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Sample Airport Hotel

VIEWS: 33 PAGES: 13

									 Sample Airport Hotel
       Sample, USA

mComp Competitive Report

       January 14, 2011
                                               table of contents
   introduction ...........................................................................................................................2
   building a pool of competitive properties ..............................................................................2
   geographic mapping ..............................................................................................................4
   network diagram ...................................................................................................................5
   mComp methodology ............................................................................................................6
   initial filtration .......................................................................................................................6
   clustering analysis ..................................................................................................................8
   market share diagram ............................................................................................................9
   descriptive plots...................................................................................................................10
   recommended mComp core competitors ............................................................................11
   RPM reconciliation diagram .................................................................................................12




mComp Competitive Report                                                                                                            1|P a g e
introduction
The purpose of STR Analytics’ mComp Competitive Report is to use statistical methods and STR’s comprehensive hotel data set to determine
which hotels have the most statistical relevance to form a competitive set within the Sample Airport market. This analysis was conducted using
Sample Airport market data from January 2010 to December 2010. The analysis in this report follows the objective statistical methods developed
by STR Analytics, which are detailed throughout this report. STR’s unique access to occupancy and rate information allows the competitive set to
be determined with objectivity and statistical validity.


building a pool of competitive properties
To identify the competitive set, STR Analytics begins with a reference, radial, and scale search for potential close competitors. Then, through
statistical methods, we narrow this market-wide list to a set of close competitors.

Reference: The primary competitive sets identified by all individual hotels in the Sample Airport Hotel’s primary competitive set are used to form
the basis of hotels to be examined for competitive statistical relevance. The perspective is also reversed and all hotels that list the sample hotel
as a primary competitor are extracted from STR’s database along with the other hotels identified in those competitive sets and those too are
added to pool of hotels to be examined.

Radial and Scale: The list of potential competitors is expanded with a radial search, selecting hotels within the same submarket and geographic
location, where applicable. This list is narrowed by price scale, retaining only those hotels that fall within two price scales (one above and one
below) of the sample hotel.

The resulting comprehensive list of potential competitors thus takes into account properties that management and/or ownership of hotels in the
subject area consider to be competitors, as well as properties that are likely to compete based on similarity of location and price scale.




        mComp Competitive Report                                                                                           2|P a g e
For the Sample Airport Hotel (A Hotel) this methodology produced an initial list of 37 hotels:


                     A Hotel                                               H Inn & Suites Airport
                     B Inn                                                 H Inn Airport 2
                     C Suites                                              H Express
                     C Hotel                                               H Airport
                     C Inn & Suites                                        L Inn & Suites
                     C Inn                                                 Q Inn & Suites
                     C Suites Airport                                      R Hotel
                     C Inn & Suites Airport                                R Inn
                     C Airport                                             R Hotel Airport
                     D Inn                                                 R Inn & Suites Airport
                     E Lodge                                               R Inn Airport
                     E Lodge Airport                                       S Hotel
                     E Suites                                              S Inn & Suites
                     F Inn                                                 S Suites Center
                     H Inn                                                 S Suites
                     H Lodge                                               S Suites Airport
                     H Inn Airport                                         S Airport
                     H                                                     T Lodge




        mComp Competitive Report                                                                    3|P a g e
geographic mapping
Mapping these hotels in the greater Airport market indicates that this methodology includes a diverse range of hotels and is likely to capture the
                                                                Hotel.
most statistically relevant competitors of the Sample Airport Hotel The map below indicates the locations of the 37 hotels generated by the
                                                                                                                  Hotel.
reference, radial, and price scale techniques. The orange marker indicates the location of the Sample Airport Hotel However, our statistical
  chniques                                                                                    ’s
techniques indicate that geography alone is insufficient to determine the Sample Airport Hotel’s true competitive set.




        mComp Competitive Report                                                                                         4|P a g e
network diagram
                                                                                                                          following
STR Analytics uses diagramming techniques to understand the complexity of the reference search and has developed the followin reference map,
indicating which hotels are consistently considered to be competitors. This customized analytical network illustrates that the reference technique
alone cannot accurately determine true competitors.

Geographical mapping uses location as the only means of competitive set selection. Reference diagramming uses the subjective, albeit informed,
opinions of area hotels that may choose competitive sets for numerous reasons that may or may not be relevant. A typical net  network map shows a web
                                                  petitive
of connections, allowing a property to see its competitive set and consider other properties that may list a subject property as a primary competitor.

The Sample Airport Hotel is the focal point of the network diagram shown below Radiating from that subject property are two separate colored and
                                                                         below.
directional arrows:

        These properties are named in the primary set of the subject
        property.

