Pricing Intelligence Engine
Thousands of signals.
One smarter price.
HostMetric's pricing methodology combines property-level, historical and market-level data to estimate demand conditions and support dynamic pricing decisions designed to improve revenue performance.
Comparable Properties
Similar accommodation type, location, capacity, amenities, positioning and market segment provide competitive pricing context.
Local Market Demand
Seasonal patterns, local demand conditions and differences between high- and low-demand periods influence expected willingness to book.
Historical Booking Data
Historical reservations, observed rates, lead time and booking patterns create a baseline for analysing future demand.
Booking Pace
Pickup velocity measures how quickly future nights are being reserved relative to previous comparable periods.
Revenue KPIs
ADR, occupancy and revenue-per-available-inventory metrics help evaluate the balance between price and inventory utilization.
Price Elasticity
The relationship between price changes and expected demand provides information about how aggressively a rate can be adjusted under different market conditions.
Optimization Objective
Not maximum occupancy.
Maximum economic performance.
A property filled at an unnecessarily low rate may achieve strong occupancy while leaving revenue on the table. The pricing engine therefore evaluates rate and expected demand together, adjusting recommendations as booking pace, remaining inventory and market conditions change.