🎧 Spotify Churn Prediction & Engagement Analysis (2025)

🌟 Project Overview

This project focuses on Exploratory Data Analysis (EDA) and data transformation to understand user engagement patterns and customer churn for a simulated Spotify dataset. The analysis was initially performed using Google Sheets and is now documented and stored here on GitHub.

The primary objective is to identify key factors leading to customer cancellations and provide actionable insights to help Spotify reduce its churn rate.

🎯 Key Objectives

1. Data Transformation: Clean and structure the raw dataset for analysis.
2. Dashboard Creation: Develop a data visualization dashboard (initially in Google Sheets) to display key performance indicators (KPIs) and churn drivers.
3. Result Analysis: Analyze engagement metrics, subscription types, and device usage to pinpoint high-risk user segments.

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💾 Dataset Information

Column (Feature)	Description	Data Type
user_id	Unique identifier for each user.	int64
gender	User gender (Male/Female/Other).	object
age	User age.	int64
country	User location (e.g., US, CA, AU).	object
subscription_type	Type of Spotify subscription (Free, Premium, Family, Student).	object
listening_time	Minutes spent listening per day.	int64
songs_played_per_day	Number of songs played daily.	int64
skip_rate	Percentage of songs skipped (engagement metric).	float64
device_type	Device used (Mobile, Desktop, Web).	object
ads_listened_per_week	Number of ads heard per week.	int64
offline_listening	Binary indicator for offline mode usage (0/1).	int64
is_churned**	Target Variable (0 = Active, 1 = Churned).	int64

• Total Rows: 8,000
• Source: Spotify Analysis Dataset 2025 on Kaggle
• Author: Nabiha Zahid

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📁 Repository Structure

This repository is structured to mirror the workflow used in the Google Sheets analysis:

File Name	Corresponds to	Description
data	Raw Data	The original synthetic dataset used for the project.
analysis_summary.md	Data Transformations & Results	Documentation detailing the methodology, calculations, and analytical results .
dashboard_visual.png	Final Dashboard	A static image of the complete data dashboard created for visualization.
README.md	Project Overview	This introductory document.

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🔗 Accessing the Dashboard

You can explore the final visual output and interactive elements in two ways:

1. Original Google Sheets File (Live Dashboard): ➡️ View the Live Dashboard

2. Dashboard Static Image: The general layout and metrics are visible in the static image file:

   (Refer to the dashboard_visual.png file for the full dashboard view.)