What Can Businesses Learn from Text Mining

Topics: Text mining, Privacy, Data mining Pages: 6 (2160 words) Published: November 26, 2012
Case StudyWhat Can Businesses Learn From Text Mining?Text mining is the discovery of patterns and relationships from large sets of unstructured data – the kind of data we generate in e-mails, phone conversations, blog postings, online customer surveys, and tweets. The mobile digital platform has amplified the explosion in digital information, with hundreds of millions of people calling, texting, searching, “apping” (using applications), buying goods and writing billions of e-mails on the go.Consumers today are more than just consumers: they have more ways to collaborate, share information, and influence the opinions of their friends and peers; and the data that they create in doing so have significant value to businesses. Unlike structured data, which are generated from events such as completing a purchase transaction, unstructured data have no distinct form. Nevertheless, managers believe such data may offer unique insights into customer behaviour and attitudes that were much more difficult to determine years ago.For example, in 2007 JetBlue (the American Airline) experienced unprecedented levels of customer discontent in the wake of a February ice storm that resulted in widespread flight cancellations and planes stranded on Kennedy Airport runways. The airline received 15,000 emails per day from customers during the storm and immediately afterwards, up from its usual daily volume of 400. The volume was so much larger than usual that JetBlue had no simple way to read everything that its customers were saying.Fortunately, the company had recently contracted with Attensity, a leading vendor of text analytics software, and was able to use the software to analyze all of the e-mail it had received within two days. According to JetBlue research analyst Bryan Jeppsen, Attensity Analyze for Voice of the Customer (VoC) enabled JetBlue to rapidly extract customer sentiments, preferences, and requests it couldn’t find any other way. This tool uses a proprietary technology to automatically identify facts, opinions, requests, trends, and trouble spots from the unstructured text of survey responses, survey notes, e-mail messages, Web forums, blog entries, news articles, and other customer communications. The technology is able to accurately and automatically identify and many different “voices” customers use to express their feedback (such as a negative voice, positive voice, or conditional voice) which helps organisations pinpoint key events and relationships, such as intent to buy, intent to leave, or customer “wish” events. It can reveal specific product and service issues, reactions to marketing and public relations efforts, and even buying signals.Attensity’s software integrated with JetBlue’s other customer analysis tools, such as Satmetrix’s Net Promoter metrics, which classifies customers into groups that are generating positive, negative, or no feedback about the company. Using Attensity’s text analytics in tandem with these tools, JetBlue developed a customer bill of rights that addressed the major issues customers had with the company.Hotel chains like Gaylord Hotels and Choice Hotels are using text mining software to glean insights from thousands of customer satisfaction surveys provided by their guests. Gaylord Hotels is using Clarabridge’s text analytics solution delivered via the Internet as a hosted software service to gather and analyze customer feedback from surveys, e-mail, chat messaging, staffed call centres, and online forums associated with guests’ and meeting planners’ experiences at the company’s convention resorts. The Clarabridge software sorts through the hotel chain’s customer surveys and gathers positive and negative comments, organizing them into a variety of categories to reveal less obvious insights. For example, guests complained about many things more frequently than noisy rooms, but complaints about noisy rooms were most frequently correlated with surveys indicating an unwillingness to return to the...

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