A bi‐objective procedure to deliver actionable knowledge in sport services. Issue 6 (10th August 2020)

• Record Type: Journal Article
• Authors: Pinheiro, Paulo; Cavique, Luís
• Other Names: Gonzalez‐Pardo Antonio guestEditor.; Tallón‐Ballesteros Antonio J. guestEditor.; Yin Hujun guestEditor.; Cortez Paulo guestEditor.; Bifet Albert guestEditor.
• Is Part Of: Expert systems. Volume 37:Issue 6(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-08-10
• Subjects: actionable knowledge -- business utility -- retention intervention -- sport services; Expert systems (Computer science); 006.33
• DOI: 10.1111/exsy.12617
• Languages: English
• ISSNs: 0266-4720

Abstract

Abstract: The increase in retention of customers 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 that uses the following pipeline (data collection, predictive model and retention interventions). In the first step, it extracts and transforms existing real data from databases of the sports facilities. In the 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 associated cost are measured. This document presents a bi‐objective study in order to choose the more efficient scenarios.