商业银行零售客户交叉购买行为预测研究
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摘要
随着现代社会生活步骤的加快,人们不愿花费太多的时间挑选供应商,而更倾向于在同一个供应商那里持续的购买不同的产品或服务,这一现象被大多数学者叫做客户的交叉购买行为。这一行为给企业提供了一个保留老客户、创造更多利润的机会,因此,企业为了促使客户交叉购买行为的发生制定了许多交叉销售策略,而且为了使营销策略更有针对性,对客户交叉购买行为的分析预测成为企业有效实施交叉销售策略的关键。
本研究通过调查问卷确定影响客户交叉购买行为的主要因素,在逐步加入影响因素的同时构建了我国商业因素零售客户未加入影响因素的预测模型及加入影响因素的预测模型,并对某商业银行随机抽取的客户交叉购买行为分别进行实证检验,并且比较了实证结果的预测准确性。
研究结果表明：影响客户交叉购买行为的主要因素有：客户特征、产品特征、交易特征、营销努力、企业特征、获得渠道、情感特征,其中交易特征、客户特征及营销努力对客户交叉购买行为影响最为显著；加入产品特征、交易特征所构建的交叉购买行为预测模型的预测结果要比未加入这些影响因素的预测模型的准确度提高7.5个百分点,说明产品特征和交易特征对客户的交叉购买行为有很大的影响,对这两个方面数据的掌握能更好的帮助银行把握客户的交叉购买行为；随机选择某商业银行的客户分别对两个模型进行实证检验,预测准确度分别为73.71和81.23%,较好的预测该银行客户的交叉购买行为。
本研究将文献研究与调查问卷数据相结合,得出影响客户交叉购买行为较为显著的因素,将这些因素与需求成熟度的理论模型相结合构建适合我国商业银行特征的交叉购买行为预测模型。在验证的过程中,逐步加入影响因素,并在同等条件下比较模型的预测准确性,进一步验证某些因素的重要作用。研究的结果给商业银行合理分配营销资源,针对性开展营销策略提供帮助。
As the pace of life continues to increase, People are fast losing the art of relaxation, they are unwilling to spend so much time to choose product, and tend to purchase more product or service continuing from the same supplier who is they trusted. This phenomenon is called customers' cross-buying by most scholars. It gives a chance to enterprise to maintain old customer and to create more profits, so most of enterprises establish cross-selling strategy to cause the behavior, in order to the marketing strategy more pertinence, it is necessary to grasp customers'cross-buying behavior firstly.
Cross-selling is an important marketing tool for the enterprise promote customer assets, and expand the profit space, so the analysis and prediction of the customer's behavior of the cross-buying is a key for the enterprise to practice the cross-selling strategy. Through the questionnaire this study determined the main factors of customer's behavior of cross-selling, and constructed the cross-buying behavior prediction model of the retail customers in Chinese commercial bank, and tested the behavior of cross-buying of the VIP in a certain commercial bank empirically, and compared with the empirical results which did not join the influencing factors in model, which checking the important role of the influence factors selected to the behavior prediction of cross-buying in turn.
The results show that:The major factors influenced customer's behavior of cross-buying: the customer characteristics, the product characteristic, transaction characteristics, marketing efforts, enterprise characteristics, acquiring channel, emotional characteristics, in which trade characteristics, customer characteristics and marketing efforts are the most significant influence to customer's behavior of cross-buying. The efficiency of prediction improve 7.5 percentage points which is the model of join the product characteristic, transaction characteristics than the model of not participating. It is explained that the product features and transaction characteristics are influenced highly on the customer's behavior of cross-buying, and the data of the two aspects can help Banks understand customer's behavior of cross-buying. This paper choose a diamond level customers of an commercial bank to get empirical test, the average accuracy of them reached separately 73.71% and 81.23%, forecasted the bank customers cross-buying behavior well.
In this paper, the author put literature search combine questionnaires to obtain the significant factors of cross-buying, and Put the factors to combine demand maturity mode to build the forecast of Retail customer's cross-buying behavior from our country commercial bank. In the process of verification, and put them in to the mold step by step, and compare the efficiency of prediction at the equal condition, and get a verification of the factors. The result of research can offer help for commercial bank to allocate marketing resource reasonable and to draw up differentiation cross-selling strategy.
本研究通过调查问卷确定影响客户交叉购买行为的主要因素,在逐步加入影响因素的同时构建了我国商业因素零售客户未加入影响因素的预测模型及加入影响因素的预测模型,并对某商业银行随机抽取的客户交叉购买行为分别进行实证检验,并且比较了实证结果的预测准确性。
研究结果表明：影响客户交叉购买行为的主要因素有：客户特征、产品特征、交易特征、营销努力、企业特征、获得渠道、情感特征,其中交易特征、客户特征及营销努力对客户交叉购买行为影响最为显著；加入产品特征、交易特征所构建的交叉购买行为预测模型的预测结果要比未加入这些影响因素的预测模型的准确度提高7.5个百分点,说明产品特征和交易特征对客户的交叉购买行为有很大的影响,对这两个方面数据的掌握能更好的帮助银行把握客户的交叉购买行为；随机选择某商业银行的客户分别对两个模型进行实证检验,预测准确度分别为73.71和81.23%,较好的预测该银行客户的交叉购买行为。
本研究将文献研究与调查问卷数据相结合,得出影响客户交叉购买行为较为显著的因素,将这些因素与需求成熟度的理论模型相结合构建适合我国商业银行特征的交叉购买行为预测模型。在验证的过程中,逐步加入影响因素,并在同等条件下比较模型的预测准确性,进一步验证某些因素的重要作用。研究的结果给商业银行合理分配营销资源,针对性开展营销策略提供帮助。
As the pace of life continues to increase, People are fast losing the art of relaxation, they are unwilling to spend so much time to choose product, and tend to purchase more product or service continuing from the same supplier who is they trusted. This phenomenon is called customers' cross-buying by most scholars. It gives a chance to enterprise to maintain old customer and to create more profits, so most of enterprises establish cross-selling strategy to cause the behavior, in order to the marketing strategy more pertinence, it is necessary to grasp customers'cross-buying behavior firstly.
