What Can Businesses Learn from Text Mining
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
Bibliography: Online Sources Daily Mail Online (2010) Big Brother society is bigger than ever: New technology is ‘undermining privacy by stealth’ Available at: http://www.dailymail.co.uk/news/article-1328445/Big-Brother-society-bigger-New-technology-undermining-privacy-stealth.html#ixzz1s9qMFfIg (Accessed 10/04/2012) JISC (2012) The Value and Benefit of Text Mining to UK Further and Higher Education. Digital Infrastructure Available at: http://bit.ly/jisc-textm (Accessed 10/04/2012) Nucleus Research (2007) SPSS Text Mining. Available at: http://www.spss.ch/eupload/File/PDF/Guidebook%20--%20SPSS%20Text%20Mining.pdf (Accessed 10/04/2012) World Academy of Science, Engineering and Technology (2005) Powerful Tool to Expand Business Intelligence: Text Mining. Available at: http://www.waset.org/journals/waset/v8/v8-21.pdf (Accessed 10/04/2012)