When it comes to data, everyone has their own magic formula, and each KPI should illustrate an aspect of my strategy. In a company that defines itself as data-driven, data takes on fundamental importance.
The technological transformations of recent years have driven many companies to change their decision-making process, no longer relying solely on experience but on solid data. In tourism, especially in revenue areas, making choices without firmly backed data is like driving without seeing your revenue on dangerous, obstacle-filled roads.
Revenue, RevPAR, IMO, ADR are just acronyms if we cannot grasp their implications for our strategy. Among the data points that can provide valuable insights into revenue, I’ve chosen pick-up. Pick-up is a very important indicator in revenue analysis; its centrality is often underestimated, yet it should be one of the data points observed daily.
Increasingly, rate optimization will hinge primarily on how quickly we analyze this data to act swiftly on prices, availability, restrictions, and distribution.
In this regard, an RMS can certainly become an excellent ally.
Among the many accurate definitions of pick-up, I prefer one that describes it as “booking rhythm”: the heartbeat of my complex “forecasting”. Pick-up is influenced by various variables and, in turn, can influence our pricing choices; it is definitely the most significant factor in rate increases for specific periods or dates and is often only observed for what manuals define as “event dates.”
One of the most frequent errors in hotel management is oversight: an event might be forgotten, its existence ignored, or its impact underestimated. That’s where pick-up comes in: it starts to increase unusually, ringing an alarm bell that prompts us to delve deeper into the analysis, though often it’s too late. Sudden rate increases or quick reductions won’t help us anymore, and part of our revenue is lost.
Pick-up curves often come in two types: one where the curve skews under the date, with a sudden rate drop under the date – and an increase in bookings; another shows that we set a rate too high far in advance, quickly saturating our availability and hitting the rate cap well before the date of interest.
In both cases, with a good pick-up analysis, we could have made adjustments, such as:
- avoiding rates that are too low or too high at the start
- adjusting price increases or decreases more steadily
MyForecast RMS offers on the same dashboard historical data from the past two years and an accurate representation of pick-up: up to 60 days over 365 days, in a direct and immediate comparison.
This is just an initial analysis of pick-up: the truly interesting data is the relationship between the increase/decrease in pick-up relative to the booking source. Observing this data allows us to understand how to adjust rates based on the macro-channel/segment: an increase in pick-up from a contracted business segment is not a signal to raise rates but rather a prompt to reevaluate the agreed rate. If the rate is too low, it may be better to reduce the allotted rooms—where possible—or reconsider the contract at renewal.
A macro-channel producing a high pick-up with a public rate warrants attention and proper rate adjustments, as in this case, pick-up genuinely signals market interest. Similar considerations should be made for TO/adv rates.
Pick-up is closely linked to pricing, but price is not the only data point involved. Pick-up enables us to understand the implications between rate and distribution, between segments and restrictions, leveraging all possible levers, not just price.
Tina Ingaldi, Sales Manager MyForecast RMS