What Can Businesses Learn from Text Mining

compositors case StudyWhat Can Businesses Learn From Text excavation? Text digging is the baring of patterns and relationships from large sets of ambiguous data the kind of data we generate in e-mails, phone conversations, blog postings, online node surveys, and tweets. The mobile digital platform has amplified the outburst in digital culture, with hundreds of millions of people expecting, schoolbooking, searching, apping ( use applications), buying goods and writing rouseions of e-mails on the go.Consumers at once are more than than just consumers they turn out more ways to collaborate, fate data, and influence the opinions of their friends and peers and the data that they create in doing so progress to probatory value to businesses. Un uniform structured data, which are generated from events much(prenominal) as complementary a corrupt transaction, unstructured data have no trenchant form. Nevertheless, managers believe much(prenominal) data whitethorn offer uni que keennesss into guest behaviour and attitudes that were often more backbreaking to determine socio-economic classs ago.For example, in 2007 JetBlue (the Ameri thunder mug Airline) experienced unprecedented levels of customer discontent in the bestir of a February ice storm that resulted in widesp rake flight butt jointcellations and planes abandon on Kennedy Airport runways. The airline received 15,000 emails per day from customers during the storm and instantaneously afterwards, up from its usual daily volume of 400. The volume was so much large than usual that JetBlue had no simple way to read everything that its customers were saying.Fortunately, the lodge had recently contracted with Attensity, a dealing vendor of text analytics packet, and was adequate to use the software package to analyze all of the e-mail it had received in spite of appearance two days. According to JetBlue research analyst Bryan Jeppsen, Attensity Analyze for Voice of the client (VoC) ena bled JetBlue to rapidly extract customer sentiments, preferences, and requests it couldnt find any new(prenominal) way.This tool uses a proprietary technology to automatically identify facts, opinions, requests, trends, and rough-and-tumble spots from the unstructured text of survey responses, survey notes, e-mail messages, nett forums, blog entries, news articles, and other customer communications. The technology is able to accurately and automatically identify and many an(prenominal) different voices customers use to express their feedback (such as a negative voice, overconfident voice, or conditional voice) which helps organisations pinpoint come upon events and relationships, such as intent to buy, intent to leave, or customer deprivation vents. It rouse reveal detail product and dish issues, reactions to marting and state-supported relations efforts, and even buying signals. Attensitys software integrated with JetBlues other customer analysis tools, such as Satmetri xs acquit Promoter metrics, which classifies customers into groups that are generating positive, negative, or no feedback about the participation. using Attensitys text analytics in tandem with these tools, JetBlue developed a customer bill of rights that addressed the major(ip) issues customers had with the company.Hotel chains like Gaylord Hotels and Choice Hotels are using text mine software to glean insights from thousands of customer satisfaction surveys provided by their guests. Gaylord Hotels is using Clarabridges text analytics solution delivered via the Internet as a hosted software helping 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 companys convention resorts.The Clarabridge software sorts by means of the hotel chains customer surveys and gathers positive and negative comments, organizing them into a renewing of categories to reve al less obvious insights. For example, guests complained about many things more a great deal than noisy rooms, but complaints about noisy rooms were most a great deal correlated with surveys indicating an un resultingness to return to the hotel for another stay. Analyzing customer surveys used to transfer weeks, but promptly takes only days, thanks to the Clarabridge software.Location managers and corporate executives have as well used findings from text exploit to influence finishs on building mendments. Wendys International adopted Clarabridge software to analyze nearly 500,000 messages it collects each year from its Web- base feedback forum, call centre notes, e-mail messages, receipt-based surveys, and social media. The chains customer satisfaction team had previously used spreadsheets and keyword searches to review customer comments a very slow manual approach.Wendys management was looking for a better tool to fastness analysis, detect emerging issues, and pinpoint ex uberant areas of the business at the store, regional or corporate level. The Clarabridge technology enables Wendys 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 government agencies and large companies with information systems departments that had the means to properly use the complicated software, but Clarabridge is now offering a version of its product geared toward small businesses. The technology has already caught on with law enforcement, search tool interfaces, and listening platforms like Nielsen Online. Listening platforms are text mining tools that focus on stake management, allowing companies to determine how consumers feel about their brand and take steps to oppose to negative sentiment.Structured data analysis wont be rendered disused by text anal ytics, but companies that are able to use both(prenominal) methods to develop a clearer picture of their customers attitudes leave have an easier time establishing and building their brand and gleaning insights that give enhance profitability. ENDCase Study Questions 1. What challenges does the addition in unstructured data present for businesses? 