In our last blog post we made brief reference to hotel comp sets. A great deal has been written lately on this subject, including academic research, and opinions from some familiar hotel industry figures. There seems to be a consensus that comp set selection is important. And that the quality (ie representativeness) of a hotel’s comp set impacts the analysis that hotels and their stakeholders do, and ultimately the decisions that they make.
Experience has shown, however, that the typical lodging industry approach to comp set selection remains short on analysis and long on subjectivity. In this post we provide our own perspective, and introduce an alternative analytical approach that brings objectivity to this critical analytical process.
“Comp Set” has a specific meaning in the hospitality industry – most hotels have a set of competitors that they use as a basis for competitor benchmarking. The results of year-over-year RevPAR share measurement take center stage in discussions between ownership, brands and operators; hence the numbers are highly visible and important. The choice of competitors impacts a hotel’s share performance, so the selection of the comp set usually involves careful negotiation between a hotel’s stakeholders. The objective of that negotiation is to find a “fair” comparison set for the hotel.
The focus on comparison of property results introduces a bias into competitor sets, particularly when we are trying to understand and predict future performance. Performance is a factor of how many people book a hotel and how much money they spend during their stay. When people book hotels they have no interest in the outcome of that hotel’s benchmarking exercise, so it makes little sense to assume that a benchmark comp set represents the realities of a competitive market. Yet hotels and hotel companies continue to take this very approach.
This bias is exacerbated by the availability of competitor hotels for reporting. Not every hotel shares its data for industry reporting, so if a hotel has direct competitors whose data is not available, then it must look further afield for comparison properties. The confidentiality of the data places further limitations to ensure that hotels cannot calculate one another’s performance – eg when a comp set contains sister properties within the same brand, management company or ownership group. These restrictions are well-understood and necessary for the core purpose of the reports, but they are unhelpful to our understanding of competitive hotel markets. Bookers don’t restrict their hotel selections based on performance data availability, so smart competitive analysis should understand these limitations.
A better way to define competitors is to ask the question: “If a booker is considering booking this hotel, which other hotels are they most likely to be considering?”
This question is more relevant to understanding future competitive dynamics than historical Average Daily Rate (ADR) and occupancy levels. It can be answered objectively by analyzing hotels through the lens of customer choice. We can understand a hotel’s competitive position by measuring variables like hotel location, brand, hotel type, meeting room space, and – critically – the rates that it typically charges.
Rate is a major determinant of hotel choice – in fact today’s booking engines usually facilitate the grouping of hotel search results by their selling rates. It is reasonable to assume that hotels that habitually price at similar levels are likely to be direct competitors. This has an interesting consequence for comp set selection: selling rates change, often dramatically, which means that comp sets should also be able to change periodically – eg from season to season.
These dynamics are understood by revenue managers, but they sit uneasily alongside a comp set selection methodology that is grounded exclusively in historical performance. Hence the industry’s approach to selecting competitors continues to be suboptimal – a view that appears to be borne out by current industry commentary.
When we balance the most important drivers of customer choice, we can develop a reliable view of which hotels are the most direct competitors. Hotel Compete has been researching this area extensively, comparing the results of objective data analysis to the comp sets that are nominated by hundreds of different properties. You should not be surprised to learn that the research highlights some interesting discrepancies.
In our next post we will share some results from our own research, and we will return to this subject frequently over the coming weeks and months. Comp set selection is – as we suggested above, and in our last blog post – a can of worms to which the industry has historically devoted too little analytical capacity.
In the meantime, you can learn more about the potential uses and benefits for the comp set analysis approach described above by downloading one of our white papers.