Pricepoint's pricing intelligence isn't a simple set of rules (e.g., "+10% when occupancy hits 80%"). It behaves more like an always-on revenue manager: it gathers data, runs forecasts and simulations, and continuously searches for the price with the highest probability of success at any given moment.
Rather than changing prices once per day or following fixed steps, Pricepoint recalculates after every relevant signal — a new booking, a market shift — taking into account a range of factors:
Demand & Pace
Measures how quickly bookings are coming in for each date, relative to what's typical for that date at that point in the booking window.
Pricepoint AI looks at:
How many beds/rooms have been sold so far
How fast they’re selling compared to typical patterns
Whether current pick-up is ahead of or behind where it “should” be.
This helps determine whether current demand will reach target occupancy at the right price, or whether pricing needs to adjust to speed up or slow down sales.
Occupancy & Inventory Pressure
Occupancy isn't just “high” or “low”. Pricepoint evaluates:
Current occupancy for each date and room type
How this level compares to expected occupancy at this stage
How much inventory is left and how many opportunities remain to sell it
A date at 80% can be “too full” (if it's early and demand is still strong) or “not full enough” (if it’s last-minute). The AI adjusts based on that context.
Booking Window & In-Window Seasonality
Booking window is more than “far out vs last minute”. Pricepoint analyzes:
How far in advance guests typically book each specific date (e.g. Saturday vs Monday, holidays vs low season).
Where today falls on that booking curve.
Whether guests for that date normally book early, steadily, or very late.
This helps align today's price with the real booking behavior for that specific date, rather than a generic rule.
Event & Local Demand
The AI evaluates scheduled and unscheduled demand drivers around your property, such as:
Conferences, concerts, sports events, festivals
Public holidays, long weekends, school breaks.
Spikes in pick-up that may indicate local events not otherwise on record
When demand is clearly above or below normal, Pricepoint adapts to capture extra revenue or stimulate demand accordingly.
Market Trends & Compset Behavior (only applies if you have competitors configured in Rate Shopper)
If you have competitors set up in Rate Shopper, Pricepoint also considers market context as part of its pricing:
Price trends across nearby properties
How your compset is moving for the same dates (up, down, or flat)
Whether your current position makes sense given your product and segment.
This factor doesn't apply if you don't have competitors configured. See Setting Up Rate Shopper to add competitors.
Real-Time Demand Signals & Micro-Trends
Beyond pace and known events, Pricepoint also tracks day-specific anomalies that don't fit an expected pattern. It looks at real-time demand signals such as:
Sudden changes in search activity and pick-up across channels
Micro-trends for specific dates (e.g. one Friday behaving very differently from another)
Patterns unique to each date, rather than a single average pattern.
Rather than assuming demand is a smooth line, Pricepoint learns the complex demand curve and constantly adjusts as new data comes in.
Price Sensitivity & “What-If” Simulations
Instead of applying a fixed percentage adjustment, Pricepoint runs scenario comparisons:
"What if price increases by 2, 4, or 7?"
“What happens to expected occupancy and revenue under each scenario?”
It estimates how sensitive demand is to price for each day and room type, and then selects the price that maximizes expected revenue, not just occupancy or ADR alone.
Live Price & Demand Interaction
Being competitive on OTAs and marketplace platforms doesn't mean being the cheapest. It means:
Having a price that makes sense for your quality, date, and market
Understanding how that price is performing against actual demand
Pricepoint looks at how your live prices interact with real booking demand on distribution channels, using that signal as part of its pricing decisions.
Minimum Price & Hurdle Logic
Traditional revenue management systems use a separate "hurdle rate" or Last Room Value (LRV) to decide which rates to open or close. Pricepoint doesn't calculate a separate hurdle value — that logic is built directly into the pricing engine. Every price already reflects the same underlying question a classical hurdle model would ask: sell now, or hold out for higher-value demand?
The minimum price in Pricepoint works differently:
It is defined by the property, not by the algorithm.
It acts as a business safeguard for brand and profitability.
It is intentionally excluded from optimization.
Pricepoint will never recommend below your minimum — pricing decisions stay within your defined floor, while the AI optimizes freely above it.
Rather than making a binary open/close decision like older hurdle models, Pricepoint continuously estimates what guests are likely to pay by analyzing:
Current and forecasted demand
Booking pace and pick-up trends
Remaining inventory and time to stay date
From this, it calculates the price that best balances occupancy, ADR, and total revenue, within your minimum and maximum boundaries.
Property Strategy & Constraints
Pricing always operates within your defined boundaries:
Minimum and maximum prices
Length-of-stay and restriction rules
Segmentation (non-ref vs refundable, early-bird vs last-minute, etc.)
Revenue and occupancy priorities
Data Quality & Factor Visibility
The weight given to each factor depends on your account configuration, market, and the quality of available data (market, compset, channel data, etc.). If data is noisy, incomplete, or unreliable, Pricepoint automatically down-weights or excludes it rather than acting on it.
Key Takeaway
By combining these factors, Pricepoint:
Monitors demand and market conditions continuously
Runs simulations rather than following fixed rules
Uncovers patterns and micro-trends that would be difficult to track manually
The result is accurate, data-driven, real-time pricing that aligns with your property's goals and the actual dynamics of your market.