S1:E4 Cancellations

In the first part of this two-part series on cancellations, Daniel Foreman and Connor Vanderholm tackle the challenges and opportunities cancellations present. Learn how to predict and manage cancellations, turning potential setbacks into opportunities for higher revenue. This episode provides the strategies and tools needed to accurately forecast cancellations and implement overbooking strategies that keep your occupancy and revenue on track.

However, when managed correctly, cancellations represent an opportunity to “trade up”. We can, in theory, get a second chance to re-sell these lost rooms at a higher rate, or a more desirable stay pattern than the original booking that was canceled. 

In our last installment, we talked about segmentation and we’ll continue to lean heavily on this concept as we talk about cancellations, while also introducing a few other novel ways to look at this new sellout-affecting variable.

Our guest for this time is Connor Vanderholm, CEO and Founder of Topline!

While we, as revenue managers, will never be able to control the weather… or whether the large wedding party staying at your hotel is called off, we can at least use data to make the best possible decisions that make perfect sellouts more likely, and less prone to fall apart on the very last day.

To keep things simple, I'll talk about 3 different ways to analyze cancellations within our Business Intelligence products, but remember, that with Rate Insight, you can easily apply multiple filters to dig deeper and explore even more factors. Here are the 3 factors I found most interesting for my example hotel:

• International / Domestic mix
  There are distinct differences in cancellation patterns between these guests which we'll explore in detail.

• Market Segmentation Mix
  Different segments displayed different tendencies in regards to cancellation habits, but what causes this?

• Day of Week (Weekday vs Weekend)

There’s plenty more to explore in Revenue Insight, by the way, including, Rate Code, Room Type, Travel Agent, Company, and LOS!

International vs.

Domestic Mix.

Let’s start with one interesting variable that you can analyze to get a grasp on whether cancellations might put your perfect sellout at risk: International/Domestic Mix

Take a look at this month’s cancellation report for a dynamic hotel in a major city (the example hotel I used when creating the podcast episode) On the left is the cancellation by booking window for international guests from Great Britain (our largest International Feeder Market). On the right side is cancellations by booking window for domestic guests (from within the United States)

This is very typical of what you can expect to see from domestic and international bookers in a major market; notice that only 1.5% of GB cancellations happen within the 0-6 day from arrival window, whereas 15.7% of domestic cancellations are happening within that 4-6 day from arrival window.

Something else to consider is that international guests almost always have a longer average length of stay or ALOS than domestic guests. While these guests tend to cancel earlier in the curve, when they do cancel, you are often losing a very lucrative stay pattern which you then have to replace with a domestic traveler who is very likely staying for a shorter time (and still might go on to cancel anyway).

Here’s a snippet of what Connor said when he saw this graph in the podcast interview:

Market segmentation mix

Next, let’s talk about market segmentation in relation to cancellations. I’ve noticed trends over the years using our BI products that may help you determine when you’d like to sell out (based on when you’re likely to lose rooms). These trends popped up again when analyzing the example hotel for the podcast episode.

As a very general rule of thumb, bookings with more lax cancellation/guarantee policies tend to have a higher ADR premium.

Why is that?

Think for a moment about times in which you’ve booked a fully refundable rate and compare that with times in which you've booked an advance purchase non-refundable.

With the refundable BAR rate, you are also paying for a level of security and flexibility. There is a premium on being able to cancel that stay in case things go awry! It’s no surprise that guests, armed with this flexibility and security tend to have a higher rate of cancellation as a total mix of RN activity, because they can do so without penalty.

Don’t take my word for it though, let’s jump back into our example hotel, and analyze cancellation rate by market segment within Business Intelligence and take a look at our YTD performance:

Notice that, far and away, the Best Available Rate segment (which includes multiple retail rate plans, tied to lax policies with 24 and 48-hour cancellation clauses) had the highest cancellation rate.

I added a trendline to reinforce the fact that there is indeed a correlation between lower ADR segments and their overall cancellation rate. It’s not a super-strong correlation but there’s definitely something here.

What I recommend next is to learn a bit more about when each market segment cancels. Below is an example from Rate Insight where I take a look and compare the cancellation window of both the Best Available Rate segment (left) and Corporate Group Segment (right)

I know from my experience that I often put too much emphasis on attracting only BAR/RETAIL segment guests because of the allure of the high ADR, but put yourself in the shoes of a revenue manager who is in charge of this dynamic hotel…

Would you really want the hotel to be filled with 100% retail guests for a big event night?

Most revenue managers would probably say yes.

But, what if it were 7 days to arrival? Would you trade some of that cancellation uncertainty and perhaps prefer a mix of 30% Corporate Group and 70% Best Available Rate?

This would come with a much lower cancellation risk, and therefore higher likelihood of executing a perfect sellout!

This is why cancellations and segmentation go hand in hand - all along the booking curve a good revenue manager is monitoring their market mix and adjusting their cancellation forecast.

Weekday vs Weekend

Finally, we will round out our analysis with a 3rd method for analyzing cancellation data.

To do this, let's filter our cancellation data by day of week and the stay date in question…

For my example hotel, I pulled the distribution of booking window vs. cancellation window for another hotel YTD and found something interesting:

For this particular hotel, weekday stays tended to be both booked later and canceled later in the booking curve than weekend stays.

While I expect this to vary from property to property, this would likely be very valuable information for a revenue manager to know when trying to maximize occupancy on a mixture of weekdays and weekends.

Also, to take it a step further, using Rate Insight, we know that this property is experiencing an overall drop in weekday cancellations, however, their weekend cancellations are becoming fewer, though more last minute (note the uptick in cancellations in the 0-3 and 4-6 day window.

Cancellation Data for weekdays (left) and weekends (right)

Booking Data for weekdays (left) and weekends (right)

How to discourage cancellations

Ways in which we as revenue managers can dissuade cancellations:

• Thoughtful application of effective cancellation and guarantee policies

• Building a healthy market mix throughout the booking curve and not relying too heavily on a single particular segment, feeder market, or length of stay pattern.

• Logical pricing strategies that deter booking churn (avoiding dropping rate last minute so that guests cancel and re-book)

Key Takeaways:

• Identify where you are in the booking curve, and compare it against your Guest Country report in Revenue Insight or a similar report you may have. A simple international-to-domestic ratio of guests may provide some insights into what you can expect cancellation-wise.

• Learn the cancellation rate of each of your major segments using Revenue Insight.

• Consider what day of the week you are trying to sell out on. Do your weekends tend to experience cancellations later in the booking curve? What about your year-over-year trends? Are guests' cancellation patterns becoming more last minute, or further from arrival?