Showz is a global event ticketing platform. This project serves as a comprehensive Business Analytics audit to determine the efficiency of their marketing investments. By analyzing user sessions, order logs, and advertising costs, I identified critical leaks in the marketing budget and proposed a high-impact reallocation strategy.
The analysis was divided into three core pillars of performance:
- Calculated DAU, WAU, and MAU to understand user retention.
- Analyzed Average Session Duration (ASL) and Sticky Factor to measure platform addiction and return rates.
- Cohort Analysis: Tracked the time elapsed between the first session and the first purchase.
- LTV (Lifetime Value): Calculated the total revenue generated by users over time to determine their long-term value.
- CAC (Customer Acquisition Cost): Breakdown of costs per source.
- ROMI (Return on Marketing Investment): Identified which channels were burning cash and which were generating profit.
- The "Source 3" Red Flag: This channel received the highest investment (USD 141,321) but yielded a negative ROMI of -61.43%.
- Hidden Gems: Sources 1 and 2, despite having higher CAC, bring in high-value customers with positive ROMIs (+49.24% and +9.61%).
- Device Gap: Desktop users outperform "Touch" (mobile) users significantly. Touch devices show a staggering -56.56% ROMI, indicating a poor mobile conversion experience.
- Stop the Bleeding: Immediately pause investment in Source 3 and re-evaluate the UX for Touch devices.
- Scale Winners: Reallocate the recovered budget from Source 3 into Sources 1, 2, and 9.
- Investigate Source 7: Analyze why this "zero-cost" source is performing so well to replicate its success organically.
- Language: Python
- Libraries: Pandas (ETL & Cohorts), NumPy (Calculations), Seaborn/Matplotlib (Visual Analytics).
- Techniques: Cohort Analysis, Unit Economics (LTV, CAC, ROMI).