DATA MINING Research Paper Example | Topics and Well Written Essays - 1250 words

DATA MINING - Research Paper Example In fact, the early stages of predictive analytics involve product recommendations and behavioral targeting. Another advantage is the possibility of behavior-based advertising. In order to achieve this, the available data is analyzed to predict the areas which interest each customer and the advertisements of that area are presented to the customer. Yet another area where this predictive analytics can be useful is issues like fundraising for nonprofits. In order to do this, often, companies filter the data to identify donation amounts. Similar is the case of insurance pricing and selection. In fact, it is possible to offer individually tailored insurance packages by analyzing the available data. In addition, it is possible for insurance companies to assess insurance risk using the data. Another area where predictive analytics is highly useful is email targeting. In order to do this, companies identify the nature of the emails each customer is likely to respond to and emails are designe d accordingly. However, one of the most important areas of utilizing predictive analytics is retention of customers. It is possible to identify customer defection and attrition through predictive analytics. This will help in reaching customers immediately and effectively stopping their going away. Admittedly, associations discovery helps businesses in a number of different ways. Associations discovery involves indentifying the relationship that exists between the sales of different things or services. In simple terms, association is the discovery of various association relationships in a set of items or services. First of all, this helps organizations identify the related items a customer is likely to buy so that the customer is offered all the related items from the same company. This helps save the time and effort of the customer and ensures that the customer is retained. In addition, it ensures that companies are enabled to sell more by keeping all those items closer which are of ten sold together. Admittedly, various organizations around the world are effectively utilizing this facility. The first example is Wal-Mart. As Khattak, Khan and Lee (2010) point out, Wal-Mart uses basket analysis and clustering in order to smoothen the business transactions; and this helps the company identify the most sold products, identify the customers based on their purchasing capacity, divide the customers based on their arrival time, and identify the items of major trade. Web mining has its own unique advantages either in the form of selling more products or in the form of reduced costs. The web data collected on customers should be categorized and clustered in order to use the same for various purposes ranging from developing marketing strategies, customer relationships, and competitive analysis. It is possible for a company to utilize usage mining or web log data in order to identify a potential customer and reach out to that customer with a tempting offer. The various fo rms of web mining ranging from structure mining, usage mining and content mining offer considerable amount of marketing intelligence. This results in more personalized strategies from the part of companies, more sales, more satisfied customers and higher customer loyalty and retention. Admittedly, data mining algorithms are likely to err seriously in the real production environment. So, it becomes necessary to check their validity before using them in the real working environment. The first way of validating a particular algorithm