Before you examine forecasts, trends, or year-over-year comparisons, you have to understand how STR revenue numbers are generated. Raw reservation data isn’t suitable for revenue and pricing analysis — it’s built for reservation systems and accounting — and crucially, detailed pricing information usually isn’t attached to a reservation when it’s stored, and is often lost. The data has to be processed and transformed first.
Revenue sorting
Quibble organizes revenue into three buckets — Rent, Ancillary, and Tax — so each can be managed on its own. Rental revenue is the focus, since rent is the bulk of revenue and drives nightly rates; watching how booking pace responds as you change prices reveals whether the market is reacting as expected. Ancillary fees like cleaning change less often and should track real servicing costs — reasonable and commensurate with the rate, since excessive fees deter bookings.
Revenue proration
Reservations are typically stored as single-line records that attribute revenue to the booking’s first day — fine for GAAP, useless for revenue management. A revenue manager needs to know exactly how much revenue sits in April versus May, and which weekdays were booked at what prices. Quibble’s proration process distributes each reservation’s revenue across its individual booking dates, which also corrects each month’s occupancy rate.
Real-time price capture
Even prorated, one critical piece is missing: the unique price set for each day, which reservation systems don’t capture. Quibble’s Real-Time Pricing Capture (RTPC) records pricing at the calendar-day level and attaches it to prorated reservations, revealing patterns like weekend rents running well above weekday rates. Before RTPC, that data would have been lost forever.
Your revenue tells your company’s performance story — what adjustments are needed and what the future holds — but only once it’s understood at the reservation level. Quibble designs and automates that processing to feed its analytics platform.