Pinheiro, PauloCavique, Luís2020-11-182020-11-182020-081468-0394http://hdl.handle.net/10400.2/10178The increase in retention of customer in gyms and health clubs is nowadays a challenge that requires concrete and personalized actions. Traditional data mining studies focused essentially on predictive analytics, neglecting the business domain. This work presents an actionable knowledge discovery system which uses the following pipeline (data collection, predictive model, retention interventions). In the first step, it extracts and transforms existing real data from databases of the sports facilities. In a second step, predictive models are applied to identify user profiles more susceptible to dropout, where actionable withdrawal rules are based on actionable attributes. Finally, in the third step, based on the previous actionable knowledge some of the values of the actionable attributes should be changed in order to increase retention. Simulation of scenarios is carried out, with test and control groups, where business utility and associate cost are measured. This document presents a bi-objective study in order to choose the more efficient scenarios.engActionable knowledgeRetention interventionBusiness utilitySport servicesjournal articlehttps://doi.org/10.1111/exsy.12617