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Data Mining Hotel Data Analysis (0)

5 VÄGA HEA
Punktid
TALLINN  UNIVERSITY  OF  TECHNOLOGY
Institute of Informatics
Department of Informatics
Chair of Foundations of Informatics
Analysis  of  Hotel  Data
2nd  Task  for Data Mining   Course
IDN0100
Student :
Matriculation ID:
E-mail:
Supervisor:  Innar  Liiv
TALLINN
2011
Findings:
 The  hotel  is business oriented, which is supported by the high percentage of business
occupants, and the multitude of conventions held   within the hotel. The  statement  is further
supported by the  fact  that occupancy drops with the  decrease  of influx of business people.
 The occupancy drops significantly in the  July  and August which is probably due to the fact
that businesses generally run slower in that  part  of the  summer  (due to plague  of vacations)
in the  northern hemisphere on latitudes with explicit seasonal  changes . Therefore, the hotel
must be  located on the part of the  globe  described.
 The occupancy by  women seems to be somewhat statistically correlated with percentage of
tourists residing in the hotel. This may imply that the most business people staying in the
hotel are men.
 The women occupancy seems to peak  at three points: April, October and December. The
latter  is probably due to couples and  families  (influx of people aged under 20 is in December
and October too)  going  on vacation for  Christmas , New  Year ’s Eve and other  seasonal
holidays .
 The  length of the  stay  is the shortest in December, which may  serve  as further  proof  for the
above  theory of families coming in for the  winter  holidays.
 The  average  length of stay also tends to drop significantly as tourists  gain in occupancy
percentage, which may indicate that the  location  of the hotel is not very favourable to
tourism  business as the area can probably be explored quickly.
 The conventions seem  to  affect  the average length of stay positively. This may be due to the
fact that conventions attract a notable number of occupants that are  bound to stay for the
span of the  whole  convention, which, on average, implies at  least  two day long stay.
 It would seem that 33-55 year-olds are more prone to use reservation through the  agency  that
any other customer group, whereas 20-35 year-olds seem to be favouring  direct  reservations.
This may be due to the fact that the older generation is keener on personal assistance they get
at the agencies and find  additional source of security in having  a  middle -man supposedly at
their side. The younger people are more independent in their ways and are better at
navigating the  available  information (hotel listings in print , most probably, as the data was
sampled before  the  advent  of digital era).
Suggestions:
As the hotel is not a pot of  gold and cannot  possibly appeal to everybody and its target  audience
seems to consist of business-minded people, it's best  to concentrate on that target group as it would
appear that the hotel is quite  well equipped for that. So, strengthening the  good point  first , so that
instead of being simply good they're excellent ( plus oftentimes it's easier  to make a good thing
excellent  than to make a bad thing  even  mediocre-good).
 Monthly pricing should be adjusted to the  current  data on visitor tendencies – the  lower  the
amount  of visitors, the lower the  price .
 Price  policy  can also be dynamic – lower when a multitude of  rooms is available and when
the  date  draws closer and over, say, 10 percent  of rooms are  still  available,  higher  when
rooms are  getting  massively reserved for a distant date.
 Introduce loyalty programs for corporations, offer  bargains for conferences.
 Encourage conventions – invest in some  equipment  that would put this very hotel at a
competitive  advantageMarket  the hotel as a convention venue.
 Seek contacts and  relationship establishment with the business world; advertise in business
print issues (when the data was gathered there  has been no web ones ).
 As summer is evidently the slowest  season and the season of mass corporate  drowsing, the
hotel  could appeal to tour operators and even airlines for  affiliate  cooperation.
 Offer added value  to business clients – do a market research on what could possibly be
useful to such visitors and equip rooms with said facilities that would put the hotel at an
advantage.
Data Mining Hotel Data Analysis #1 Data Mining Hotel Data Analysis #2 Data Mining Hotel Data Analysis #3
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