Market Intelligence

Rockbuster Revenue & Market Analysis

SQL-driven market intelligence for a phased streaming launch strategy

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Overview

Developed a market prioritization framework for Rockbuster Stealth's transition from physical rentals to streaming. Using complex SQL queries across a 15-table relational PostgreSQL database, I calculated customer lifetime value by geography, analyzed revenue by genre, and designed a phased rollout strategy targeting 108 countries.

Business Problem

Rockbuster Stealth needed to decide where to launch its streaming service first, which content to license, and how to allocate a limited marketing budget across global markets.

Business Objectives

  • Prioritize launch markets
  • Identify revenue-driving content
  • Target highest-value customers
  • Optimize rollout investment

Data

  • 15-table relational PostgreSQL database
  • 599 customers across 108 countries
  • Rental and payment history

Analytical Approach

Used multi-table JOINs across the full schema, CTEs, subqueries, and window functions to calculate CLV by geography, revenue by genre and rating, and build a market prioritization framework.

Horizontal bar chart showing total revenue by genre
Sports, Sci-Fi, and Animation lead genre revenue, guiding content licensing priorities for the streaming launch.

Key Findings

Bar chart showing top 10 customer countries led by India, China, and United States
India (60), China (53), and the U.S. (36) represent the highest customer concentration, forming the Tier-1 launch markets.

Top Insights

  • India, China, U.S. = ~40% of customers → Tier-1 launch markets
  • Sports, Sci-Fi, Animation generate 20% higher revenue per rental
  • High-value customers distributed globally (not concentrated in one region)
  • Customer concentration enables phased Tier-1 rollout before broader expansion

Business Impact

Global customer distribution map and business impact summary
High-value customers are distributed globally. Launch strategy must balance customer density with CLV.

Revenue Impact

  • Prioritize launch in highest-density markets (India, China, U.S.)
  • Lift ARPU via high-performing genres (Sports, Sci-Fi, Animation)
  • Increase CLV through targeted acquisition

Cost Efficiency

  • Allocate 60% of budget to Tier-1 countries
  • Reduce spend in low-ROI long-tail regions
  • Replace broad global campaigns with focused rollout

Phased launch limits capital exposure and de-risks expansion with data-backed market prioritization.

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For a full technical breakdown including code, queries, and methodology, view this project on GitHub.

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