Data Mining for Multi-level Marketing Planning in E-commerce

W. Kritboonyalai and V. Avatchanakorn (Thailand)


Data Mining, Kohonen Neural Network, E-Commerce, Multi-Level Marketing


The widespread usage of internet under World Wide Web platform in business practice. E-Commerce, brings in a huge mound of data to organizations. Data mining has become a highly focused issue. This paper aspires to propose data mining algorithm in E-Commerce, with a focus on clustering task by KOHONEN for B-to-C E Commerce. Basically, the algorithm has to be adjusted base on the business application and interested information. Selected variable, Network and Learning Parameter are the major adjustment factors. Distributor Network Planning under Multi-Level Marketing E Commerce is used as the application domain to testify the effectiveness of algorithm. The Mining result is used as business intelligence to understand distributors' expansion propensity in order to use on the first stage of network expansion strategic planning. Furthermore under certain condition the algorithm is easily picked up to use with the new incoming without conscious.

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