The Role of Artificial Intelligence in the Customer Experience

GDS Modellica
Improvements to Artificial Intelligence have had a positive impact on the Customer Experience, helping to provide a more immediate, personalised and effective response to customer queries
The ability to provide an immediate and flexible response has led to the increased use of chatbots to interact with customers in an agile and efficient manner
During the pandemic, Artificial Intelligence (AI) went from being a trendy add-on to being an essential tool. Faced with confinement measures and other restrictions, companies have seen themselves forced to increasingly incorporate digital solutions into the way they work. According to KPMG, during the first three months of the pandemic, the average growth in IT expenditure by brands in the USA increased by some 5%, around $15 billion more each week.
Investment in AI has particularly focused on the Customer Experience (CX), cost optimisation and operational efficiency. By improving these three key areas, these digital solutions aim to make businesses more resilient to the challenges they face. AI programmes, in particular, have facilitated a significant leap forward when it comes to collecting and analysing data, whether it be locations, search history, times (days, dates or hours) or acquired products or services, and this information has enormous potential and value for those businesses looking to improve the way they interact with their customers and personalise the customer experience.
Data is the key to knowing customers better and automating and personalising processes. GDS Modellica lists a number of benefits and challenges involved in improving the customer experience. These include being able to provide customers with an immediate and effective response, knowing where customers spend most of their time, providing automatic responses 24 hours a day, 365 days a year, understanding customer habits, identifying weak points, improving locations and content and, finally, emulating human conversation.
The ability to provide an immediate and flexible response has led to the increased use of chatbots in order to interact with customers in an agile and efficient manner. This automated and more personalised approach ultimately provides a more fluid experience for the customer, and capturing and processing data helps to guarantee the quality of the information used. Furthermore, intelligent Robotic Process Automation (RPA) is used in many processes to improve the customer experience, achieve operational excellence and simplify the management of risks and regulatory compliance. And finally, intelligent routing helps to optimise resources, eliminate bottlenecks and above all, reduce the time and number of steps required to resolve customer queries.
For financial institutions, this type of technology can also enable advanced analytics and new risk management techniques. In particular, GDS Modellica’s High-Performance Environment provides rapid processing capabilities and high levels of data storage at lower costs, thereby providing better support for risk management decisions and process integration. In the current dynamic and complex market, lenders need to use all the available data to better understand customer behaviour. This information can then allow banks to use customer payments, spending patterns, social media activity and even online browsing to make better risk management decisions.
Ultimately, the power of AI is directed towards benefitting customers by achieving greater performance, productivity and engagement.

But as well as encouraging the adoption of new digital strategies, the pandemic has revealed new ways of connecting with each other. It has taught us the importance of interaction, emotional intelligence and empathy, and as a result, customer experiences have had to become more personalised and interconnected. AI has evolved considerably, and voice analysis has made it possible to understand customers’ feelings and emotions in real time. At the same time, speech analytics can provide real-time information about the customer. And last but not least, predictive analysis makes it possible for companies to be less reactive and more proactive in responding to their customers. With all the available knowledge, companies are showing a genuine commitment to improving efficiency and thereby increasing customer satisfaction and loyalty.
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