Cross-selling is an important marketing tool for the enterprise promote customer assets, and expand the profit space, so the analysis and prediction of the customer's behavior of the cross-buying is a key for the enterprise to practice the cross-selling strategy. Through the questionnaire this study determined the main factors of customer's behavior of cross-selling, and constructed the cross-buying behavior prediction model of the retail customers in Chinese commercial bank, and tested the behavior of cross-buying of the VIP in a certain commercial bank empirically, and compared with the empirical results which did not join the influencing factors in model, which checking the important role of the influence factors selected to the behavior prediction of cross-buying in turn.
The results show that:The major factors influenced customer's behavior of cross-buying: the customer characteristics, the product characteristic, transaction characteristics, marketing efforts, enterprise characteristics, acquiring channel, emotional characteristics, in which trade characteristics, customer characteristics and marketing efforts are the most significant influence to customer's behavior of cross-buying. The efficiency of prediction improve 7.5 percentage points which is the model of join the product characteristic, transaction characteristics than the model of not participating. It is explained that the product features and transaction characteristics are influenced highly on the customer's behavior of cross-buying, and the data of the two aspects can help Banks understand customer's behavior of cross-buying. This paper choose a diamond level customers of an commercial bank to get empirical test, the average accuracy of them reached separately 73.71% and 81.23%, forecasted the bank customers cross-buying behavior well.
In this paper, the author put literature search combine questionnaires to obtain the significant factors of cross-buying, and Put the factors to combine demand maturity mode to build the forecast of Retail customer's cross-buying behavior from our country commercial bank. In the process of verification, and put them in to the mold step by step, and compare the efficiency of prediction at the equal condition, and get a verification of the factors. The result of research can offer help for commercial bank to allocate marketing resource reasonable and to draw up differentiation cross-selling strategy.
引文
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[2]LI Shi-bo, SUN Bao-hong, WILCOX R T. Cross-Selling Sequentially Ordered Products: An Application to Consumer Banking Services[J]. Journal of Marketing Research,2005, 42(2):233-239.
[3]JARRAR Y F, NEELY A. Cross-Selling in the Financial Sector:Customer Profitability is Key[J]. Journal of Targeting, Measurement and Analysis for Marketing,2002,10(3): 282-296.
[4]FREDERICK F R, SASSER W E. Zero Defections:Quality Comes to Services[J]. Harvard Business Review,1990,68(5):105-105.
[5]BLATTBERG R C, GETZ G, THOMAS J S. Customer Equity:Building and Managing Relationships as Valuable Assets[M]. New York:Harvard Business Press,2001.
[6]NASH E L. Database Marketing:The Ultimate Marketing Tool[M]. New York: McGraw-Hill Companies,1993.
[7]DEIGHTON J, PEPPERS D, ROGERS M. Consumer Transaction Databases:Present Status and Prospects[M]. New York:Harvard Business Press,1994.
[8]KAMAKURA S, WAGNER N A. Applying Latent Trait Analysis in the Evaluation of Prospects for Cross-Selling of Financial Services[J]. International Journal of Research in Marketing,1991,8(4):329-349.
[9]杨恒.客户关系驱动因素研究及实证分析——以电信行业为例[D].杭州：浙江大学,2004.
[10]范琳琳.基于CLV和活跃度的客户细分模型及其应用研究[D].西安：西安工业大学,2010.
[11]傅巧灵.北京地区银行业交叉销售的现状、问题及对策[J].新金融,2009(8)：54-58.
[12]邹玉.银行卡的特色营销策略[J].职业时空,2011,7(1)：28-29.
[13]LEHMANN D R. Television Show Preference:Application of a Choice Model [J]. Journal of Marketing Research,1971,8(1):47-55.
[14]KUMAR V, GEORGE M, PANCRAS J. Cross-Buying in Retailing:Drivers and Consequences[J]. Journal of Retailing,2008,84(1):15-27.
[15]VERHOEF P C, FRANSES P H, HOEKSTRA J C. The Impact of Satisfaction and Payment Equity on Cross-Buying:A Dynamic Model for a Multi-Service Provider[J]. Journal of Retailing,2001,77(3):359-378.
[16]陈明亮.客户忠诚决定因素实证研究[J].管理科学学报,2003(5)：72-78.
[17]杨宜苗.国外交叉购买驱动因素模型评析[J].管理观察,2008(23)：244-245.
[18]胡咏雪.顾客交叉购买的驱动因素实证研究[D].上海：上海财经大学,2009.
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