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 language | English |
|---|---|
| Title of host publication | 2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC) |
| Publisher | IEEE |
| Number of pages | 3 |
| Volume | Piscataway, NJ |
| ISBN (Electronic) | 9781538623657 |
| DOIs | |
| Publication status | Published - 15 Jan 2018 |