        These properties are not named by the subject property in the
        primary competitive set but they do name the subject property in
        their primary set.

In total, the Sample Airport Hotel names five properties in its primary comp
set, while six properties name the Sample Airport Hotel in their primary
competitive sets.




        mComp Competitive Report                                                                                        5|P a g e
mComp methodology
The mComp Competitive Set Selection is performed by STR Analytics using the combination of Hierarchal Cluster Analysis postulated by Jin-
Young Kim and Linda Canina, PhD. of Cornell University1 supplemented by a principal component analysis of market shares from the demand
model developed by R. Rothschild from the Economics Department of University of Lancaster; P. Swann from the University of West London and
M. Taghaavi of Newcastle-upon-Tyne Polytechnic2. This technique uses potential competitors based on location, size, perceived competitiveness
to “cluster” ADR and RevPAR and then specifically indentifies the Core Competitors based on market share data. We believe this process is the
most objective method available to track how the market identifies, compares, occupies, and pays for hotel room nights within a geographic
area. STR maintains the most comprehensive data regarding daily hotel occupancy, ADR, RevPAR and, most critical for this analysis, market
share.


initial filtration
Using daily data for the trailing 12-month period, we determine the average of the Sample Airport Hotel’s average daily rate (ADR) as well as the
standard deviation of the hotel’s ADR. The same calculations are done for revenue per-available-room (RevPAR). Next, we use the standard
deviations to form relevant groups around ADR and RevPAR. The percentage band allows more flexibility as consumer theory suggests that it is
relative prices that matter more than absolute prices. Furthermore, using a percentage based on the standard deviation of the Sample Airport
Hotel’s ADR and RevPAR considers the variability of prices within a market by day, week, and season. The bands formed with this method are
then applied back to the daily data, and we observe the frequency with which potential competitors fall within the band. With these bands we
are able to rule out properties that rarely have prices or performance matching that of the Sample Airport Hotel, thereby ruling out the most
distant competitors. These outliers are eliminated from further consideration.




1
    Canina and Kim, Product Tiers and ADR Clusters: Integrating Two Methods for Determining Hotel Competitive Sets, Cornell Quarterly, 2009
2
    Rothschild, Swann, Taghavi, Identifying Competitors from Market Share Data: A Technique and an Application, Applied Economics, 1991, pp 23,525-530
           mComp Competitive Report                                                                                                6|P a g e
The initial narrowing based on the Sample Airport Hotel’s (A Hotel) ADR and RevPAR bands yields the following condensed list:


                    A Hotel                                                  H Inn & Suites Airport
                    B Inn                                                    H Inn Airport 2
                    C Suites                                                 H Express
                    C Hotel                                                  H Airport
                    C Inn & Suites                                           L Inn & Suites
                    C Inn                                                    Q Inn & Suites
                    C Suites Airport                                         R Hotel
                    C Inn & Suites Airport                                   R Inn
                    C Airport                                                R Hotel Airport
                    D Inn                                                    R Inn & Suites Airport
                    E Lodge                                                  R Inn Airport
                    E Lodge Airport                                          S Hotel
                    E Suites                                                 S Inn & Suites
                    F Inn                                                    S Suites Center
                    H Inn                                                    S Suites
                    H Lodge                                                  S Suites Airport
                    H Inn Airport                                            S Airport
                    H                                                        T Lodge

                                                   *Eliminated from analysis due to insufficient data




       mComp Competitive Report                                                                                        7|P a g e
clustering analysis
Once outliers have been filtered out, STR Analytics uses a hierarchical
clustering technique based on daily ADR and RevPAR performance
data. This method creates groups such that differences between
individual properties within a group are minimized while differences
between a set are maximized. Properties that compete closely with
one another will be properties that fall into the same group using this
method. Theory suggests that consumers will view close competitors
similarly, and thus competing properties will have underlying
similarities in their ADR and RevPAR histories, which this method can
identify using STR’s daily performance data on each property.
Consequently, properties statistically compete with hotels that fall
within their grouping, while groups once or twice removed from the
subject group compete less directly with the subject.

In the figure to the right, the red boxes identify the groups created by
this method, while the Sample Airport Hotel is marked with a blue dot.

