This essay describes an analysis in 3 questions how people interact online with US Airlines Carrier in USA through PC and Mobile devices. It has been identified a descriptive analysis of the comScore spreadsheets, number of real passengers and finally a correlation between online search behaviour and passenger data.

1. Big
Data
in
the
Airline
Industry
IS
Strategy
&
Enterprise
System
Assigment
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2. Big
Data
in
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Airline
Industry
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Table
of
Contents
Summary
...............................................................................................................
3
1.
Descriptive
analysis
of
the
comScore
data
..........................................................
3
2013
.........................................................................................................................................................................
3
2014
.........................................................................................................................................................................
6
Conclusions
...........................................................................................................................................................
9
2.
Market
share
table
for
the
time
period
2010
–
2014.
..........................................
9
3.
Correlation
analysis
between
passenger
data
and
online
search
behavior
........
11
Interpretation
of
the
graphs
.......................................................................................................................
12
References
...........................................................................................................
13

3. Big
Data
in
the
Airline
Industry
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Summary
People now use both desktop and mobile device to surfing on Internet. It
essay will describe an analysis in 3 questions how people interact online with
US Airlines Carrier in USA through PC and Mobile devices. It will be identified
a descriptive analysis of the comScore spreadsheets, number of real
passengers and finally a correlation between online search behavior and
passenger data.
1.
Descriptive
analysis
of
the
comScore
data
For this question it has been decided to exclude smaller competitors and
companies with missing data. It was assumed it doesn’t affect the total data.
2013
Fig. 1. Total Unique Visitors/Viewers. (Source:comScore)
Fig. 1 above refers to the provided data in March 2013 related to Unique
Visitors. The Total Digital Population of PC and Mobile users is approximately
237 millions. From this total 223 millions of user belong to PC while 121
million user proceed from Mobile devices; 106 millions only use PC; 14 million
only use mobile and 117 millions of users use PC and mobile.
It could be concluded that in 2013 PCs were the channel to search in the main
airlines websites.
117M.
106M.
14M.
237 M.
Total
Digital
Population
PC
Mobile

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Data
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Airline
Industry
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Fig. 2: Total Unique Visitor (000) per Airline in 2013. (Source: comScore)
The graph above represents a summary of unique visitors per airlines. It was
divided in PC; mobile; and PC and Mobile users. This three categories are
related for each airline website. Southwest.com lead the table with values
around 10 millions in PC, 4 millions in Mobile and 1 million in PC and mobile
of unique visitors/viewers, whereas Allegantiar.com had the smallest visitors,
It just reached 1M in PC and less of 1 in the other categories.
Southwest.com, Delta.com, United.com, aa.com and jetblue.com have
presented the highest results in March 2013. By contrast airtran.com,
spirit.com, alaskaairlines.com, flyfrontier.com allegiantair.com ranging from
about 1 to 2 million using PC, in Mobile the total number of viewers were from
294,000 to 825,000.
In general Unique Visitors preferred using a PC instead of a Mobile to search
for flights on Internet.
Fig. 3: Total Views (MM) in PC in 2013. (Source: comScore)
On March 2013 Total views of airlines websites through a PC are presented in
the pie above. Southwest.com and Delta.com reached a 45% of the views
24%
21%
15%
16%
3%
5%
2%
5%
4%
2%
3%
SOUTHWEST.COM
DELTA.COM
UNITED.COM
AA.COM
JETBLUE.COM
USAIRWAYS.COM
AIRTRAN.COM
SPIRIT.COM
ALASKAAIRLINES.COM

