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from
eezeer data lab collects, moderates and
aggregates on a real-time basis the public
timeline of twitter feeds of all airline brands
and the consumers interacting with them.

From this source, we provide a complete set
of statistical information on twitter usage in
the airline industry.
Section 1 :

               ‘Best in class’ :
               Top performing airline brand with the
                greatest number of all the tweets
                exchanged this month between an
                airline and its consumers.
               Accounts for all the tweets collected :
                  outbound (from airline to consumer)
                   and
                  inbound (from consumer to airline).
Section 1 :




 184 airlines have registered, at least, one twitter
  account
 77 airlines have an active twitter account
Section 1 :




 ‘Airline Listening Champions” :
 the top three airlines having received the most tweets
 from consumers.
Section 1 :




 ‘Airline Talking Champions” :
 the top three airlines having sent the most tweets to
 consumers.
Section 2:

 Beyond collecting, moderating and aggregating the
  twitter time line on the conversation between
  consumer and brands, eezeer data lab, also,
  monitors the information available directly at twitter
  on the airlines accounts.
 It allows for additional sets of data that permits
  other view of the airlines‟ activity over twitter.
Section 2:

              Comparing April 2011 to
               March 2011, we see :
              Inbound tweets = stable
              (from consumer to airlines)
              Outbound tweets = +25%
              (from airlines to consumer)
              Growth comes from the
              consumers interacting more
              and more with airlines
Section 2:




 ‘Total number of tweeting airlines’ :
 accounts for all the airlines that have created one or
 more accounts on twitter.
Section 2:




 ‘Active tweeting airlines’ :
 some airlines have created accounts that are not yet
 active. For eezeer data lab, an “active tweeting
 airline” has sent or received an average of at least 5
 tweets daily over the month of April 2011.
Section 2:




 ‘Inbound tweets’ :
 is the total number of tweets received by airline
 brands from consumers in April 2011.
Section 2:




 „Outbound tweets‟ :
 is the total number of tweets emitted by airlines to
 consumers in April 2011.
Section 2:




 ‘Most Followed Airline’
    twitter accounts can be followed by other twitter accounts.
    The “Most Followed Airline” is the airline with the most followers at the end of April 2011.
 ‘Most Following Airline’
    twitter accounts can follow other twitter accounts, consequently listening to the chatter on the
     public timeline of these users.
    The “Most Following Airline” is the airline who follows the most other twitter accounts at the
     end of April 2011.
Section 3:
 eezeer data lab collects, moderates and aggregates the
  content of all the tweets to and from airlines brands.
 These tweets are assigned and rated according to one or
  more of six consumer‟s category of interest :
      social conversation,
      customer service,
      timeliness,
      food & entertainment,
      comfort &security and
      luggage handling.
 This section focuses on the tweets from the consumers to the
  airlines (inbound tweets).
 From the moderated tweets, we can calculate for each and
  every airline, the nature of the messages sent by
  consumers.
Section 3:



 Airlines talk to consumers while consumers tweet their
  concerns and satisfactions to airlines.
 Consumers have « subjects » about which they talk
  positively or negatively.
 Often, airlines answer in a much more neutral manner
Section 3:




 Between March 2011 and April 2011, tweets referring to
  « Timeliness » issues grew considerably
 Over the same period, tweets referring to « Customer
  Service » decrased drastically
 Consumers are tweeting more precise requests to airlines
Section 3:




 From a record high of 93.8% in March 2011,
 consumers tweeted less about Customer Service in
 April 2011.
Section 3:




 Measured at 1.2% of the tweets in March 2011, this
  category of tweets has almost been multiplied by 4.
 It is our monthly « Trending Topic ».
Section 3:




 The category « Food & Entertainment » has doubled
 as the subject of tweets (April 2011 vs March 2011).
Section 3:




 From a record high of 1.1% in March 2011 to 2.2%
 in April 2011, « Comfort & Security » is a rising item
 of concern.
Section 3:




