针对汽车行业营销业务复杂、数据量大的特点,提出一种基于联机分析处理(on line analyticalprocessing,OLAP)的应用方案,给出系统的体系结构,并构建了汽车行业常用营销分析模型,开发出具有跨平台、开放性和自定义功能的汽车行业营销OLA...针对汽车行业营销业务复杂、数据量大的特点,提出一种基于联机分析处理(on line analyticalprocessing,OLAP)的应用方案,给出系统的体系结构,并构建了汽车行业常用营销分析模型,开发出具有跨平台、开放性和自定义功能的汽车行业营销OLAP系统.该系统支持多种主流数据库和常用数据模型,并提供多种数据展现方式,为哈飞汽车销售公司的销售及售后数据分析处理提供了技术支撑,从而为企业深入把握市场动态,制定合理的营销策略提供科学的决策依据.展开更多
In this paper, we designed a customer-centered data warehouse system with five subjects： listing, bidding, transaction, accounts, and customer contact based on the business process of online auction companies. For ea...In this paper, we designed a customer-centered data warehouse system with five subjects： listing, bidding, transaction, accounts, and customer contact based on the business process of online auction companies. For each subject, we analyzed its fact indexes and dimensions. Then take transaction subject as example, analyzed the data warehouse model in detail, and got the multi-dimensional analysis structure of transaction subject. At last, using data mining to do customer segmentation, we divided customers into four types： impulse customer, prudent customer, potential customer, and ordinary customer. By the result of multi-dimensional customer data analysis, online auction companies can do more target marketing and increase customer loyalty.展开更多
文摘针对汽车行业营销业务复杂、数据量大的特点,提出一种基于联机分析处理(on line analyticalprocessing,OLAP)的应用方案,给出系统的体系结构,并构建了汽车行业常用营销分析模型,开发出具有跨平台、开放性和自定义功能的汽车行业营销OLAP系统.该系统支持多种主流数据库和常用数据模型,并提供多种数据展现方式,为哈飞汽车销售公司的销售及售后数据分析处理提供了技术支撑,从而为企业深入把握市场动态,制定合理的营销策略提供科学的决策依据.
基金Supported by the National Natural Science Foundation of China (70471037)211 Project Foundation of Shanghai University (8011040506)
文摘In this paper, we designed a customer-centered data warehouse system with five subjects： listing, bidding, transaction, accounts, and customer contact based on the business process of online auction companies. For each subject, we analyzed its fact indexes and dimensions. Then take transaction subject as example, analyzed the data warehouse model in detail, and got the multi-dimensional analysis structure of transaction subject. At last, using data mining to do customer segmentation, we divided customers into four types： impulse customer, prudent customer, potential customer, and ordinary customer. By the result of multi-dimensional customer data analysis, online auction companies can do more target marketing and increase customer loyalty.
