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Next week will be an important one for the industry dialogue on competitive set selection.  Readers of this blog will know that comp set selection is an issue close to our hearts, so we are looking forward to a session that will reveal some interesting insights into this important subject at a leading Revenue Management conference. 

 

The occasion is the INFORMS Revenue Management and Pricing Conference, which takes place at Columbia University in New York on June 23/24.  And the insights come from the presentation of a paper currently being prepared by Roger Lederman, with Professor Garrett van Ryzin and Assistant Professor Marcelo Olivares, in collaboration with Hotel Compete.

The paper seeks to understand comp sets from the point of view of customer choice.  In our last blog post we explained how the focus on historical benchmarking biases comp sets.  In particular hotels tend to prioritize “fair” competitors – ie hotels that are likely to achieve similar performance to them – above hotels with whom they compete directly for business.  We suggested that a better way to frame competitive analysis is to ask the question: “If somebody is considering booking this hotel, which other hotels are they most likely to be considering?”

Further, it has long been our belief that hotel comp set selection – typically a subjective process – lends itself to an analytical approach, based on the characteristics of the hotels in the market.  To understand which hotels bookers consider as alternatives, our analysis should focus not on historical performance (into which bookers typically have no visibility) but rather the key attributes of location, hotel class, price, amenities, services, etc.  Bookers are adept at using technology to filter searches based on these characteristics, so these ought to be the things that we analyze when we select comp sets.

The Columbia study – an extended abstract of which can be found here – models the relationships between hotel types (defined by their characteristics), customer segments, location-specific demand drivers, and the demand patterns affecting the properties over time.  The models use highly detailed information about all of the hotels in a major US market, and a subset of study properties within that market, which were observed over a three-month measurement period. 

The work on the study is ongoing – next week’s presentation will cover preliminary findings only.  Interestingly, though, the abstract notes how well-suited the hospitality is to empirical study of this nature. Whereas, in general, customer choice can be highly subjective, several important elements of hotel choice (e.g., location, rate, amenities, etc.) are readily quantifiable.  This gives context to the argument that we made last time – ie that the current industry approach to comp set analysis is short on analysis and long on subjectivity.

We will be in New York next week for the presentation and to take part in the discussion that we hope it will stimulate.  Please look us up if you’re there too!  In the meantime, for more insight into the importance and the practical uses of comp set analysis, please download one of our white papers.

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