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and on the other hand Flyfrontier.com and Airtran.com just accounted 2% of
views each one.
Fig. 4: Total Views (MM) in Mobile Phones in 2013. (Source: comScore)
By contrast the pie above presented the total views using mobile devices in
March 2013. This pie clearly illustrated a varied segmentation and at the
same time evidenced how Delta.com decrease drastically to 7% of views and
some of the lower airlines sites concerning to views in PC, here, achieve
significant results.
Southwest was gained the highest value corresponding to 31% of the views
and Spirit the worst result with 1% of views.
Fig. 5: Total Minutes (MM) in Mobile and PC in 2013. (Source: comScore)
31%
7%
12%
18%
9%
10%
6%
1%
1%
2%
3%
SOUTHWEST.COM
DELTA.COM
UNITED.COM
AA.COM
JETBLUE.COM
USAIRWAYS.COM
AIRTRAN.COM
SPIRIT.COM
ALASKAAIRLINES.COM
FLYFRONTIER.COM
ALLEGIANTAIR.COM
156
130
97
95
30
42
14
24
21
11
16
34
22
15
14
8
12
6
1
3
2
4
0
20
40
60
80
100
120
140
160
180
200
Total
Minutes
(MM)
Airlines
Mobile
PC

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The bar chart above has indicated the total minutes a person spent in the
website using a PC or a Mobile.
It can be seen that minutes in front a PC to search a flight was higher in
comparison with Mobile devices. In a PC, 156 million of minutes were spent
on Southwest.com followed by 130 million of minutes in Delta.com.
United.com and AA.com were not far behind with 95 millions of minutes
approximately. However, on Mobile devices the time spent was significantly
different for the same data describe before. In this segment it was reached
from 34 million of minutes in Southwest.com to 1 million in Spirit.com.
2014
Fig. 6. Total Unique Visitors/Viewers. (Source:comScore)
Venn Diagram above refers to the values provided in March 2014 and they
are related to unique online Visitors/Viewers in the US air carriers. In this
month Total Digital Population of PC and Mobile users was reached 249
millions. From this big set 227 millions of user fall to PC subset while 167
million user proceed from Mobile devices; 82 millions only use PC; 22 million
only use mobile and 145 millions of users use PC and mobile to access to
airlines websites.
145M.
82M.
22M.
249 M.
Total
Digital
Population
PC
Mobile

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Fig. 7: Total Unique Visitors (000) per Airline in 2014. (Source: comScore)
The bar graph above illustrates three data sets: PC, Mobile, PC&Mobile of
Unique Visitors in March 2014. In a high level, use of PC as a channel was
the most representative in this month followed by Mobile.
Southwest.com and Delta kept positioning in the first places, although Delta
presented a lightly increase using Mobile devices with 3, 5 millions of viewers
whereas Southwest.com had 3.1 millions in the same channel. United.com,
Aa.com and Jetblue.com belong to the 5 websites with more viewers in the 3
channels. On the other hand Spirit.com, Alaskaairlines.com, Airtraing.com
and Flyfrontier.com are the companies with less visitors. The last ones
together have reached 4, 1.1 and 0,1 millions of unique viewers in PC, Mobile
and PC&Mobile respectively.
Fig. 8: Total Views (MM) in PC in 2014. (Source: comScore)
21%
25%
17%
16%
4%
4%
2%
4%
4%
1%
2%
SOUTHWEST.COM
DELTA.COM
AA.COM
UNITED.COM
JETBLUE.COM
USAIRWAYS.COM
ALLEGIANTAIR.COM
SPIRIT.COM
ALASKAAIRLINES.COM
AIRTRAN.COM

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The pie above presented Total views of airlines websites on March 2014
using a PC. Southwest.com and Delta.com reached a 46% of the views and
on the other hand Flyfrontier.com and Allegiantair.com just accounted 2% of
views each one and Airtran.com 1% of views.
Fig. 9: Total Views (MM) in Mobile Phones in 2014. (Source: comScore)
By contrast, Views on Mobile devices on March 2014 evidence three great
websites with more views: Delta.com (35% views), Aa.com (28% views) and
Southwest.com (14%). The 23% left is shared by the 8 websites remaining.
Fig. 10: Total Minutes (MM) in Mobile and PC in 2014. (Source: comScore)
14%
35%
28%
9%
7%
2%
3%
0%
1%
1%
0%
SOUTHWEST.COM
DELTA.COM
AA.COM
UNITED.COM
JETBLUE.COM
USAIRWAYS.COM
ALLEGIANTAIR.COM
SPIRIT.COM
ALASKAAIRLINES.COM
AIRTRAN.COM
FLYFRONTIER.COM
121
107
73
91
25
31
15
19
21
4
17
28
91
33
41
5
3
7
1
2
1
2
0
50
100
150
200
250
PC
Mobile

