Applying Bayes Models and Markov Chain in Customer Baskets Analysis
Date Issued
2005
Date
2005
Author(s)
Hsu, Yu-Lin
DOI
zh-TW
Abstract
The enterprises have to develop the valuable customer relationship and keep the advantages in this fast changing market. Digging the profit out of the customer relation is an important matter. Therefore, how to select the correct customer segment in the marketing area is the subject worth studying. But the traditional method takes the population variables as the segmenting foundation which does certainly not to be the effective solution. Thus, the enterprise must improve the efficiency in finding the right customer community of huge customer population, then applying marketing strategy to the different customer groups, and keep analyzing the customer data and changing the marking plans in this intense competing market. Holding the dynamical and heterogenic strategy is also a good way to save enterprise budget and improve efficiency. This thesis use Bays statistics model and Markov Chain to build up the migration matrix. Then I use RFM model to define the purchase statement of the customers and Hierarchical Bayes Methodology to compute postier distribution. This system is to offer a commendation reference for marketing managers.
Subjects
馬可夫鏈
層級貝式模型
市場區隔
Markov Chain.
Hierarchical Bayes Methodology
Segmentation
Type
thesis
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