Who are my “true” competitors? This million-dollar question is often a central discussion point in boardrooms, during the development of annual sales and marketing plans, in the creation of promotional campaigns and during weekly revenue strategy meetings. From quiet philosophical conversations to heated debates, this question remains a point of contention. However, I believe it’s simply a matter of perspective.
Let’s assume for a moment that our friend “Tom” has been tasked with the challenge of securing funding for a new development project or acquisition of an existing property. Given the cyclical nature of the economic state during the past several decades and the corresponding demand oscillations that are the bane of our industry, it is understandable that lenders may look for increased assurances prior to underwriting a project. Yes, there are probably still investors out there looking for “trophy” properties and who will spare no expense in acquiring them; however, for obvious reasons, those would be the exception and not the norm. Tom’s job then, is to relay a story—a story that will support the investment objectives of a given lender.
One element of Tom’s story is the competitive environment in which the target property will operate. It would stand to reason, then, that Tom would select a competitive set that would demonstrate the upside potential for his property. In some cases, this means he would probably pick properties that are likely to realize a high average daily rate since this would help demonstrate that high-end demand exists in the market. Presumably, Tom’s property would become an attractive alternative for potential guests over what had previously existed. Often, upon realizing that the ramp-up is taking longer than anticipated, this original set used for underwriting soon becomes known as the “aspirational” set, and a second “operational” or “peer” set is then selected for tactical benchmarking purposes. Of course, this doesn’t change the pro forma, so pressures on management companies and others to meet the original (and possibly contrived) expectation still exists.
The same could apply for an occupancy bias whereby demand projections based on past performance within a given market or specific set are generated. With comparatively short development cycles for new projects, particularly in the midscale and limited hotel sectors, in addition to a recent proliferation of brand extensions (each presumably targeting a distinctive audience), previously unidentified supply could very quickly and easily erode this upside occupancy potential. Recognizing threat, but not having a crystal ball at his disposal, Tom is likely to generate a guidance range that is reasonable but slightly optimistic. Given this, Tom may be inclined to select a set that would consist of properties that are established, popular and perhaps have amenities and services that are slightly superior to those of the project being contemplated.
Operational performance considerations
Surprisingly, there are a few operators that don’t consider their competition but instead rely on their own historical performance to judge today’s successes and failures. For most properties, competitive benchmarking such as that provided by STR through its STAR reports product is the mainstay for performance evaluation on hospitality-related key performance indicators such as occupancy, ADR and revenue per available room, in addition to indexes associated with each of the KPIs mentioned.
Competitive set selection is critical to ensuring the data provided in these reports is relevant. Some of the typical pitfalls associated with comp set selection include:
- Ignoring the demand base. Similar product type, amenities and location are often used as the prime criteria for comp set selection, but the target market for a given property is overlooked. For example, two properties in an airport market may be identical, but a large amount of crew business for one may skew the metrics. The same pitfall would apply when selecting a property with a large group base when your property has a predominantly transient following.
- Choosing a known outlier. The STAR report is based on averages, so intentionally selecting a property with unique performance characteristics likely will compromise the validity of the results.
- Overestimating or underestimating value. Knowing what current and prospective guests value in their selection process is critical. Even more critical is the need to know how well your property and those of your competitors meet those needs. An honest, unbiased evaluation is key.
- Only benchmarking one set. Particularly for resorts, properties in unique geographical locations or those with distinctive attributes (e.g., conference centers), multiple comp sets representing regional, national and sometimes international competitors could be appropriate. Mixing the above into a single set would not be.
As mentioned previously, a given operation may have a bias toward benchmarking performance to one metric over another. For example, a high-end property with a relatively high variable cost per occupied room likely will want to focus on growing rate where possible since this strategy is most likely to have a direct positive impact on net operating income. A midscale property with comparatively low variable cost per occupied room may wish to focus on driving occupancy whereas a full-service resort with the potential to drive ancillary spend beyond the guestroom product may vary their focus by season—driving rate in season and occupancy in the off-season.