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The bar chart above indicates the total minutes a user spent in the website
using a PC or a Mobile device.
It can be seen that minutes in front a PC to search a flight was higher than
Mobile devices. In this year Delta.com showed and significantly increase in
minutes spent in mobile, it is almost balanced with total minutes using a PC.
Southwest was the leader with a total of 149 millions of minutes whereas
Airtrain.com was the worst with 5 millions of minutes.
Conclusions
Unique visitor preferred search flight in a PC rather in a Mobile device.
Southwest.com was steady in 2013 and 2014 whereas Delta improved its
results in Mobile channel. It could be because its app mobile was re design in
2014. United.com, Aa.com, and Jetblue.com were fought shoulder to shoulder
in both years.
Views and Total minutes were directly related to unique visitors.
2.
Market
share
table
for
the
time
period
2010
–
2014.
Passengers
US Carriers 2010 2011 2012 2013 2014 2010 -2014
Total Passengers 717,744,056 728,368,297 734,322,469 740,859,387 303,839,192 3,225,133,401
Southwest Airlines 106,227,521 110,586,815 112,234,074 115,322,785 49,487,314 493,858,509
Delta Air Lines 109,329,792 112,016,262 114,958,112 118,933,921 49,882,256 505,120,343
American Airlines 86,086,130 86,035,851 86,330,792 86,820,595 35,885,254 381,158,622
United Air Lines 53,032,240 49,619,083 91,493,988 89,278,038 36,041,659 319,465,008
JetBlue Airways 24,198,698 26,352,900 28,934,369 30,427,534 12,745,231 122,658,732
US Airways 51,810,721 52,919,646 54,236,961 57,005,389 23,817,567 239,790,284
Spirit Air Lines 6,750,835 8,296,297 10,176,191 12,098,255 5,495,865 42,817,443
Alaska Airlines 16,475,351 17,781,491 18,494,613 19,699,599 8,142,994 80,594,048
AirTran Airways 24,558,468 24,595,735 21,744,597 17,817,319 4,599,604 93,315,723
Frontier Airlines 9,250,686 10,595,626 10,312,607 10,207,534 4,209,044 44,575,497
Virgin America 3,891,100 5,006,329 6,212,914 6,317,311 2,612,456 24,040,110
Hawaiian Airlines 8,417,732 8,659,205 9,476,251 9,918,745 4,022,621 40,494,554
Envoy Air 16,246,048 17,347,591 18,730,881 17,748,299 6,766,740 76,839,559
ExpressJet Airlines 13,930,942 14,218,126 32,376,038 32,956,476 12,665,954 106,147,536
SkyWest Airlines 24,218,092 24,407,881 26,153,130 27,131,161 10,984,416 112,894,680
Airlines 77% 78% 87% 88% 88% 83%
Other Airlines 23% 22% 13% 12% 12% 17%
Table 1. Number of Passengers (Source: RITA)
The table above present a summary of the data extracted of Research and
Innovative Technology Administration (RITA) Bureau of Statistics. It is shown
the main airlines companies who provided data and only the U.S. Carriers
between 2010 and 2014. This values included domestic and international
flights. For this table it was accounted only the percentage of passengers of
the main airlines. It could be seen each year main airlines gained more
customers than the other airlines (generally, small companies). It was started

