Applications of Data Mining in the areas of Marketing Communications Essay Example for Free

Applications of info Mining in the atomic number 18as of Marketing Communications EssayIntroductionIn the learning age, technological advancements have facilitated the collection of heavy(a) amounts of information on various fields to include military intelligence, scientific and business data amongst some(prenominal) others. Computers are able to sort out this data with the aid of database management systems. info can be classified according to predefined criteria.selective information digging involves the extraction of implicit and useful information from databases. Use of relational databases is more helpful in the sense that it allows linkage with the structured query language (SQL) that allows for predicting, comparison and the intention of variations (Che, Han Yu, 1996). In websites, this technology is used by businesses in crawling through web pages and collect information that enables the organization to enhance business, analyze the market trends and utilize the information obtained to their best interest (Web Data Mining, 2013).Applications of Data Mining In the Areas of Marketing Communications, Public Relations and Corporate CommunicationsWith the development of business intelligence, bodily management through the use of data marts and reporting software can obtain data from every region or field of interest in computer readable form in a relatively short time. It uses this data to forecast on future market expectation and consumer trends. Through its models and tools, managers are able to predict future events (Web Data Mining, 2013). It allows the analysis of past records and selling to tailor and narrow coffin nail audience. It also helps in the determination of marketing methods in the end, it increases revenue on sales with fewer campaigns.Data mining can predict consumer behavior, the psychology of the consumer, behavior while shopping, influence of business environment on consumers and consumer motivation depending on the impo rtance of the fuck uping. The products sold to consumers provide data on items how they are positioned. Data mining analyzes use of goods and services patterns, for instance, during festive seasons to find out which products sell more and the association betwixt one product and another. It is common to associate the purchase of bread with butter (Raorane Kulkarni, 2011).Association is utilized in making decisions in cross marketing. Through web crawling information on consumer preferences are collected, their purchase records are used in making inventory decisions and analysis of fraudulent payments (Web Data Mining, 2013).Data mining can be categorized according to the data that is collected, in businesses the identification of high profit and low risk customers is an important occupation for business owners, customers can be segmented with associated characteristics as loyalty and other traits. This is useful in marketing and customer relationship management (Rajagopal, 2011 ). Accuracy is how often models get their predictions right while reliability is a measure of consistency of the model. Validation is done to determine how models perform against real data quality and characteristics of a data mining model must be evaluated before deployment. However, data mining models are considered genuine if they generate the same type of predictions and return the same pattern of findings regardless of the test data.Reliability in data mining is also dependent on the skill, knowledge and the ingenuity of the analyst. Meaningful relations between variables can be extracted from databases in complex formats that are unachievable through manual systems. However, reliability is no longer assured in data mining due to its complex heterogeneous and dynamic nature. It is infallible to incorporate preventive measures to safeguard data validity and integrity (Kavulya, Gandhi, Narasimhan, 2008).ConclusionData mining is an impelling tool in fields as medicine, marketi ng and crime prevention amongst many others. The use of computers has seen this diminish the time required for researches. The tools and models it utilizes are very helpful in business in determining and predicting consumer trends and consumption patterns that were unknown in the past. This seeks to promote revenues with little campaigns. Additionally, the use of web data mining allows businessmen to monitoring device consumer patterns, clusters and associations for inventory purposes. However, this technique may not be completely reliable, this depends on the skills of the user and preventive measures installed checking on reliability. Through legislation and technological interventions these issues can be alleviated.ReferencesKavulya, S., Gandhi, R. Narasimhan, P. (2008). Gumshoe Perspective. IEEE Trans. Knowledge and Data Engineering, 8 (1), pp. 866-883.Rajagopal, S. (2011). node data clustering using data mining technique. International journal of Database Management Systems , 3(4), pp. 1-9.Raorane, A Kulkarni, R.V. (2001). Data mining techniques a source for consumer behavior analysis. Retrieved November 13, 2014 from http//arxiv.org/pdf/1109.1202.pdfWeb data mining. (2013). Predictive analytics and data mining. Retrieved November 13, 2014 from http//www.web-datamining.net/analytics/