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The growth of the public Internet and enterprise intranets as a digital distribution mechanism for information has exploded and today one of the most promising developments is the so‐called push technology. Current push technology‐based packages deliver customised news to users' desktops, reducing the burden of acquiring and integrating data from multiple and dynamic sources. Aims to discuss the potential of push technology in integrating current techniques for evaluating IS/IT investments.

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