DATABASE MARKETING AND TARGETING
Retailers use data mining to better understand their customers. Data mining allows them to better segment market groups and tailor promotions to effectively drill down and offer customized promotions to different consumers.
How to do Data Mining
The accepted data mining process involves six steps:
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Business understanding
The first step is establishing the goals of the project are and how data mining can help you reach that goal. A plan should be developed at this stage to include timelines, actions, and role assignments.
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Data understanding
Data is collected from all applicable data sources in this step. Data visualization tools are often used in this stage to explore the properties of the data to ensure it will help achieve the business goals.
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Data preparation
Data is then cleansed, and missing data is included to ensure it is ready to be mined. Data processing can take enormous amounts of time depending on the amount of data analyzed and the number of data sources. Therefore, distributed systems are used in modern database management systems (DBMS) to improve the speed of the data mining process rather than burden a single system. They’re also more secure than having all an organization’s data in a single data warehouse. It’s important to include failsafe measures in the data manipulation stage so data is not permanently lost.
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Data Modeling
Mathematical models are then used to find patterns in the data using sophisticated data tools.
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Evaluation
The findings are evaluated and compared to business objectives to determine if they should be deployed across the organization.
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Deployment
In the final stage, the data mining findings are shared across everyday business operations. An enterprise business intelligence platform can be used to provide a single source of the truth for self-service data discovery.