 In March 2011, 2.2 % of the tweets mentioned
 « Luggage Handling » concerns. This category
 almost doubled in April 2011.
Section 4:
 As tweets are assigned to a consumer‟s category of interest,
  they are also reviewed and rated by eezeer‟s moderation
  team. The rating attributed can be positive, neutral or
  negative. By aggregating category and rating data, we can
  rank the airlines on each of these categories of interest.
 eezeer data lab calculations compare positive and negative
  tweets to the total number of tweets received by each airline
  for that category of interest.
 This method attributes a score to the airline on each category
  of interest. These scores rank and compare airlines together.
  A score of 100 represents the average of all airlines in a
  category.
 This section, based on April 2011‟s consumer tweets,
  presents the best airline for every category of interest.
Section 4:




 2nd : Air France (107.0), 3rd : West Jet Airlines (106.7)
 In the top 10 airlines, we find :
    4 North American airlines,
    3 European airlines,
    3 Asian Pacific airlines
Section 4:




 2nd : West Jet Airlines (105.1), 3rd : Porter Airlines (105.1)
 In the top 10 airlines, we find :
    4 North American airlines,
    3 European airlines,
    3 Asian Pacific airlines
Section 4:




 2nd : Spice Jet (103.7), 3rd : Jet Airways (102.1)
 In the top 10 airlines, we find :
    5 North American airlines,
    3 European airlines,
    2 Asian Pacific airlines
Section 4:




 2nd : Cebu Pacific (111.4), 3rd : Alaska Airlines (111.0)
 In the top 10 airlines, we find :
    7 North American airlines,
    1 European airlines,
    2 Asian Pacific airlines
Section 4:




 2nd : Frontier Airlines (112.6), 3rd : West Jet Airlines (106.4)
 In the top 10 airlines, we find :
    7 North American airlines,
    2 European airlines,
    1 Asian Pacific airlines
Section 5:
Section 5:
        Once attributed to a consumer
         category of interest, tweets can
         have a positive, neutral or
         negative appreciation of the
         item by the consumer.
        « Comfort & Security » is the
         top rated category by
         consumers where positive
         appreciation are more important
         than negative appreciation.
Section 5:
        In a general manner, we can
        say that consumers tweet
        almost equally satisfaction and
        dissatisfaction when they tweet
        about airline‟s « Customer
        Service ».
Section 5:
        When a consumer tweets an
         airline and the subject of it
         relate to « Timeliness », more
         than likely, its appreciation
         will be negative.
        This month it appears to have
         been the most negatively
         appreciated item.
Amtr   april 2011 data

