How to Use Data Mining to Gain A Competitive Edge in the Market

In the modern world, organizations around the world have to work with enormous amounts of data on a daily basis. Raw data in this form needs a lot of time and effort to sift through, but is critical to maintaining and improving a business.  Delegating such tasks to a data entry outsourcing company that has adequate experience and knowledge data mining, can be regarded as the best solution in this case.

Data mining refers to a sophisticated and organized methodology that aims to identify major information from the strands of data, which is otherwise invisible to the naked eye.  They are entrusted with filtering out arbitrary factors, transforming all sorts of data into valid, understandable information that can be readily analyzed to make critical business decisions.

Data mining thus serves as a filtration process for data leaving out the unwanted information to unlock hidden profitability, reduce client loss to expand the business exponentially. Below are certain ways you can use Data mining to your organization’s advantage.

  1. Sales Prediction: Data mining facilitates sales predications where organizations can easily track the number of customers in a particular market and pick out the prospective ones. Analysis also helps to determine a strategy for planned obsolescence or developing newer product ideas to sell.
  2. Database Marketing: Data mining is a process which automatically enhances and extends the database. The collection of information depends on crucial data received from sales, subscriptions, surveys and questionnaires. This information is analyzed for creating more customer friendly products and turning customers into advocates for the brand.
  3. Guarantees: This is an important aspect of data mining, as it allows the management to foresee the exact amount of customers that can cash in on the guarantee of the product. One way of doing this, is to study the data of past guarantees and sales and profits. This allows the management to effectively frame their guarantee policies to get an edge over rest of the competition.
  4. Affinity Analysis: Affinity analysis refers to the assumptions by which the management can predict future customer behaviours by studying past performance data, like purchases and preferences. It is extremely helpful for evaluating patterns of telephone use in an office, or to identify fraudulent insurance claims.

Data mining has thus become an almost primordial function for a business, which helps marketers better serve their customers on a regular basis. The principle here is simple; the more information the marketer has about customers, the more value they can deliver to them, resulting in a higher return on investment.

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