Group Category: Dataset
Product Category: Database Design & Development
Sub Category: PostgreSQL
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
Stores subscription records including type, start and end dates for each user. This file supports lifecycle tracking, churn detection, and plan-based segmentation.
Key Features:
- Includes
user_id,subscription_type, and validity dates - Helps identify active, cancelled, and expired subscriptions
- Core for revenue modeling and retention analysis
Records all monetary transactions made by users, including amount, method, and date. Essential for financial reporting and revenue analytics.
Key Features:
- Links users and subscriptions to payment data
- Tracks
amount,payment_date, andpayment_method - Enables MRR/ARR calculation and LTV segmentation
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
Contains registered user information including personal identifiers, contact details, and subscription types. This file supports user segmentation, onboarding analysis, and account-based filtering.
Key Features:
- Records core user attributes such as
user_id,username,email, and subscription type - Can be used to group users by plan type (e.g., free vs paid)
- Ideal for building user cohorts or joining with behavioral or transactional tables
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