Brands need to pay more attention to CX as most customers are willing to pay more for a great customer experience.
According to McKinsey & Company, 75% of consumers have tried a new shopping behaviour, most intend to continue doing so even when the crisis is over. To accurately predict the future of customer experience and be better prepared for the upcoming customer demands, companies should revaluate their data mining techniques. They should use data mining techniques that involve the use of statistical information, correlation and clustering.
Along with using these advanced data mining techniques, marketers can use tactics like data warehousing, decision trees and logistics regression predictive techniques to predict the future of CX. Analysing past consumer behaviour can also help brands personalise marketing efforts and be prepared for the next stage of CX – predictive customer experience.
Predictive analytics methods are set to overcome the shortcomings of traditional CX measurement. AI and machine learning, in particular, can help brands define a pattern of customer behaviour and then train algorithms to offer a seamless CX.
[5 minute read]
