Recently, during a conversation with a friend, he asked me a question that had clearly been on his mind:
“How can you spend your whole day analyzing bookings?”
NB: This is an article from berner+becker, one of our Expert Partners
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I smiled and said, “Think of it as feeling the heartbeat of a hotel – you’re not standing at the front desk watching guests check in, you’re checking the pick-up.”
He looked puzzled. “Pick… what?”
I explained matter-of-factly: The pick-up measures the change in a hotel’s booking status over a specific period of time (usually until the end of the following calendar year). It shows how many additional bookings have been made compared to the previous day, week, or another reference point – including cancellations.
This makes pick-up a key indicator for assessing current market demand and the effectiveness of pricing strategies.
Example: If you had 80 rooms booked for next week yesterday and today there are 90, the pick-up is 10 rooms. If it’s the other way around, bookings are dropping – the hotel’s heartbeat slows, and that directly affects revenue.
My friend frowned and asked: “Okay, but what do you actually need to analyze pick-up properly? How do you make sense of it?”
I told him you don’t need complex models – just a few basic metrics:
- Room nights: How many additional nights were booked? What’s the impact of cancellations?
- Revenue: How much income do the new bookings generate (minus cancellations)?
- Average Daily Rate (ADR): Are the new bookings above or below the current average? Is the ADR rising or falling?
- Comparison values: What was the pick-up yesterday? On the same day last year? That’s how you tell whether the hotel’s pulse is strong or weak.
Example: +20 room nights compared to yesterday, plus X euros in revenue, ADR slightly higher. Sounds good. But if last year on the same day the pick-up was +30 room nights higher, that’s a warning sign. Looking at multiple perspectives at once – that’s key.
However, visualizing pick-up is also crucial for understanding and interpreting booking dynamics. Depending on the period you choose – two weeks or several months – the picture can change dramatically.
A short lead time highlights spontaneous or last-minute demand, while a long lead time reflects strategic or planned bookings.
So, the chosen visualization greatly influences what conclusions you draw from the pick-up and which actions you take to optimize booking behavior.
