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Data mining - Essay Example

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Data mining Name Professor Course Institution Date QUESTION 1 Benefits of data mining process Predictive analytics to understand the behavior of customers The use of predictive analytics helps in the determination of a predictive score for the elements associated to the organization…
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Download file to see previous pages... The predictive model work measures predictive scores based on the company’s data (Han et al, 2011). The predictive scores produced by the predictive analytics helps to increase the customer responses during the strategized marketing campaigns. The predictive score also helps in increasing the conversions and clicks, which in turn, help in decreasing the associated churns. Associations discovery in products sold to customers The dynamism of the market has led to the influence on the way the business interacts with their customers. The contemporary market bears no guarantee for the loyalty of a customer. This situation has led to the use of data mining in allowing for associations discovery on the goods sold to the customers. Association discovery consist of rules that use an antecedent (if) and a consequent (then) which represent items associated to the obtained customer’s data (Vaidya et al, 2006). The “if” is found in the data while “then” represent an item, which is in integration with the antecedent. The association rules works through analysing the if/then patterns yielded by the customers. The organization then records the patterns to help in identifying the most important relationships. The criteria used involve marking a either pattern as “support” or “confidence”. These criteria are important in studying the behavior of the consumer towards the products of any given organization. The association rules can be applicable in product clustering, catalog design and store layout (Han et al, 2011). Web mining to discover business intelligence from Web customers Web mining is an important application for data mining helping to study the web patterns. This application is important to organizations, which would like to discover then behavior of the web customers. Web mining works through gathering information from the websites using the traditional data mining whereby there is integration of data obtained from the interaction of the potential customers around the web. Web mining presents the business community with the ability to apply intelligent marketing strategies because of the knowledge about the customers. It helps the business to establish a close relationship with the website customers because of the satisfactory analysis on the market. Clustering to find related customer information Clustering in data mining is an important activity for businesses, which helps the latter to find various customers with similar taste to each other. It works through clustering data objects having same attributes concerning the market trend. Through clustering, the firms are able to select high-quality clusters that have low inter-cluster similarity and high intra-cluster similarity. This means that the more similarity between members of a cluster than to a member of another cluster. The process of selecting the clusters in the market is useful in situations where there are many cases with no grouping. The use of clustering algorithms helps in finding the natural groupings. QUESTION 2 Reliability of data mining algorithms The data mining algorithm reliability can be accessed through analysing how they create the data models from a given data. The algorithms are reliable because of the study of specific trends about a given data. The obtained result about the trend helps in identifying the optimal parameters required for the creation of data mining models. The presented optimal parameters helps in deducting appropriate patterns and statistics required for the given ...Download file to see next pagesRead More
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