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.
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 : 189 airlines have registered, at least, one twitter account 83 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 May 2011 to April 2011, we see: Inbound tweets = stable (from consumer to airlines) Outbound tweets = +24% (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 May 2011.
Section 2: ‘Inbound tweets’ : is the total number of tweets received by airline brands from consumers in May 2011.
Section 2: „Outbound tweets‟ : is the total number of tweets emitted by airlines to consumers in May 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 May 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 May 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: From a record high of 93.8% in March 2011, consumers tweeted less about Customer Service in April 2011 and again, less in May. This is however, our Trending Topic of the month.
Section 3: This category has only decreased ever so slightly from 4.2% in April to May‟s result.
Section 3: The category « Food & Entertainment » has decreased a whole 1% from 3.4% in April to May‟s result.
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.
Section 3: In April 2011, 4.3 % of the tweets mentioned « Luggage Handling » concerns. This category increased slightly in May 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 May 2011‟s consumer tweets, presents the best airline for every category of interest.