| Summary: | 碩士 === 淡江大學 === 資訊管理學系碩士在職專班 === 104 === “Bio-economy” will replace the information communication technology (ICT) industry as a core sector of Taiwan’s economy in the future. In the face of the NT$500-billion target of Taiwan’s biotechnology industry, using the kinetic energy of the double engines of electronic information and bio-economy in actual sales to seek the best marketing activities, reasonable resource distribution, and deeper customer relationships to construct national competitiveness for biotechnology industry development can benefit the industry’s sustainable growth. This is one of the most important issues in the industry today.
This study aims at the application of data mining technology to the actual transaction database. With process planning based on CRISP-DM, it is able to build a set of standard operating procedures (SOP) for the analysis and prediction of customer value in the biotech industry. After collecting customer transaction data, first, it takes the RFM (Recency. Frequency, and Monetary) classification model as three indicators for the benchmarks of customer value, dividing customers of medical institutes into four types. Next, through decision tree analysis of data mining tools, it can dig out different customer sales data rules. Finally, expert interviews based on the data mining results can evaluate suitable solutions, concluding marketing support and strategic planning according to different values of customer groups. The study results allow the biotech industry to understand the trading characteristics of medical institutes, and this also contributes to product marketing. As for other Business to Business (B2B) operators, the results serve as effective references for the planning of sales management as well as maintenance of customer relationship.
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