This video explains the crucial but often overlooked metric of "Booking Lead Time" for Airbnb hosts. The speaker argues that while dynamic pricing tools like PriceLabs and Airbnb's own algorithm don't fully utilize this metric, it's vital for optimizing pricing strategies, occupancy rates, and ultimately, revenue. The video demonstrates how to find and interpret booking lead time data within the Airbnb Insights dashboard and how to use it to set dynamic occupancy targets.
A lower booking lead time compared to competitors suggests that guests perceive your listing as offering superior value, prompting them to book closer to their desired dates rather than far in advance. If guests are booking your listing significantly closer to their stay dates than they are booking comparable listings, it implies they see your offering as the best option available at that time. This could be due to a combination of factors such as price, amenities, reviews, or overall guest experience, which collectively create a strong value proposition that doesn't necessitate booking far in advance.
The speaker recommends setting occupancy targets based on a combination of the listing's booking lead time and the market's expected occupancy for a given period.
Here's the breakdown:
Baseline (Ideal Market): In a market with high expected occupancy (e.g., 100%), the speaker suggests a sliding scale. If your booking lead time is 15 days, you should aim for 50% occupancy at 15 days out. This translates to:
Adjusting for Seasonality (Slower Market): When the market occupancy is lower due to seasonality (e.g., 60% instead of 100%), you need to adjust your targets proportionally. This is done by dividing the ideal targets by the expected market occupancy.
The speaker emphasizes that these targets should be monitored and adjusted, ideally up to two times per year to account for significant seasonal shifts, but not too frequently to maintain pricing stability.
