Customers’ ranking inabilities in optimizing customer journeys

This paper is an introduction in how customer satisfaction and customer journeys can be optimized using ranked preferences of customers. Individuals are asked to rank similar alternatives from most preferred to least preferred. Due to the complexity of providing a complete ranking, one needs to deal with the ranking inability of the individuals. The latent-class rank-ordered logit model will be considered for estimating the preferences efficiently, keeping in mind the ranking inabilities of individuals. The model uses latent segments to recognize the ranking abilities of individuals. The latent-class rank-ordered logit model will be applied on two datasets about gaming platforms to obtain how this model can be implemented in a practical way for an electronic company and how this model can help improving the customer satisfaction and optimizing the customer journeys.