| Summary: | 碩士 === 僑光科技大學 === 企業管理研究所 === 107 === In recent years, the medical industry is booming. Although the number of clinics is increasing, the performance of pharmaceutical companies is not proportional to the competition among pharmaceutical companies is getting more and more intense. If you neglect the relationship between the customer and the product, will not be able to grasp the needs and trends of customers, therefore, pharmaceutical companies also need strategic planning and change to achieve the goal of locking customers and selling successfully.
In this study, a total of 10,378 transaction data from January 2016 to December 2017 were analyzed by a pharmaceutical company. Through data collection, data preprocessing, data warehousing, data mining, pattern evaluation, and results display, the data mining process was constructed.
First, establish a basic statistical query trend report through online analysis and processing. In order to further study the implicit knowledge between customers, commodities, seasons, institutional categories, and dosage fields, then, through the correlation rules in data mining technology, we can find out the correlation rules between the customer's and product's and each season's correlation rule pattern, organization type, and product and sales volume. And the relationship between the two doses of product A06 4mg, 5mg and the customer, season, sales, the analysis results will be provided to the decision makers of the pharmaceutical factory for reference.
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