When booking windows shorten, the game changes: guests book later, pickup accelerates closer to arrival, and dynamic pricing needs a faster, more structured cadence. The good news: with the right analysis, shorter lead times can become an advantage.
Glossary terms for booking window analysis
- Booking Window and Pickup
- Market Segment and LOS
- MLOS: when minimum stay helps on peaks
1) Don’t look at the average booking window—look at the distribution
The average often lies. More useful views:
- median (typical lead time);
- 25th/75th percentiles (how spread demand is);
- weekend vs weekday differences.
This helps you set your review cadence (e.g. more frequent checks in the last 14 days).
2) Segment by channel and demand type
Different segments behave differently. Minimum segmentation:
- direct vs OTA;
- leisure vs business;
- groups vs transient guests.
Without segmentation you end up with "average" decisions that fit nobody. Sigma Revenue supports this through Analytics.
3) How shorter lead times change dynamic pricing
When guests book later, two things matter more:
- Faster cadence: more frequent reviews, smaller steps.
- Better triggers: pace/pickup, competitor context, events.
Practical approach: combine a weekly 30/60/90-day review with more frequent checks for the next 14 days. See how to read booking pace.
4) Stay controls: when price isn’t enough
With shorter booking windows, you risk filling up with short stays right before a peak. This is where controls like MLOS help, alongside calendar-level decisions.
In Sigma Revenue, these decisions are easy to spot by date in Calendar View.
5) How Sigma Revenue helps as booking windows shift
Combining Demand Forecasting with Real-time Data gives you better context earlier and faster detection closer to arrival. That makes dynamic pricing more resilient under volatility.
Want to see how this would be configured for your hotel? Contact us.