In the absence of a specific bias towards rate and/or occupancy, RevPAR and, more specifically, change in RevPAR Index would be an appropriate metric to consider. An index is simply a ratio (expressed as a percent) between the performance of a given property to its competitive set for a given KPI metric.
In the above example, the subject property’s RevPAR of US$120 is approximately 14.3% greater than US$105, representing a penetration, or index, of 114.3%. While this “above average” result may look good at first blush, it is important to understand what this result looked like for a similar period in the past. By way of example, if the RevPAR index was 110% against the same comp set last year, then this expansion to 114.3% is a positive development. Conversely, if the RevPAR index was at 117% last year, then the penetration gap has closed slightly. If declining RevPAR index is a trend that is occurring during several periods, then the root causes need to be identified and appropriate corrective action taken.
STR Analytics, a division of STR, has recently developed some reports (Bandwidth and RPM) that will provide operators with additional insight into performance. While individual properties are still not identified, these new tools disaggregate the data so subscribers are able to understand and benchmark their performance, not against broad averages, but against the leaders within the comp set.
While the actual selection of a comp set is still quite subjective, STR Analytics is attempting to change this by introducing “mComp.” By using objective selection criteria and proprietary processes, they draw a distinction between the properties you think you compete with and those properties you should consider as part of your true competitive set.
In the book “Blue Ocean Strategy” by W. Chan Kim and Renee Mauborgne, the authors provide several examples of companies that have sought after and capitalized on uncontested market space. Unless you are fortunate enough to be a stakeholder in a hotel operation that offers such a differentiated experience that your competition is rendered irrelevant, it is likely that you are competing head-on with others that are reasonable substitutes.
Revenue managers need to clearly understand the price/value perception that prospective customers have of their property and the alternative options available at any given time through any given channel. This daunting task can most easily be performed by reviewing materialized demand through booking pace, channel production and rate production reports. Unfortunately, these only tell part of the story.
Ideally, a property would review the publicly available pricing for the same competitors contained within the STAR report. However, with services available in the marketplace today such as TravelClick’s RateView, Rubicon’s MarketVision Price Position, RateTiger’s Shopper and others, reviewing secondary competitors becomes relatively easy. The secret then is to know when to respond to a competitor’s pricing tact and when to ignore it. In fact, many automated revenue management systems (RMS) today do leverage this type of competitive pricing information to help generate or validate system recommendations.
Beyond traditional travel agencies and corporate booking tools, it’s no secret that Web search engines such as Google and Bing and travel sites such as Expedia and Travelocity are used by travelers to understand what accommodation choices are available in a given location at a given time. In fact, 90% of all travel-related purchasing decisions are made online, according to Forrester Research. So, despite our best efforts to define who we think our competition is, it’s really customer perception that drives purchasing decisions.
Properties would be well-advised to keep close tabs on their online reputation and those of their competitors by regularly reviewing TripAdvisor, Yelp, OTA sites, Twitter and Facebook comments. Of course, formal customer satisfaction research may also reveal some surprising insights into who your customers think your true competitors really are. That said, there is no substitute for physically experiencing what a guest would experience by actually staying with your competitors and using their facilities—just as a particular customer segment would. And, as you instinctively look for the negatives, keep a note of things that would fall in the plus side of the ledger. You may just find something innovative that you would like to adopt for your property.
OTAs use methods based on such factors as location proximity, rate band and quality rating (per their own customer feedback scores), to determine which properties are likely to compete against each other. They then use this information in their display algorithms.
Factoring in a given customer segment’s perception of value available through online reviews will be the next evolution in RMS development in my opinion. This plus a “remaining supply” analysis (the opposite side of the demand curve) will allow further insights into consumer behavior prediction and allow for better quality system outputs relating to pricing recommendations, hurdles and oversell limits.
So, while the question “Who are my true competitors?” will continue to linger, technology, resources and analytics will continue to evolve. This will undoubtedly provide us with greater insights and strengthen the position of individuals involved in those lively boardroom discussions. But one fact will remain: It’s simply a matter of perspective.
This article was first published on HotelNewsNow.com