# Property Portfolio Profitability Review

## Business question
**The portfolio is making money. Is it making enough?**

A synthetic property-management analytics case study designed to show how I would move from operational data to an owner-facing decision.

## What this demonstrates
- Property-level performance analysis
- Occupancy vs. ADR tradeoff analysis
- Contribution / revenue-leakage analysis
- Property prioritization
- Simple PostgreSQL-style SQL
- Data dictionary and modeling assumptions
- Translating metrics into practical owner decisions

## Core recommendations in the case
- **P05:** test pricing because demand is strong while ADR is low.
- **P06:** investigate turnover/cleaning economics because ADR is strong but operating cost is high.
- **P09:** diagnose demand and cancellations before making a blanket pricing change.

## Method
The simulation uses a 30-day window. The page and SQL use the same calculation logic. Booked nights are adjusted for cancellation rate. Gross revenue is modeled as booked nights × ADR. Contribution is simplified to revenue less a 3% platform fee and modeled cleaning/turnover cost. Cleaning is modeled as one turnover per three booked nights.

## Important limitation
This is synthetic portfolio data created for portfolio demonstration. It is not real client data and is not a complete property P&L.

## Files
- `index.html` — interactive case study
- `data/property_monthly.csv` — synthetic input data
- `data/data_dictionary.csv` — field definitions
- `sql/property_performance.sql` — performance query
- `sql/property_profitability.sql` — profitability query
- `sql/underperformers.sql` — prioritization query
- `README.md` — project notes
- `Property_Portfolio_Profitability_Case_Study.pdf` — printable case-study summary