Hotel Pricing & Inventory Model

Project Overview

During my time at Datawealth, I developed predictive models to optimize hotel pricing strategies and inventory management.

Key Outcomes

• Pricing Model: Achieved 85% accuracy (15% MAPE). This model analyzed historical booking data, seasonality, and competitor pricing to recommend optimal room rates.
• Inventory Management: The Proof of Concept (PoC) model achieved 94% accuracy, helping to predict room demand and prevent overbooking or under-utilization.
• Impact: These tools allowed tactical pricing strategies that directly contributed to revenue growth and cost reduction.

Dashboards & Analytics

Beyond modeling, I engineered self-service analytics dashboards. These tools empowered non-technical stakeholders to independently generate reports and monitor operational performance across various business units.

Technologies Used

• Python (Pandas, Scikit-learn)
• SQL for data extraction.
• Visualization Tools for dashboards.