Churn prediction model for effective gym customer retention

Jas Semrl, Alexandru Matei

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    In the fitness industry, rolling gym membership contracts allow customers to terminate a contract with little advanced notice. Customer churn prediction is a well known area in Machine Learning research. Many companies, however, face a data science skills gap when trying to translate this research onto their own datasets and IT infrastructure. In this paper we present a series of experiments that aim to predict customer behaviour, in order to increase gym utilisation and customer retention. We use two off-the-shelf machine learning platforms, so that we can evaluate whether these platforms, used by non ML experts, can help companies improve their services.
    Original languageEnglish
    Title of host publication2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC)
    PublisherIEEE
    Number of pages3
    VolumePiscataway, NJ
    ISBN (Electronic)9781538623657
    DOIs
    Publication statusPublished - 15 Jan 2018

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