Reversing an 18% Airbnb Revenue Drop
Diagnosing profitability gaps for RevBoost across five U.S. cities with Tableau and predictive analytics.
Result: High operating costs, static pricing and weak customer targeting caused the decline. Miami's cost-efficient model became the benchmark for the other cities.
Goal
RevBoost's Airbnb portfolio in Chicago, Los Angeles, New York, Miami and San Francisco lost 18% of its revenue in Q1 2024. The goal was to find the cost, pricing and marketing inefficiencies behind the drop and build a data-driven plan to restore profitability.
Approach
- Tableau: Visualized regional profitability, spending behavior and cost breakdowns.
- Regression & Excel modeling: Isolated pricing inefficiencies and cost drivers.
- Scenario simulation: Generated realistic financial scenarios with ChatGPT to stress-test strategic options.
Recommendations
- Adopt dynamic pricing algorithms.
- Cut costs through bulk purchasing.
- Refocus marketing spend on higher-value customer segments.