2. How does text mining break decision-making? 3. What kinds of companies are most likely to modifyment from text mining software?Explain your answer. 4. In what ways could text mining potentially hold to the wearing away of personal information privacy? Explain. 5. Visit a meshworksite such as TripAdvisor. com (or high street retailer ) detailing products or act that have customer reviews. Pick a product, hotel, or other service with at least several customer reviews and read those reviews, both positive and negative. How could Web content mining help the offering company improve or better market this product or service?What p ieces of information should be highlighted What can 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 translucent form, unlike structured data, which is generated from events such as completing a purchase transaction.The challenge of having unstructured data means that it can be difficult to give a large quantity of data in a short time as there are so many differing pieces of data rather than just a few structured pieces. The postulate to use tools such as text mining to interpret unstructured data adds extra challenges specifically those related to finance. The price of implementing such tools can be great not only does the technology invite purchasing the rate at which technology evolves means there will be costs in the upkeep with regards to updating new software.Other costs will include staff training this will have an initial spending as well as a continuous financial clash as new technologies will require new training. 2. How does text-mining improve decision making? Using text mining improves decision making as it can analyse a vast quantity of data, condense the results into specific categories and reveal information that would have been less obvious otherwise. It can build correlations between many different factors more comfortably than without the text mining analysis.Using these less obvious insights gleaned from the information it is possible for a business to agnise better informed decisions that may never have been thought of if it was not used. Using text mining tools allows companies to build prophetic models to gain insight into both their structured and unstructured data. Using these tools it is possible to recognise patterns and commonality themes amongst unstructured data , particularly those gained from things such as focus groups and blogs. Identifying these themes allows better decisions as it can show 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 needs. 3. What kinds of companies are most likely to benefit from text mining software? Large companies that have information system departments will benefit broadly speaking 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 normally take weeks to work through in just days.Other companies will benefit from smaller packages of the text mining software, particularly those that incorporate listening platforms. This will allow companies to more easily gauge how they are perceived by their consumers in toll of brand satisfaction and highlight any improvements that need to be rendered. fiscal and communications provider 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 retain their most profitable clients.Marketing 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 change magnitude insight into the movements and habits of the public.A lthough text mining can help make improvements in the services being offered, it also gains a large amount of information about an somebody. This insight into ones personal information notwithstanding adds to the ever growing big brother society or command 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 conjecture that personal privacy is quickly being eradicated. Text mining tools may be another way in which this is apparent.An example of this is text mining tools used on holiday purchases such a simple tax can give an insight into the financial circumstances of an individual from the cost of the holiday to any extras purchased with it, as well as spending habits of that individual and other preferences. One way this information could infringe privacy is if it is thus used to market other products specifically to that individual based on their prior 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 gild to better promote their services 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 appear to be the accessibility to amenities, particularly the tube station, and which points they need to improve on, particularly apparent is the attitude of the staff. Not only will web mining easily fla g up these points it will easily show trends in the feelings of the guests, which could be missed if the reviews were to be analysed manually.The hotel would also allay time and money by allowing the use of web mining as it eradicates most man power and human error. Bibliography Books Kenneth C. Laudon, Jane P. Laudon (2012). Management Information Systems Managing The digital Firm. Harlow Pearson Education Limited. 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