AI
“Business leaders need to proactively engage with the ongoing discussions around AI and be transparent on how the technology will impact their workforce.”
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 analysing 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. Tey should only implement tools to suit their specific needs. Finally, businesses can adapt the models by training and testing. Te process of training
involves uploading data, such as text or images, to the AI model. Te 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.
Why AI delivers results Staying ahead of customer demands is increasingly difficult in today’s business environment. Research by Accenture suggests that 64% of consumers want companies to respond faster to their requirements, but most executives (88%) think customers’ needs are changing too quickly for their businesses to keep up. It’s here that AI can give business leaders an edge, handling and processing huge amounts of data in seconds. Tis delivers key insights at the right moment, enabling organisations to offer a more personalised level of service, or pinpoint common complaints and deal with them in real time. Te data delivered by such systems can also help business leaders anticipate future trends, such as peak times when more staff will be needed, or even whether a new product will succeed. Customers also want self-service and their queries answered
instantly - AI can deliver both. Oſten a customer’s first encounter with a business will be AI-driven, setting the standard for the rest of their journey. AI can also help to reduce average wait times by utilising the data the model has been trained with to answer basic questions and respond immediately. In fact, nearly two-thirds of companies that have decreased their call volumes say that improved self-service was a key driver of this. With returning customers, conversational AI can offer agents recommendations based on previous data, allowing them to refine their approach. Tis all makes for a more tailored service, helping organisations to improve customer retention and drive higher revenues. Today’s customer journeys need to be as frictionless as possible,
as one negative experience is all it can take for a customer to jump ship. By empowering agents with AI, they can deliver the sort of personalised, responsive service that makes customers stay. Implemented correctly, alongside training, customer service agents will feel supported by AI, allowing them to focus on higher- value tasks. Bringing people and technology together in this way will unlock the benefits of a fully digitised, data-driven customer service operation.
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