Planet Fitness - Roswell Alpharetta Gym Performance Analysis

Introduction

Welcome to the Planet Fitness - Roswell Alpharetta Gym Performance Analysis repository. This project delves into the performance of the Planet Fitness gym located in Roswell Alpharetta, highlighting areas of underperformance compared to nearby competitors. Through data analysis and forecasting, we aim to identify opportunities for improvement and provide actionable recommendations to enhance the gym's performance.

Overview

This project utilizes a data-driven approach to analyze various aspects of the gym's performance, including customer acquisition, activation, retention, referral, and revenue. By leveraging the AARRR framework (Acquisition, Activation, Retention, Referral, and Revenue), we aim to gain insights into key metrics and develop strategies for improvement.

Data Analysis

The project involves extensive data exploration and visualization to uncover insights into customer behavior, preferences, and trends. We analyze factors such as foot traffic patterns, demographics of visitors, customer feedback, and facility conditions to identify areas of strength and weakness.

Key Insights from Data Analysis

• Competitive Landscape: Nearby competitors include another Planet Fitness with better facilities and a Crunch Fitness located in the same shopping area.
• Customer Feedback: Negative reviews mention theft, homeless individuals, and poor customer service, impacting customer satisfaction and retention.
• Visitor Behavior: Visitors stay on average 25 min at the underperforming gym compared to almost 50 min at competitors, indicating dissatisfaction with amenities and services.

Data Forecasting

In addition to retrospective analysis, this project involves forecasting future performance based on historical data trends and market dynamics. We utilized machine learning models to predict gym visitor counts for different locations.

Forecasting Results

Milton Gym:

• Linear Regression: MSE of 14580.08
• Random Forest: MSE of 15348.06
• Neural Network: MSE of 23766.88 (More details about model performance and interpretation)

Woodstock Gym:

• Linear Regression: MSE of 51991.50
• Random Forest: MSE of 51145.39
• Neural Network: MSE of 56525.90 (More details about model performance and interpretation)

Roswell Gym:

• Linear Regression: MSE of 39674.90
• Random Forest: MSE of 36798.62
• Neural Network: MSE of 43643.06 (More details about model performance and interpretation)

Underperforming Roswell Gym:

• Linear Regression: MSE of 24191.68
• Random Forest: MSE of 20758.33
• Neural Network: MSE of 33002.04 (More details about model performance and interpretation)

Repository Structure

• Data: Contains datasets used for analysis and forecasting.
• Notebooks: Jupyter notebooks documenting data analysis, visualization, and forecasting methodologies.
• Reports: Reports summarizing key findings, insights, and recommendations.
• Presentations: Presentation slides for communicating analysis results to stakeholders.
• Scripts: Python scripts for data preprocessing, modeling, and visualization.

Conclusion

By leveraging data analysis and forecasting techniques, this project aims to provide actionable insights and recommendations to enhance the performance of the Planet Fitness gym in Roswell Alpharetta. Continuous monitoring and adaptation based on data-driven insights will be crucial for achieving long-term success and maintaining a competitive edge in the fitness market.

Please see report for more details