UTILISING ARTIFICIAL INTELLIGENCE TO INVESTIGATE THE RELEVANCE OF CUSTOMER BENEFITS

Abstract

To support market success, it is important to identify customer needs, and the relation between customer needs and customer purchasing behaviour. This paper provides an overview over existing, already established approaches to determine the relevance of customer benefits. Then, an approach utilising artificial neural networks to correlate the attributes of battery electric vehicles and their sales performance is presented. This approach is discussed in relation to needs expressed by customers in surveys as well as typical user behaviour of passenger cars. It seems that, for example, charging speed of electric vehicles is more important than operational range despite customers regularly expressing operational range as their greatest concern. The presented approach can be integrated into the reference process for developing product profiles and can be coupled with drive system optimisation methods, to consider sales performance alongside vehicle performance, efficiency and costs in the early stage of product generation engineering.