Data Analysis Applications
Data Mining Is Being Applied in a Variety of Business Sectors
Apr 6, 2009
It has been pointed out that many organizations, due to the strategic nature of their data mining operations, will not even discuss their projects with outsiders. This is understandable due to the important and potential competitive benefit these successful solutions offer organizations. However, there are several well-known applications that are proven performers across the business spectrum.
Customer Profiling and Market Basket Analysis
In customer profiling, for example, characteristics of good customers are identified with the goal of predicting which other customers will become ‘good customers,’ and assist marketing departments to target new prospects. Data mining can find patterns in a customer database that can be applied to a prospect database so that customer acquisition can be appropriately targeted. For example, by identifying good candidates for mail offers or catalogs, direct-mail marketing managers can reduce expenses and increase their sales generation efforts. Targeting specific promotions to existing and potential customers offers similar benefits.
Market basket analysis helps retailers understand which products are purchased together by an individual over time. With data mining, retailers can determine which products to stock in which stores and how to place them within a store. Data mining can also help assess the effectiveness of promotions and coupons.
Fraud Detection and Prediction
Another application of data mining is fraud detection, which is of great benefit to credit card companies, insurance firms, stock exchanges, government agencies and telecommunications firms. The aggregate total for fraud losses in today’s world is enormous, but with data mining these companies can identify potentially fraudulent transactions and contain damage. Financial companies use data mining to determine market and industry characteristics as well as to predict individual company and stock performance.
Another interesting niche application is in the medical field. Data mining can help predict the effectiveness of surgical procedure, diagnostic tests, medication, and other services.
Data Mining: Summing Up
As the previous examples indicate, data mining has numerous applications across a broad spectrum of business sectors, and with a data warehouse installed and operational, the elements for applying data mining techniques are present. However, unlike the “plug-and-play, out-of-the-box” business solutions that are popular, data mining is not a simple application. It involves considerable forethought, planning, research, and testing to ensure a sound, reliable, and beneficial project. It is also important to remember that data mining is complementary to traditional query and analysis tools, data warehousing, and data mart applications. It does not replace these useful and often vital solutions.
Data mining enables organizations to take full advantage of the investment they have made and are currently making in building data stores. By identifying valid, previously unknown information from large databases, decision-makers can tap into the unique opportunities that data mining offers.
One difference between data mining and other business analysis tools is in the approach that each method uses in exploring the data. Many tools support a verification-based approach in which the user hypothesizes about specific data relationships and then uses the tools to verify or refute those presumptions.The effectivenes of this verification-based process is based on the intuition the user has to pose the questions and refine the analysis based on the results of complex queries against a database.
For those organizations which have adopted data mining and integrated the required processes into their corporate environments as a component of CRM strategies, the benefits have proven to be significant, fully justifying their investment of time, money and resources.
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