Stay Pattern
Stay Pattern refers to the combination of check-in day, check-out day, and length of stay most frequently observed at a property over a defined period. Analysing stay patterns reveals how guests naturally organise their visits — which arrival days drive the most volume, how many nights they typically book, and where gaps or compression points appear in the calendar.
Key Dimensions
A stay pattern analysis typically examines:
- Arrival day distribution — which days of the week see the most check-ins (e.g., Friday leisure vs. Monday corporate)
- Departure day distribution — which days create the most departures and housekeeping pressure
- Length of stay (LOS) distribution — the spread of 1-night, 2-night, 3-night+ stays by segment or channel
- Day-of-week crossover — how mid-week arrivals differ from weekend arrivals
Example
A city-centre business hotel may show that 60% of bookings check in on Monday or Tuesday with a 2–3 night LOS, while a coastal resort shows Friday check-ins dominating with a 7-night LOS over summer. Each pattern demands different length-of-stay restriction strategies.
Why It Matters
Stay patterns directly inform several revenue management decisions:
- MinLOS and MaxLOS controls — MinLOS restrictions are most effective when calibrated to the natural stay pattern; restricting shorter stays on high-demand nights can improve RevPAR only if most demand genuinely prefers a longer stay
- Pricing by day of week — BAR by day-of-week pricing should reflect the check-in and length-of-stay mix, not just isolated night-level demand
- Forecasting — accurate demand models must account for the proportion of bookings that straddle multiple rate periods
- Staffing and operations — housekeeping, front desk, and F&B planning all benefit from understanding peak arrival and departure days
Segment Variations
Stay patterns typically vary significantly by:
- Segment (leisure vs. business vs. group)
- Channel (OTA-originated bookings often skew shorter and more weekend-heavy than direct corporate bookings)
- Season (summer resort patterns differ sharply from off-peak)
- Market (domestic guests often book shorter stays than international guests)
Related
- MinLOS / MaxLOS — length-of-stay restrictions directly derived from stay pattern analysis
- ALOS (Average Length of Stay) — the headline metric summarising the LOS distribution
- Booking Window / Lead Time — the booking behaviour counterpart to stay pattern
- Channel Mix — stay patterns often differ materially by booking channel