Hotel competitive sets, commonly known as “comp sets,” are a core element of our performance benchmarking program.
NB: This is an article from STR
Without a comp set, and the marketplace intel that comes along with it, you’re left guessing as to where you can improve the performance of your property or portfolio.
That is why choosing the appropriate group of competitor hotels is vital in the quality of the reports and analysis STR delivers you. For example, selecting hotels that perform at different levels than your subject can produce misleading results, such as extremely high or low index levels across all key performance indicators (KPIs). Simply put, you might be benchmarking against players in “different leagues.”
Let’s discuss the factors you should take into consideration when selecting a comp set, how COVID-19 and other circumstances may affect your comp set, and how we can help you in the process.
What comprises the best comp set?
We have developed a statistical model that factors data from more than 30,000 primary comp sets. Through this analysis, we have identified nine factors that most influence the dynamics within a set. For comp set grading purposes, this model considers high-level factors such as class and location, with a comparative analysis of the performance of your set and all other sets with similar composition.
Using the most current performance data, the model assigns a grade to your set, based on how much your set deviates from the norm. The larger the deviation, the lower the grade. A low grade is an indication that your property is not being benchmarked against comparable properties.
When selecting a comp set, we recommend that you don’t only select those hotels “across the street” from your subject property. Instead, we encourage you to take into account the characteristics of the hotels in your area, such as their class, room count, meeting space, etc. Gaining insights on the performance of the competition leads to more informed decisions when selecting a set, and this is where our comp set advisory services can be helpful to you.
Factors causing a challenge
There are multiple industry and environmental factors that may cause a challenge when determining a comp set. For one, industry consolidation is making it difficult to create and manage comp sets over time. In addition, COVID-19 and other external factors have created tremendous disruptions in data reporting due to property closures, furloughed staff, etc. Any changes to a hotel in a comp set can shift percentages in excess of STR guidelines, rendering the comp set non-compliant.
Over 20% of hotel rooms worldwide closed temporarily in 2020, causing many competitive sets to “break” as member properties stopped reporting data. While many of those closed rooms have since reopened, some have permanently closed, and more could be on the horizon. This threatens total hotel supply and competitor set options.
The solution: Composite Comp Sets
Launched in October 2020, the Composite Comp Set behaves like a traditional comp set, providing a relevant benchmark to subject property performance. The key difference? A Composite Comp Set has a composite property, which is a composite of performance from multiple hotels. Each composite property is automatically weighted to act like one additional property in your comp set.Image
How can Composite Comp Sets help?
- Non-compliant comp sets: A composite property can be plugged in to a non-compliant comp set and bring the non-compliant set back to sufficient.
- Replace one property in set: A hotelier can remove a property that is less comparable than they would like and replace it with a composite property.
- Add one property in set: A hotelier can add one real property to their sets in conjunction with a Composite Property.
- Create comp sets in areas with low sample: A composite property can “fill out” sets for your properties with only 3 out of 4 comparable properties needed to create a set.
Why should I care about the strength of my comp set?
The proof is in the pudding. Let’s take a look at Property A and its current set, which has a grade of “C” based on our model’s calculations.
A custom RPM report provides a snapshot of the subject’s performance for the running-9 months as of December 2019, showing that it ranks 7th in terms of RevPAR index.
After some analysis, our team has found a new and improved set, with a grade of A+. The custom RPM for the new set, based on performance for the same time period, shows that the subject property ranks 5th for RevPAR index.
Whereas with a new set like the one above, the subject property is not the leader of the pack as desired. The aggregated competitor set performance sheds some light on areas in which the subject property has optimal performance and areas where there is room for growth.
It’s important to spend time choosing the properties that would make the best competitor set for you.