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with a 77% of the Total of passengers in 2010 and finished with 88% of the
total of passengers in 2014.
The last column of the table contains the accumulation of number of
passengers (2010-2014) per airline. Thus, taking 83% of the total (3,2 billions
of passengers), it is presented the following market share graph:
Fig 11. Market Share of Passenger between 2010-2014. Source: RITA
It pie consolidated the billion of passengers that took flights per US carriers
main airlines. The total of passenger considered to build this pie was 88% of
total of passengers between 2010 and 2014. The 12% remaining belonged to
other airlines without information.
Undoubtedly the market was lead by Delta Airlines (19%) and Southwest
Airlines (18%) in a steady way, in this period of time, it means a constant
number of passenger decided to take these airlines to travel in U.S. or to a
foreign country. American Airlines (14%), United Air Lines (12%) were
remained fairy constant at this period. Around 9% and 5 per cent referred to
US Airways and JetBlue Airways respectively. A minority (4 per cent of the
total) has preferred to fly in SkyWest and ExpressJet airlines. Finally, less
than a fifth of passengers decided to travel in the six US air carriers left.
Seeing these results (table and pie graph) it could be noticed that the market
has been almost segmented equitably during this period of time. It would be
concluded there were not drastic changes according to the number of
passengers and their selections.
18%
19%
14%
12%
5%
9%
2%
3%
3%
2%
1%
1%
3%
4%
4%
Number
of
Passenger
between
2010
and
2014
(May)
Southwest
Airlines
Delta
Air
Lines
American
Airlines
United
Air
Lines
JetBlue
Airways
US
Airways
Spirit
Air
Lines
Alaska
Airlines
AirTran
Airways
Frontier
Airlines
Virgin
America
Hawaiian
Airlines
Envoy
Air
ExpressJet
Airlines
SkyWest
Airlines

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Data
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3.
Correlation
analysis
between
passenger
data
and
online
search
behavior
For this question it was be considered just 10 air companies in order to relate
online data (comScore) and passenger data (RITA)
Fig 11. Correlation Number of Passengers vs. Unique Visitors 2013
The previous linear graph shows the correlation between real number of
passenger vs. unique visitors of 10 websites airlines.
It can be observed most of the points in the graph were closed to the line and
have positive values. It could mean whether unique visitors increase, number
of passengers increase as well. The R squared value obtained is 0.81 that
also might indicate a direct correlation.
R²
=
0.80731
0
2
4
6
8
10
12
14
16
0
50
100
150
Unique
Visitors
Millions
Number
of
Passengers
Millions

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Data
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Airline
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Fig 11. Correlation Number of Passengers vs. Unique Visitors 2014
In 2014 R2
= 0.93, which means that the unique viewers, determine 93% of
the number of passenger in a specific airline. Although 2014 has not finished
yet, it presents sustainable values that affirm la correlation found in 2013.
Interpretation
of
the
graphs
Both graphs 2013 and 2014 pointed that online campaigns of the different
airline companies have had effect in their sales significantly. Thus these
models could estimate expenses in marketing online to gain more unique
visitors. This concludes that, the models applied (marketing online campaign)
could statistically predict the number of passengers.
R²
=
0.93453
0
2
4
6
8
10
12
0
10
20
30
40
50
60
Unique
Visitors
Millions
Number
of
passengers
Millions

13. Big
Data
in
the
Airline
Industry
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13
References
1. Analytics
for
a
Digital
World
-­‐
comScore,
Inc.
2014.
Analytics
for
a
Digital
World
-­‐
comScore,
Inc.
[ONLINE]
Available
at:
http://www.comscore.com/.
[Accessed
20
November
2014].
2. Data
Elements.
2014.
Data
Elements.
[ONLINE]
Available
at:http://www.transtats.bts.gov/Data_Elements.aspx?Data=1.
[Accessed
20
November
2014].
3. Big
data:
The
next
frontier
for
innovation,
competition,
and
productivity
|
McKinsey
&
Company.
2014.
Big
data:
The
next
frontier
for
innovation,
competition,
and
productivity
|
McKinsey
&
Company.
[ONLINE]
Available
at:http://www.mckinsey.com/insights/business_technology/big_data_th
e_next_frontier_for_innovation.
[Accessed
20
November
2014].