A rule finder machine based on boosting heuristics to support managers in developing loyalty programs in retail chains

This paper shows how an AI machine can be used as an action-oriented rule finder tool to support managerial decision-making and scenario depiction. An application is given to the project and development of loyalty programs in retail chains. In this context the knowledge created from the rule finder could be very valuable to customize each retail market relation. It also discretely tracks the effectiveness of loyalty promotions giving the opportunity to adapt to possibly upcoming changes. This study based on the concept of product as a panel of attributes, can be adapted to a broader class of marketing problems.