Subscription Lifecycle & Monetization Metrics Dataset
Group: Dataset
|Product Category: Database Design & Development
|Sub Category: PostgreSQL
About this Product
Monitor subscription trends, reduce churn, and optimize revenue streams with structured, SQL-ready subscription datasets.
Business Overview:
This dataset focuses on subscription activity and payments within a music streaming platform. It helps track monetization, plan transitions, user retention, and recurring revenue, using clean relational structures.
Product Highlights:
- Structured CSV data including
users,subscriptions,payments, andlistening history - Designed to evaluate monetization trends and retention patterns
- Ready for SQL analytics and revenue-based segmentation
- Ideal for churn forecasting and LTV modeling
Learning Outcomes:
- Analyze free-to-paid conversions and payment consistency
- Measure churn rates and average revenue per user
- Practice cohort tracking using listening activity
- Model recurring revenue logic with SQL
Resources
Tracks every listening event by users, linking them to specific songs and timestamps. This file supports session analysis, listening trends, and behavioral modeling.
Key Features:
- Granular data including
user_id,song_id, andlisten_date - Enables analysis of repeat listens, time-based usage, and user activity frequency
- Ideal for calculating daily/weekly active users, retention curves, or song popularity
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