Rye Alyanna
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Predict Fitness Usage for ACLO
Project type
Business Analysis and Predicting
Date
March 2025 - April 2025
Skills
Python, Exploratory Data Analysis (EDA), Data visualization, Data Cleaning, Statistical Modeling, Machine Learning Pipelines, Data Analysis Pipelines, Model Evaluation, RNNs
Link
Link
The primary goal of this project is to develop a predictive model for fitness visitor numbers at the ACLO Sports Centre (ACLO is the primary student sports organization in Groningen, Netherlands).
By leveraging historical fitness usage data spanning from 2017 to 2021, this analysis aims to quantify the influence of various internal and external factors on fitness attendance. Specifically, the project will investigate the impact of season, holiday periods, the day of the week, gender, educational institution (University of Groningen vs. Hanze University of Applied Sciences), and exam periods on fitness usage.
The project also explores the impact of external events such as COVID-19 lockdowns and weather conditions. The ultimate objective is to provide the ACLO with actionable insights that can inform their marketing strategies for the Fitness Card and contribute to informed decisions regarding future service offerings.
