often without having to involve an agent at all. If they’re a returning customer, conversational AI can provide forecasting abilities and offer agents recommendations based on historical data so agents can further refine their approach for a more personalized service. This helps allocate resources to minimize friction while driving higher revenue. McKinsey found that nearly two-thirds of companies that decreased their call volumes identified improved self-service as a key driver. The ability to have issues resolved efficiently and swiftly is central to building a loyal customer base. In our digital hybrid world, it’s never been more important to ensure the customer journey is as frictionless as possible.
Great customer experience is a table-stakes consumer expectation. Competition is rife, and all it can take is one negative experience for a customer to jump ship. By empowering agents with AI, businesses can provide optimised recommendations, reduce friction, drive revenue and retain customers, all the while enabling agents to focus on higher-value tasks. Training and correct implementation will help customer service agents feel supported and empowered by AI, rather than threatened by it, to help unlock the full benefits of a digitised customer service operation.
