Hera Hotel · Athens
Hera Hotel: forecasting demand for the off-season
The booking data was already there. What was missing was a view of demand before the off-season arrived.
- Sector
- Boutique hotel
- Services
- Demand Forecasting · Business Intelligence
- Tools
- Excel · SQL · Python · Power BI
The problem
Hera Hotel is a boutique hotel in Athens. Like most independent hotels, it already had the data it needed: bookings, rates, channels, occupancy. But that data sat in separate systems and in reports that only looked backwards.
The off-season was planned reactively. Decisions on rates and offers were made once low demand had already shown up, not before.
Together with management, we set three goals:
- Forecast demand better
- Grow revenue and occupancy through decisions based on data
- Get a clearer view of the guest experience
What we built
- Analysis of 4+ years of booking data. Lead time, cancellations and seasonality, to show how demand really moves through the year.
- A week-by-week time-series demand model. The team sees where demand is heading weeks in advance.
- Off-season patterns. When, and at what rate, it makes sense to open offers.
- A live Power BI dashboard. Booking pace, pick-up and alerts when bookings fall behind, in a format the whole team can read without technical skills.
The work started from the core indicators (revenue, bookings, capacity, occupancy) and was built up step by step to the forecast.
The outcome
The off-season is no longer planned blind. Management sees booking patterns before they become a problem and decides on rates and offers from its own data.