Phoenix, Arizona
The starting point
A two-bedroom rental with Superhost status was using PriceLabs with near-default settings. The project reviewed how its pricing rules responded to demand, booking activity and gaps in the calendar.
What changed
Price positioning
Reviewed the base price, reported as moving from $115 to $128, and the relationship between pricing and market demand.
Demand-responsive settings
Reviewed seasonality, booking-recency adjustments and occupancy-based pricing rather than relying on outdated manual discounts.
Stay rules and gaps
Revisited minimum stays and enabled one-night orphan-gap availability where appropriate. These settings were specific to this property, not universal recommendations.
Reported performance
| Reported metric | Before | After | Change |
|---|---|---|---|
| Total revenue | $2,159 | $3,124 | +$965 / +44.7% |
| Booked nights | 17 | 22 | +5 / +29.4% |
| Average daily rate | $127 | $142 | +$15 / +11.8% |
The supplied revenue totals show an increase of approximately 44.7%, correcting the original 43% revenue headline. Both booked nights and the reported average daily rate increased. The revenue totals reconcile with the reported nights multiplied by ADR in each period.
What the comparison also shows
The original report also lists occupancy moving from 58% to 74% and RevPAR from $73.66 to $105.08. Those occupancy figures do not align with 17 and 22 booked nights out of 30, so occupancy and RevPAR are not used as headline results here. Availability definitions and calendar dates need confirmation before those measures can be compared reliably.
The practical lesson
Connecting a pricing tool is the starting point. Its configuration should reflect the property, its calendar and its operating constraints, with performance reviewed after changes.
Prepared by STR Booster from the supplied project case study. Individual results are not a forecast or guarantee.