Booking Curve

Key Considerations When Using Booking Curves

• Historical booking windows: Establish reference curves by season and property type to understand typical lead times.
• Seasonality & events: Peak weeks book earlier; shoulder periods book later. Layer local events onto the curve for context.
• Cancellation behavior: Track cancels and rebooks by DBA to avoid overestimating final pickup.
• Inventory position: Monitor remaining availability and pickup velocity to prevent stock-outs or underfills.
• Mix effects: Channels, LOS, and unit type can shift pace—compare like-for-like cohorts.

Positive gaps suggest price opportunity or tightened restrictions; negative gaps call for demand stimulation or easing rules.

How Booking Curves Are Used

• Forecasting: Extrapolate to expected final demand using historical conversion from each DBA.
• Rate management: If actual pace is ahead, raise rates or add fences; if behind, deploy value adds or price tests. See Dynamic Pricing and Revenue Management.
• Restriction control: Adjust minimum stay, closed-to-arrival (CTA), or closed-to-departure (CTD) rules to shape LOS and fill gaps.
• Benchmarking: Compare pace against comp-set patterns if market data is available.
• Operations: Anticipate labor, linen, and supplier needs based on projected sell-out dates.

Examples

City Hotel Near a Convention Center

Historical curves show a sharp pickup ~30 DBA. When this year’s pace jumps at 45 DBA, management increases rates for late bookers and introduces a 3-night minimum, lifting RevPAR.

Beachfront Vacation Rental

Spring break curves book early. The host launches early-bird promotions at 120–90 DBA, then tapers discounts as pace meets target, protecting ADR.

Ski Resort

Most winter weeks hit 70% by 60 DBA. To flatten last-minute pressure, the team offers refundable early-bird rates and non-refundable value tiers, smoothing the curve and operations planning.

Related Terms

Lead Time

Days between booking date and arrival; the X-axis for most booking curves.

Booking Window

Another term for lead-time distribution; informs expected pace by date range.

Occupancy Rate

The share of sellable nights booked; curves help forecast final occupancy.

Average Daily Rate (ADR)

Average revenue per sold night; rate moves respond to pace signals.

Revenue Management

Coordinating price, availability, and restrictions to optimize revenue.

Seasonality

Recurring demand patterns by time of year that shift booking pace.

FAQs

Should my booking curve be cumulative or daily pickup?

Use both. Cumulative curves show whether you’re ahead or behind target by DBA; daily pickup charts expose sudden spikes or stalls that warrant action.

How often should I update my target (reference) curve?

At least seasonally. Rebuild targets when you change pricing strategy, add inventory, or see structural shifts (e.g., new events or channel mix).

What if my pace is behind target at 30 DBA?

First check inventory and restrictions. If clean, test value tactics (bundles, perks), widen length-of-stay acceptance, or adjust price. Consider targeted marketing to past guests with similar stay dates.

How do cancellations affect booking curves?

Track cancels and rebooks by DBA. Create a net booking curve (bookings minus cancels) for forecasting; high late-stage cancellations may require stricter policies or different rate fences.

Can I compare curves across different unit types?

Yes, but segment first. Build separate curves by unit type, channel, and LOS so you’re comparing like-for-like demand patterns.

What metrics pair best with booking curves?

Pace vs. target gap, remaining availability, pickup by DBA, rate index vs. comp set, forecasted occupancy, and impact on ADR and RevPAR.

How do booking curves inform restrictions like minimum stay?

If early pace concentrates on short stays that fragment inventory, increase minimum stay or close certain arrivals to preserve longer LOS bookings.