Cognitive analytics management of the customer lifetime value: an artificial neural network approach

Purpose The purpose of this study is to show that the use CAM (cognitive analytics management) methodology a valid tool describe new technology implementations for businesses. Design/methodology/approach Starting from dataset recipes, we were able consumers through variant RFM (recency, frequency and monetary value) model. It has been possible categorize customers into clusters measure their profitability thanks customer lifetime value (CLV). Findings After comparing two machine learning algorithms, found out self-organizing map better classifies base retailer. algorithm was extract three described as personas using values scores Research limitations/implications results are strictly applicable retailer which provided data. Practical implications Even though, can produce useful information designing promotional strategies improving relationship between company customers. Social Customer segmentation an essential part marketing process. Improving further methods allow even small medium companies effectively target deliver society they offer. Originality/value This paper shows application guide implementation adoption based on CLV.