Booking pace (pickup) is one of the best leading indicators for dynamic pricing. It tells you how quickly a future stay date is building, so you can adjust rates while there's still time for the market to react.
Quick glossary shortcuts
- Booking Pace and Pickup: what they mean and how they're measured
- Booking Window: why lead time changes pricing decisions
1) Pace vs pickup vs forecast: know what you’re looking at
The terms are often used interchangeably, but separating them makes your decisions more reliable:
- On-the-books: what you've already sold for the date.
- Pickup: how many new room nights were added for the date in a period (e.g. last 7 days).
- Booking pace: pickup interpreted against a baseline (last year, typical seasonality, patterns).
- Forecast: your best estimate of the final outcome (occupancy, ADR, RevPAR), using pace and other inputs.
The most common mistake is reacting to a single pickup movement without context. Pace becomes useful only when you compare it to a baseline.
2) Build a baseline in 10 minutes
For most independent hotels, the simplest minimum is a combination of YoY and recent weeks:
- Choose a horizon: next 30/60/90 days (based on your booking window).
- Compare on-the-books and pickup to the same day of week last year (not just the same date).
- Compare to the average pickup of the last 3–4 weeks (by stay date).
- Flag 10–20 "action dates": the biggest deviations (strong or weak pace).
To connect pace to revenue, pair it with the core metrics. Start with RevPAR, ADR, and occupancy and use the RevPAR calculator.
3) Validate the signal (avoid false alarms)
Before you change rates, check whether the pace deviation reflects real demand or just noise:
- Cancellations: strong pickup plus strong cancels can indicate unstable demand.
- Groups: a single block can distort pace.
- Channel mix: did demand shift between OTA and direct? That changes net revenue.
- Events: is there a local event/holiday explaining a spike?
- Lead time: if guests now book later, pace may look weak early but still be normal for the new pattern.
Competitor context is useful as a quick sanity check. Sigma Revenue supports this with Competitor Data.
4) Turn pace into pricing and availability actions
Pace doesn't tell you the exact number to change, but it's a great trigger for when to act. Here's a simple framework:
For strong dates (pace above expected)
- Increase in small steps (disciplined dynamic pricing, not jumps).
- Consider stay controls like MLOS or CTA to protect peaks.
- Protect your direct channel (don't fill your best nights with the highest commission).
For weak dates (pace below expected)
- Start with value before discounts: packages, messaging, policies.
- If you change price: small step, then measure impact at the next review.
- Review your min/max guardrails to avoid a downward spiral. See Min/Max rates and guardrails.
5) Automate the routine, keep control of the strategy
The best setup automates the repetitive work while you keep the strategy and guardrails. Sigma Revenue combines:
- Demand Forecasting for forward-looking context;
- Calendar View for quick peak visibility and controls;
- Rate Recommendations based on your rules;
- Autopilot when you want hands-off execution.
Want to see a simple pace-driven workflow for your hotel? Contact us and we'll map it out.