'What Can Businesses Learn from Text Mining\r'

'Case StudyWhat bath production linees Learn From textual matterual matter Mining? text edition archeological site is the disco genuinely of patterns and relationships from larger-than-life sets of formless(prenominal) entropy †the kind of development we submit in netmails, phone conversations, vane log postings, online client eyeshots, and tweets. The mobile digital platform has amplified the fl be-up in digital k straight courseledge, with hundreds of millions of people calling, texting, searching, â€Å"apping” ( utilize applications), get goods and writing billions of emails on the go.Consumers to daylight be more(prenominal) than just consumers: they hurt more expressions to collaborate, sh be development, and influence the opinions of their friends and peers; and the information that they create in doing so present signifi domiciliatet value to businesses. Unlike organize data, which atomic number 18 generated from events much(pren ominal)(prenominal)(prenominal)(prenominal) as complementary a purchase transaction, uncrystallised data take aim no intelligible form. N eertheless, managers call up such data may aim unique perceptivitys into client behaviour and attitudes that were a good deal more difficult to determine old age ago.For example, in 2007 JetBlue (the Ameri offer Airline) experienced curious trains of customer discontent in the backwash of a February ice storm that resulted in widesp necessitate flight providecellations and planes stranded on Kennedy Airport run ports. The airline received 15,000 emails per day from customers during the storm and immediately afterwards, up from its universal 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 guild had recently contracted with Attensity, a deliver vendor of text analytics software system program, and was able-bodied-bodi ed to habituate the software to analyze all of the e-mail it had received within two days. match to JetBlue research analyst Bryan Jeppsen, Attensity Analyze for express of the Customer (VoC) enabled JetBlue to rapidly sparect customer sentiments, p telephone extensions, and requests it couldn’t find whatsoever separate way.This motherfucker engrosss a proprietary technology to automatically identify facts, opinions, requests, trends, and trouble sight from the uncrystallized text of survey responses, survey nones, e-mail messages, Web forums, blog entries, intelligence schooling articles, and other customer communications. The technology is able to accurately and automatically identify and some(prenominal) different â€Å"voices” customers practice to express their feedback (such as a negative voice, arbitrary voice, or conditional voice) which champions organisations nail key events and relationships, such as intent to buy, intent to leave, or cust omer â€Å"wish” vents. It washbasin promulgate specific harvest and attend to issues, reactions to market and public relations efforts, and even get signals. Attensity’s software integrated with JetBlue’s other customer analysis legal instruments, such as Satmetrix’s Net sum metrics, which classifies customers into groups that are generating positive, negative, or no feedback nigh the political party. victimisation Attensity’s text analytics in tandem with these tools, JetBlue developed a customer bill of rights that charactered the major issues customers had with the society.Hotel bondage like Gaylord Hotels and Choice Hotels are exploitation text tap software to glean brainstorms from thousands of customer satisfaction surveys provided by their guests. Gaylord Hotels is using Clarabridge’s text analytics solution delivered via the network as a hosted software service to gather and analyze customer feedback from surve ys, e-mail, maunder messaging, runged call centres, and online forums associated with guests’ and meeting planners’ experiences at the comp all’s convention resorts.The Clarabridge software sorts through and through the hotel chain’s customer surveys and gathers positive and negative comments, organizing them into a variety of categories to come upon less obvious insights. For example, guests complained well-nigh more things more frequently than noisy rooms, that complaints about noisy rooms were nearly frequently correlated with surveys indicating an un pass oningness to reaping to the hotel for another stay. Analyzing customer surveys utilise to take weeks, but now takes only days, give thanks to the Clarabridge software.Location managers and corporate executives begin also use findings from text mine to influence finales on building correctments. Wendy’s International select Clarabridge software to analyze nearly 500,000 messages i t collects separately year from its Web-based feedback forum, call centre notes, e-mail messages, receipt-based surveys, and social media. The chain’s customer satisfaction team had previously used spreadsheets and keyword searches to review customer comments; a very slow manual approach.Wendy’s worry was looking for a split tool to renovate analysis, detect emerging issues, and pinpoint troubled areas of the business at the barge in, regional or corporate level. The Clarabridge technology enables Wendy’s to track customer experiences down to the store level within minutes. This timely information helps store, regional and corporate managers spot and address problems related to meal quality, cleanliness, and speed of service. text analytics software caught on first ith regime agencies and larger companies with information systems departments that had the means to mighty use the complicated software, but Clarabridge is now offering a version of its mathem atical product geared toward small businesses. The technology has already caught on with law enforcement, search tool interfaces, and â€Å"listening platforms” like Nielsen Online. Listening platforms are text dig tools that decoct on smirch management, releaseing companies to determine how consumers feel about their shop and take steps to serve to negative sentiment.Structured data analysis win’t be rendered obsolete by text analytics, but companies that are able to use some(prenominal) methods to develop a clearer picture of their customer’s attitudes leave alone have an easier time establishing and building their brand and gleaning insights that will enhance profitability. ENDCase Study Questions: 1. What altercates does the join on in unstructured data present tense for businesses? 2. How does text archeological site ameliorate decision- devising? 3. What kinds of companies are most likely to take in from text archeological site software?Expl ain your answer. 4. In what ways could text mine potentially lead to the erosion of personal information solitude? Explain. 5. Visit a website such as TripAdvisor. com (or high street retail merchant ) detailing products or function that have customer reviews. Pick a product, hotel, or other service with at least(prenominal) several customer reviews and read those reviews, both positive and negative. How could Web content tap help the offering company improve or better market this product or service?What pieces of information should be highlighted| What grass businesses learn from text mining? 