Spotify_User_Analysis

It's my first PowerBI project "Spotify User Analysis"

Spotify User Analysis (Churn & Ads) — Power BI + SQL + Excel

#Short description: Interactive Power BI dashboard analyzing Spotify user churn, ad exposure, and subscription behavior. Includes cleaned dataset, SQL queries used for analysis, and dashboard screenshots.

#Highlights / Key Metrics (from dashboard)

• Churned users: 2,071
• Avg ads per week: 6.94
• Churn rate:25.89%
• Active hours: 5,929
• Top churn age-group:36–50

Project Structure

• images/ — dashboard screenshots
• data/spotify_cleaned.xlsx — cleaned dataset (anonymized)
• sql/queries.sql — SQL queries used for analysis
• report/ — Power BI .pbix file (optional)

#How to reproduce

1. Open data/spotify_cleaned.xlsx to inspect the cleaned data.
2. Run queries in sql/queries.sql (adjust connection details).
3. Open report/Spotify_report.pbix in Power BI Desktop to view dashboards.

#Insights & Actionable Recommendations

1. High churn (25.9%) — target retention campaigns for high-risk cohorts (36–50).
2. Ad frequency correlated with churn — test reduced ad exposure or personalized ad capping for premium prospects.
3. Similar skip rates across genders — focus personalization by behavior/age rather than gender.
4. Next steps: predictive churn model (logistic regression), cohort LTV, A/B test ad frequency.

#Tools & Stack

• Power BI Desktop (visualization)
• SQL (ETL / aggregation)
• Excel (data cleaning)

-License This project is licensed under the MIT License — see LICENSE.

• Contact vimal — [vimalbankar702@gmail.com.com] — github.com/bankar