Airlines Monthly Twitter Report November 2011 data


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Airlines Monthly Twitter Report November 2011 data

  1. 1. from
  2. 2. eezeer data lab collects, moderates andaggregates on a real-time basis the publictimeline of twitter feeds of all airline brandsand the consumers interacting with them.From this source, we provide a complete setof statistical information on twitter usage inthe airline industry.
  3. 3. Section 1 :  ‘Best in class’ :  Top performing airline brand with the greatest number of public tweets exchanged this month between an airline and its consumers.  Accounts for all the tweets collected :  Outgoing (from airline to consumer)  Incoming (from consumer to airline)
  4. 4. Section 1 : 198 airlines have registered, at least, one twitter account 90 airlines have an active twitter account
  5. 5. Section 1 : ‘Airline Listening Champions” : the top three airlines having received the most tweets from consumers.
  6. 6. Section 1 : ‘Airline Talking Champions” : the top three airlines having sent the most tweets to consumers.
  7. 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. 8. Section 2 :  Comparing November 2011 to October 2011, we see:  Public tweets = + 13%  Growth comes from the consumers interacting more and more with airlines
  9. 9. Section 2 : ‘Total number of tweeting airlines’ : accounts for all the airlines that have created one or more accounts on twitter.
  10. 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 November 2011.
  11. 11. Section 2 : ‘Incoming tweets’ : is the total number of tweets received by airline brands from consumers in November 2011.
  12. 12. Section 2 : „Outgoing tweets‟ : is the total number of tweets emitted by airlines to consumers in November 2011.
  13. 13. Section 2 : ‘Most Followed Airline’  twitter accounts can be followed by other twitter accounts.  The “Most Followed Airline”, North America Focus‟ is the North American airline with the most followers at the end of November 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” North America Focus‟ is the North American airline who follows the most other twitter accounts at the end of November 2011.
  14. 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 (incoming tweets). From the moderated tweets, we can calculate for each and every airline, the nature of the messages sent by consumers.
  15. 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. 16. Section 3 : From a record high of 93.8% in March 2011, consumers tweeted less about Customer Service in recent months, reducing by nearly 10% to June‟s result of 83.1%. But we saw a rise in July, making Customer Service the Trending Topic of the month with an increase of 3.73%, with much the same result in August with 88.2% and a fair drop in September with a result of 83.9%. October once again saw a drop, a 10% drop and the lowest result yet for this category with 73%. November saw an increase, close to Augusts result, achieving 81.8%.
  17. 17. Section 3 : This category has only decreased ever so slightly from 4.2% in April to May‟s result, but saw a 59% increase in June to 7.8%. June‟s result was slightly less at 6%. August saw a result of 4.8%, slightly more than in April. September saw a rise again to 7%. In October we saw the highest result so far with this category with 11.3% but another decrease durign November to 8%, yet this is still the second highest result.
  18. 18. Section 3 : The category « Food & Entertainment » has decreased a whole 1% from 3.4% in April to May‟s result, but has stayed much the same in June and again in July. In August it was in fact our Trending Topic of the month with a 10.6% increase to 1.8% and again in September to 3.9%. During October this category shot up, covering 7.1 % but it dropped substancially again in November to 3.4%.
  19. 19. Section 3 : « Comfort & Security » has nearly halved in concern from a record high of 2.2% in April 2011 to 1.4% in May 2011, but remained much the same in June, with a slight decrease in July and now a slight increase in August to 1.3%. Septembers result matched August‟ with 1.3%. During October, Comfort & Security became our Trending Topic with an increase of 268% to 4.7% but in November it dropped again to 1.7%.
  20. 20. Section 3 : In April 2011, 4.3 % of the tweets mentioned « Baggage Handling » concerns. This category increased slightly in May 2011 to 3.9% and increased over 1% in June, decreasing slightly in July. In August there was a 1% decrease, matching May‟s result as was September‟s result. In October the result remained much the same with 4.0%. In November it was the Trending Topic of the month with a 28% increase reaching coverage of 5.1%.
  21. 21. 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 November 2011 consumer tweets, presents the best airline for every category of interest.
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  27. 27. Section 5 :
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  29. 29. Section 5 :