The hotels identified from the clustering analysis with which the
Sample Airport Hotel competes most closely on a statistical basis are
listed on the left in the upper bracket. The bracket below the top
bracket is also closely related based on ADR and RevPAR performance
and has also been included in the analysis. Those properties not
exhibiting a relevant underlying trend will comprise the remaining
brackets. These properties have been deliberately masked in order to
illustrate the focus on the properties most relevant to the Sample
Airport Hotel.




        mComp Competitive Report                                           8|P a g e
market share diagram
The final refinement that ultimately defines the competitive set is the mComp Covariance Plot Technique, which utilizes the covariance of daily
market shares. Once a competitive group has been identified, the mComp Covariance Plot uses a principal component analysis on the covariance
matrix of market shares for the period analyzed. This technique is relevant to the hotel market as it focuses on how market shares fluctuate. Two
hotels that compete closely will have market shares that move together in a systematic way (e.g. they rise and fall together but separate from
other hotels in the cluster; but if a customer chooses Hotel A over Hotel B, then Hotel A’s market share will rise and Hotel B’s will fall relative to
each other). The converse of this is also true. Hotels that do not compete as closely with one another will not have a strong pattern in the
movement of their market shares. The technique behind the mComp Covariance Plot looks for underlying systematic movement in market
shares. Properties that compete most closely with one another are situated proximate to one another in the mComp Covariance Plot.

mComp Covariance Plot
The mComp Covariance Plot, which is centered on the subject
property, provides a statistically and theoretically valid
graphical interpretation of the competitive environment with
respect to the Sample Airport Hotel. The relative position of
the identification dots does not matter, only how far they are
from the Sample Airport Hotel. Dots that are closer to the
Sample Airport Hotel are stronger competitors. The red circles
depict the plot length radius one and a quarter times the
standard deviation from the subject property respectively. The
properties inside the red circles indicate that eight of the
remaining hotels in the group compete most closely with the
Sample Airport Hotel. These include the following hotels: B
Inn, H Inn Airport, H Lodge, H Inn & Suites Airport, R Inn &
Suites Airport, S Suites Airport, S Suites, and S Hotel.




        mComp Competitive Report                                                                                            9|P a g e
descriptive plots
                                                                                                         best-fit
Finally, STR Analytics examines three dimensional trend plots of ADR, Market Share, and RevPAR with best fit spherical analysis. A view of this
                                                                                                                     three-dimensionally examines
type of analysis is presented below, with the Sample Airport Hotel highlighted with a red dot. This type of analysis three
overall performance in ADR and RevPAR and Market Share, and combines there correlations to identifying farther outlying properties as a final
test of reasonableness. In this case the three properties that are further distinguished from the core competitors are The B Inn, the E Suites and
the H Inn Airport.




                                                                            recommended mComp core
                                                                            competitors




                                                                            As determined by these methods, the final core competitive set for
                                                                                                                      below.
                                                                            the Sample Airport Hotel is shown below These properties are
                                                                            considered the strongest competitors to the subject property based
                                                                                      depth                                           data.
                                                                            on our in-depth statistical analysis of their performance data




        mComp Competitive Report                                                                                         10 | P a g e
As determined by these methods, the final core competitive set for the Sample Airport Hotel is shown below. These properties are considered
                                                                  depth                                           data.
the strongest competitors to the subject property based on our in-depth statistical analysis of their performance data


Core Competitors
H Inn Airport
H Inn & Suites Airport
H Lodge
R Inn & Suites Airport
S Hotel
S Suites Airport
S Suites




        mComp Competitive Report                                                                                   11 | P a g e
                    iagram
RPM reconciliation diagram
                                                      in-depth
The RevPAR Positioning Matrix (RPM) allows a more in depth understanding of the performance strategies achieved in your market. The graphs
                                            ary                                                           ompetitors)
below show the RPM of your existing primary competitive set versus the mComp competitive set (Core Competitors) that were recommended
                                                                                                                          RevPAR
on the previous page. As RevPAR performance is a factor of both occupancy and ADR; each individual hotel achieves their RevPA performance
                                                                          environment,
through a unique combination of both. Even while operating in the same environment, certain properties’ strategies will likely push one metric
                                                                                                                               profitability.
harder than the other attempting to achieve the most effective balance of occupancy and ADR to maximize revenue and profitability The
                                                                                                             competitive
mComp report has analyzed all of the hotels in the Sample Airport Hotel market to reveal a potential mComp competitiv set that will allow the
                                                                                       nsight                            (x-axis) versus ADR (Y-
most effective and actionable uses of tools such as the RPM report. The RPM provides insight into the various Occupancy (x
axis) strategies, and simultaneously benchmarks those acachievements against the Sample Airport Hotel.

            mComp Competitive Set                                                          Existing Competitive Set




       mComp Competitive Report                                                                                        12 | P a g e

								
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