Providing a personalised service experience using artificial intelligence
Jan H. Blümel and Mohamed Zaki. Providing a personalised service experience using artificial intelligence. In Kristensson, Per; Witell Lars, and Zaki, Mohamed (Eds.), Handbook of Service Experience. UK:Edward Elgar Publishing.
Summary
In the digital age, personalised customer service is becoming increasingly crucial, yet challenging, due to the automation and digitisation of customer interactions. Personalised customer service, which focuses on emotional needs and the establishment of social relationships, is essential for enhancing customer satisfaction, loyalty, and engagement. Studies have shown that customers greatly value personal interactions over standardised digital communications, which significantly impacts a company's ability to retain customers and sustain a competitive advantage.
To bridge the gap between automated services and the need for personal interaction, a framework for employing conversational AI effectively is introduced. This framework comprises four key steps: contextualisation, conversation style, delegation, and training. Contextualisation involves tailoring interactions based on understanding the customer's current emotional and social state. The conversation style should appropriately balance task-oriented and emotionally enriching communications, incorporating empathy and, when suitable, humour to connect on a more personal level.
Delegation is critical when a conversation needs to transition from AI to a human agent. This step should be smooth and informed by the AI's understanding of the customer’s needs, ensuring that the personal touch is not lost. Training involves continually updating the AI with high-quality data that reflects specific contexts and customer interactions, enhancing its ability to manage complex emotional responses.
The chapter also explores the potential roles of emerging technologies like the metaverse, generative AI, and Web 3.0 in the evolution of customer service. The metaverse promises immersive environments that could redefine customer interaction spaces, while generative AI could further personalise customer service through refined language and response generation. Web 3.0 offers enhanced privacy and control over personal data through decentralised management, potentially increasing customer trust and data security.
However, these technologies also face significant challenges, including maintaining emotional accuracy, protecting customer privacy, and ensuring accessibility across diverse customer bases. A discussion in the chapter highlights the necessity of these advanced technologies for maintaining personalisation in customer service while also considering the ethical implications and operational challenges they present.
Overall, the focus is on how AI and emerging technologies can be leveraged to sustain and enhance relational personalisation in customer service, ensuring that businesses can provide meaningful and engaging customer experiences even within increasingly digital frameworks.
