AI Hotel Revenue Analysis Tool

What this export contains

What usually goes wrong with it

• RevPAR requires combining occupancy and ADR which are in separate export columns

  RevPAR = ADR × Occupancy Rate, but occupancy is often calculated from a separate rooms-available figure that isn't in the reservation export, requiring a manual step before the calculation works.

  DataMimi Datamimi calculates RevPAR from ADR and Occupancy Rate columns when both are present, or from room rate and rooms-available figures if the raw components are in the file.

• Multiple booking channels export in different formats

  OTA exports (Booking.com, Expedia) use different column names and date formats than the property's own PMS export, making channel comparison require manual column mapping.

  DataMimi It normalizes column names from multiple booking channel exports and answers channel-comparison questions across them.

• Cancelled reservations remain in the export and inflate revenue totals

  Unless explicitly filtered out, cancelled bookings with a non-zero room rate appear in revenue calculations, overstating actual realized revenue.

  DataMimi It filters cancelled bookings from revenue calculations when a Status or Cancellation column is present.

• Length of stay spans across month-end boundaries

  A guest who arrives January 28 and checks out February 3 has revenue that should be split across two months, but most PMS exports attribute the full stay to the arrival month.

  DataMimi It handles multi-month stays by attributing revenue to arrival date by default and noting when a different allocation method is needed.

• Seasonal comparison requires year-over-year data alignment

  Comparing this August to last August requires aligning two files by arrival date rather than export row order, which breaks simple column-to-column comparison.

  DataMimi It aligns year-over-year files by Arrival Date and answers seasonal comparison questions across both files.

Common questions