The Future of Customer Service in the Digital Age
The origin of Customer Service 4.0 lies in the need to ensure that customer service remains seamless and uninterrupted across different channels in the digital age. In a world where technology and customer expectations are constantly evolving, companies are challenged to develop innovative solutions to optimise their service. Examples include chatbots, artificial intelligence, machine learning and virtual assistants, which can be used to not only handle customer queries in real-time, but also anticipate them.
The cross-channel customer experience
However, the customer service of the future is not exclusively digital! Rather, it is about meeting customers on all relevant channels, without constraints such as opening hours, physical locations, queues or the frustration of inflexible chatbots or automated phone systems. Industry leaders such as Salesforce, SAP and Microsoft provide modular systems, while central platforms enable comprehensive solution approaches. This offers users uncomplicated implementations, rapid optimisations, long-lasting economies of scale, competitive prices and seamless integration of all communication channels, which benefits them.¹
Taking personalisation to a new level
With the help of Big Data and advanced analytics tools, companies today can better understand the behaviour of their customers. According to a study by PwC¹, systems based on artificial intelligence (AI) identify customised content and implement precise next-best actions as well as next-best offers. In this way, digital service is evolving from a mere cost factor into an efficient tool for up- and cross-selling (marketing channel). At the same time, this leads to a closer integration of marketing, sales and customer service – an aspect that companies should increasingly include in their strategic and organisational planning. This enables personalised customer service that goes far beyond simple salutation by name. An example of this is personalised product recommendations, as used by platforms such as Amazon or Netflix. These companies analyse the click behaviour and preferences of customers in order to generate tailored product recommendations.