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Amtr april 2011 data

  • 2. eezeer data lab collects, moderates and aggregates on a real-time basis the public timeline of twitter feeds of all airline brands and the consumers interacting with them. From this source, we provide a complete set of statistical information on twitter usage in the airline industry.
  • 3. Section 1 :  ‘Best in class’ :  Top performing airline brand with the greatest number of all the tweets exchanged this month between an airline and its consumers.  Accounts for all the tweets collected :  outbound (from airline to consumer) and  inbound (from consumer to airline).
  • 4. Section 1 :  184 airlines have registered, at least, one twitter account  77 airlines have an active twitter account
  • 5. Section 1 :  ‘Airline Listening Champions” :  the top three airlines having received the most tweets from consumers.
  • 6. Section 1 :  ‘Airline Talking Champions” :  the top three airlines having sent the most tweets to consumers.
  • 7. Section 2:  Beyond collecting, moderating and aggregating the twitter time line on the conversation between consumer and brands, eezeer data lab, also, monitors the information available directly at twitter on the airlines accounts.  It allows for additional sets of data that permits other view of the airlines‟ activity over twitter.
  • 8. Section 2:  Comparing April 2011 to March 2011, we see :  Inbound tweets = stable (from consumer to airlines)  Outbound tweets = +25% (from airlines to consumer)  Growth comes from the consumers interacting more and more with airlines
  • 9. Section 2:  ‘Total number of tweeting airlines’ :  accounts for all the airlines that have created one or more accounts on twitter.
  • 10. Section 2:  ‘Active tweeting airlines’ :  some airlines have created accounts that are not yet active. For eezeer data lab, an “active tweeting airline” has sent or received an average of at least 5 tweets daily over the month of April 2011.
  • 11. Section 2:  ‘Inbound tweets’ :  is the total number of tweets received by airline brands from consumers in April 2011.
  • 12. Section 2:  „Outbound tweets‟ :  is the total number of tweets emitted by airlines to consumers in April 2011.
  • 13. Section 2:  ‘Most Followed Airline’  twitter accounts can be followed by other twitter accounts.  The “Most Followed Airline” is the airline with the most followers at the end of April 2011.  ‘Most Following Airline’  twitter accounts can follow other twitter accounts, consequently listening to the chatter on the public timeline of these users.  The “Most Following Airline” is the airline who follows the most other twitter accounts at the end of April 2011.
  • 14. Section 3:  eezeer data lab collects, moderates and aggregates the content of all the tweets to and from airlines brands.  These tweets are assigned and rated according to one or more of six consumer‟s category of interest :  social conversation,  customer service,  timeliness,  food & entertainment,  comfort &security and  luggage handling.  This section focuses on the tweets from the consumers to the airlines (inbound tweets).  From the moderated tweets, we can calculate for each and every airline, the nature of the messages sent by consumers.
  • 15. Section 3:  Airlines talk to consumers while consumers tweet their concerns and satisfactions to airlines.  Consumers have « subjects » about which they talk positively or negatively.  Often, airlines answer in a much more neutral manner
  • 16. Section 3:  Between March 2011 and April 2011, tweets referring to « Timeliness » issues grew considerably  Over the same period, tweets referring to « Customer Service » decrased drastically  Consumers are tweeting more precise requests to airlines
  • 17. Section 3:  From a record high of 93.8% in March 2011, consumers tweeted less about Customer Service in April 2011.
  • 18. Section 3:  Measured at 1.2% of the tweets in March 2011, this category of tweets has almost been multiplied by 4.  It is our monthly « Trending Topic ».
  • 19. Section 3:  The category « Food & Entertainment » has doubled as the subject of tweets (April 2011 vs March 2011).
  • 20. Section 3:  From a record high of 1.1% in March 2011 to 2.2% in April 2011, « Comfort & Security » is a rising item of concern.
  • 21. Section 3:  In March 2011, 2.2 % of the tweets mentioned « Luggage Handling » concerns. This category almost doubled in April 2011.
  • 22. Section 4:  As tweets are assigned to a consumer‟s category of interest, they are also reviewed and rated by eezeer‟s moderation team. The rating attributed can be positive, neutral or negative. By aggregating category and rating data, we can rank the airlines on each of these categories of interest.  eezeer data lab calculations compare positive and negative tweets to the total number of tweets received by each airline for that category of interest.  This method attributes a score to the airline on each category of interest. These scores rank and compare airlines together. A score of 100 represents the average of all airlines in a category.  This section, based on April 2011‟s consumer tweets, presents the best airline for every category of interest.
  • 23. Section 4:  2nd : Air France (107.0), 3rd : West Jet Airlines (106.7)  In the top 10 airlines, we find :  4 North American airlines,  3 European airlines,  3 Asian Pacific airlines
  • 24. Section 4:  2nd : West Jet Airlines (105.1), 3rd : Porter Airlines (105.1)  In the top 10 airlines, we find :  4 North American airlines,  3 European airlines,  3 Asian Pacific airlines
  • 25. Section 4:  2nd : Spice Jet (103.7), 3rd : Jet Airways (102.1)  In the top 10 airlines, we find :  5 North American airlines,  3 European airlines,  2 Asian Pacific airlines
  • 26. Section 4:  2nd : Cebu Pacific (111.4), 3rd : Alaska Airlines (111.0)  In the top 10 airlines, we find :  7 North American airlines,  1 European airlines,  2 Asian Pacific airlines
  • 27. Section 4:  2nd : Frontier Airlines (112.6), 3rd : West Jet Airlines (106.4)  In the top 10 airlines, we find :  7 North American airlines,  2 European airlines,  1 Asian Pacific airlines
  • 29. Section 5:  Once attributed to a consumer category of interest, tweets can have a positive, neutral or negative appreciation of the item by the consumer.  « Comfort & Security » is the top rated category by consumers where positive appreciation are more important than negative appreciation.
  • 30. Section 5:  In a general manner, we can say that consumers tweet almost equally satisfaction and dissatisfaction when they tweet about airline‟s « Customer Service ».
  • 31. Section 5:  When a consumer tweets an airline and the subject of it relate to « Timeliness », more than likely, its appreciation will be negative.  This month it appears to have been the most negatively appreciated item.