1. What challenges does the increase in unstructured data present for businesses? The increase in unstructured data, such as that generated from e-mails, phone conversations, blog postings, online customer surveys and tweets, presents challenges for businesses as it has no distinct form, unlike structured data, which is generated from events such as completing a purchase transaction.The challenge of having unstructured data means that it butt end be difficult to take care a large quantity of data in a short time as thither are so some(prenominal) differing pieces of data rather than just a few structured pieces. The indispensability to use tools such as text mining to interpret unstructured data adds extra challenges specifically those related to finance. The cost of implementing such tools can be great; not only does the technology need purchase; the rate at which technology evolves means there will be cost in the upkeep with regards to updating upstart software.Other costs will include staff training; this will have an initial outlay as well as a continuous financial concussion as new technologies will charter new training. 2. How does text-mining improve decision making? employ text mining improves decision making as it can disassemble a vast quantity of data, boil down the results into specific categories and reveal information that would have been less obvious otherwise. It can give correlations between many different factors more easily than without the text mining analysis.Using these less obvious insights gleaned from the information it is possible for a business to make better aware decisions that may never have been eyeshot of if it was not used. Using text mining tools allows companies to build predictive models to gain insight into both their structured and unstructured data. Using these tools it is possible to recognise patterns and common themes amongst unstructured data, particularly those gained from things such as focus groups and blogs. Identifying these themes allows better decisions as it can tape correlations between data that otherwise would not have been visible.An example of this practice is the use of listening platforms such as Nielson Online which can determine the feelings of consumers and allow a company to better make decisions based upon their customers’ wants and inevitably. 3. What kind s of companies are most likely to eudaemonia from text mining software? Large companies that have information system departments will benefit mostly from text mining software as it will enable them to speed up processes that they are already concentrating on. The text mining software will allow these companies to analyse large amounts of data that would unremarkably take weeks to work through in just days.Other companies will benefit from littler packages of the text mining software, particularly those that comprise ‘listening platforms’. This will allow companies to more easily gauge how they are perceive by their consumers in terms of brand satisfaction and highlight any improvements that need to be rendered. Financial and communications supplier companies can benefit from using text mining software by using it to identify their customers’ needs from their customer feedback to interpret better ways in which to hold up their most profitable clients.Marketi ng companies can benefit from using text mining software to implement predictive modelling to improve marketing and promotions to their target audience and retailers can benefit from text mining software to quickly identify any major issues that occur on store level to better help managers improve their stores. 4. In what ways could text mining potentially lead to the erosion of personal information privacy? Text mining could potentially lead to the erosion of personal information privacy as it gives such an increase insight into the movements and habits of the public.Although text mining can help make improvements in the services being offered, it also gains a large amount of information about an individual. This insight into one’s personal information further adds to the ever growing ‘ unsound brother society’ or ‘ charge society’. With the introduction of things such as increased CCTV monitoring the streets and larger quantities of data constantly being stored by companies there is much speculation that personal privacy is quickly being eradicated. Text mining tools may be another way in which this is observable.An example of this is text mining tools used on holiday purchases; such a simple task can give an insight into the financial stack of an individual from the cost of the holiday to any extras purchased with it, as well as using up habits of that individual and other preferences. One way this information could infringe privacy is if it is then(prenominal) used to market other products specifically to that individual based on their forward purchases. 5. How could Web content mining help the offering company improve or better market this product or service?What pieces of information should be highlighted? Using Tripadvisor. com to read reviews on a hotel in London it has been possible to see the differing opinions of guests staying there. The hotel needs to utilise these reviews in order to better promote their serv ices and to eradicate any problems. Using web content mining could be the most efficient way to do this. The hotel has 736 reviews of which 630 are positive and 106 are negative. It would be inefficient to manually read hrough this amount of text and cross reference specific points that need addressing. Using web mining tools the hotel could easily find which points they can use to market their services, some which out to be the accessibility to amenities, particularly the provide station, and which points they need to improve on, particularly apparent is the attitude of the staff. Not only will web mining easily tholepin up these points it will easily manoeuver trends in the feelings of the guests, which could be missed if the reviews were to be analysed manually.The hotel would also save time and currency by allowing the use of web mining as it eradicates most man great power and human error. Bibliography Books Kenneth C. Laudon, Jane P. Laudon (2012). Management Information Systems: Managing The digital Firm. Harlow: Pearson Education Limited. Online Sources Daily Mail Online (2010) plentiful Brother society is bigger than ever: New technology is ‘undermining privacy by stealth’. Available at: http://www. dailymail. co. uk/ newsworthiness/article-1328445/Big-Brother-society-bigger-New-technology-undermining-privacy-stealth. tml#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) inwardness Research (2007) SPSS Text Mining. Available at: http://www. spss. ch/eupload/File/PDF/Guidebook%20â€%20SPSS%20Text%20Mining. pdf (Accessed 10/04/2012) World Academy of Science, Engineering and engineering science (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)\r\n'