Revenue and Retention Metrics Using DAX

Group Category: Use Case

Product Category: BI Reporting & Analytics

Sub Category: Power BI

Gain a comprehensive view of customer value, churn, and recurring revenue with this financial metrics toolkit powered by DAX.

Business Overview:

Revenue and Retention Metrics Using DAX empowers analysts to explore how much users are worth, how often they pay, and how long they stay. Using transactional and subscription data from a music streaming platform, you'll build DAX measures for monthly recurring revenue, customer lifetime value, churn rate, and ARPU. This product is ideal for financial analysts, business intelligence teams, and growth strategists looking to build revenue dashboards and retention models within Power BI.

Product Highlights:

A hands-on Power BI guide with 5 expert-level DAX use cases for financial and retention analytics
Covers churn detection, LTV, MRR, ARPU, and content-driven activity tracking
Built around real-world subscription and payment tables from a music service
Designed for revenue analysts, product managers, and Power BI experts
Helps drive pricing, forecasting, and growth strategy decisions

Learning Outcome:

By completing these use cases, you’ll gain skills in:

Calculating monthly recurring revenue (MRR) and active subscriber totals
Measuring customer lifetime value (CLTV) using time and transaction data
Detecting churn trends and tracking subscription health
Analyzing ARPU and payment activity for financial benchmarks
Building predictive indicators for retention and profitability

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subscriptions

| CSV

Description:
This dataset records user subscription lifecycles, including start and end dates.

Enables tracking of user retention, churn, and active subscription windows
Forms the basis for monthly churn rate and CLTV calculations
Supports analysis of plan stickiness, subscription duration, and attrition trends
Used in building retention dashboards and forecasting revenue stability
Links directly with payments for monetization analysis

payments

| CSV

Description:
This file logs all revenue-generating transactions made by users on the platform.

Captures payment amounts, user IDs, and transaction dates
Used to compute ARPU, MRR, and customer LTV metrics
Core to financial analysis, pricing strategy, and revenue modeling
Supports segmentation of users by payment behavior and lifetime value
Can be joined with subscription data to track monetization effectiveness

playlists

| CSV

Description:
This file tracks playlists created by users, including metadata like playlist IDs and creation timestamps.

Captures user-generated content behavior and curation patterns
Supports metrics such as playlist popularity, activity trends, and social influence
Enables tracking of creative engagement and content sharing
Helps identify potential playlist influencers or community leaders
Linked with follows and listening data for virality and engagement analysis

users

| CSV

Description:
This table serves as the central identity map for platform users, enabling user-level analysis and cross-table relationship building.

Contains user IDs, profile information, and demographic details
Enables linking listening behavior, payments, subscriptions, and playlist activity
Essential for computing user-level metrics such as lifetime value, churn, and engagement
Forms the base for audience segmentation and behavior modeling
Supports personalized recommendations and retention strategies

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