Principles of Cross-selling Page Design Based on Consumer Online Purchasing Behaviors --Take C to C E-commerce Website as an Example

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1 Principles of Cross-selling Page Design Based on Consumer Online Purchasing Behaviors --Take C to C E-commerce Website as an Example YU Hui 1, ZHENG Hong 2 1. School of Tourism Management, Beijing International Studies University, P.R.China, School of Tourism Management, Beijing International Studies University, P.R.China, [email protected] Abstract: With the advancement of the internet and the improvement of search-and-match based technology, product cross-selling is playing an increasingly prominent role in e-commerce. This paper will study the methods of providing cross-selling product matches via statistical analysis of the consumer base, and via questionnaires given to each customer. It will also propose that web page design in C2C e-commerce has significant influence on consumer online purchasing behavior and likelihood for purchasing a cross-sold product. A good cross-selling page design can increase the rate of successful cross-sales. By constructing the consumer online purchasing behavior model for cross-sold products, a conclusion is made that the cross-selling page design should follow three principles:1) Displaying an appropriate number of product to cross-sell on one page; 2) Close correlation between the product to cross-sell and the initial product of interest that the customer had requested; 3) Presentation for the product to cross-sell must provide detailed quality and utility assessment, and give a sense that the product is tangible. Hopefully, new and innovative cross-selling page designs will be developed, that will bring more cross-selling opportunities and further promote cross-selling to main stream business. Keywords: CRM, E-commerce Website, consumer behavior, online cross-selling, Webpage design 1 Introduction In the 21st century, with the rapid development of the Internet and information technology, there has been increasingly intense competition in the e-commerce industry. This increase in competition has been attributed to the rise in new network marketing techniques. In recent years, a new online sales network method, known as Online Cross-selling emerged from the combination of the cross-selling marketing methods and Internet. Online cross-selling has the advantages of both cross-selling and network transaction. It has the ability to sell more products and services to each individual customer (thereby increasing revenue), as well as provide the consumer with increased satisfaction (thereby increasing customer loyalty). An increasing number of e-commerce companies are becoming aware of the importance and benefit of online cross-selling. This has resulted in wide adoption of the method throughout the industry, especially in C2C e-commerce websites. According to a research findings from a U.S. based study; it had suggested that 62 companies out of the global top 100 largest online retailers implement various forms of cross-selling strategy 3. However, the success of online cross-selling depends on the willingness of the consumer to purchase the suggested product. This factor in turn is largely affected by the design of the web-page containing the suggested products for cross-selling. Principles for such webpage design will be suggested, based on the analysis of Internet consumer behavior. We hope that these design principles will result in increased cross-selling opportunities, and profit. 1 Yu Hui, School of Tourism Management, Beijing International Studies University, P.R.China, Zheng Hong, School of Tourism Management, Beijing International Studies University, P.R.China, Cheng Yan. Q-learning-based dynamic cross-selling approach in e-commerce[j].journal of Management Sciences in China, 2008,11(3):

2 Generally, cross-selling is a marketing method which, firstly, aims to find out the multiple, but related needs of existing customers by using CRM (customer relationship management), analytical techniques and experience. The next step would be to meet these needs by providing these services or selling these products. Based on the above-mentioned analysis of the targeted customer's needs, it makes full use of all available resources to do marketing in order to develop the market and attract customers. Online cross-selling is to implement the cross-selling method online. It has both the advantages of cross-selling and network marketing, turning it into a more competitive marketing method. Online cross-selling can be divided into two parts: one is the online cross-selling between e-commerce websites, and the other one is within an e-commerce website. This paper mainly focuses on the online cross-selling in C2C e-commerce website and find out the principles of cross-selling page design based on the consumer online purchasing behaviors. Foreign scholars study the cross-selling method from different views. Netessine et al from University of Pennsylvania defines online cross-selling as "dynamic cross-selling". She describes "dynamic" as product mix, discount prices and real-time decision-making ability all coming together to make cross-selling "dynamic cross-selling" 4. Harrison and Ansell (2001) predicted the cross-selling opportunities by using survival analysis and they provided an alternative method for predicting the time of implementing the cross-selling. Knott, Hayes and Neslin (2002) established a NPTB (next product to buy) model to improve the effectiveness of cross-selling; Peltier et al (2002) proposed to predict cross-selling based on market segmentation; Doyle (2002) put forward a method of optimizing cross-selling resource allocation in the process of CRM; Cohen (2004) proposed an approach for the banks to optimize the effectiveness of cross-selling and get more up-selling opportunities 5. In terms of factors which affect web-consumer behaviors, foreign scholars study it from different aspects: Terry.L.childers and Christopher. L. Carr (2001) set up a model based on TAM consumer attitudes. They have tested the important role of the convenience factor in predicting the formation of web-consumer attitudes. Ming-Huihuang proposed that novel information plays a positive role in changing consumer behavior, but complicated information will reduce the purchasing aspirations of potential customers. Satya Menon, Barbara Kahn (2002) and Sevgin A. Eroglu et al (2001) focused on the effect of online shopping environments on web-consumer behavior. They emphasize that a good online shopping environment can alter consumer behavior and make them more likely to perform repeated purchasing. C. Ranganathan, Shobha Ganapathy (2002) pointed out that content, design, information and privacy-security are the four main factors that affected online shopping 6. Although domestic scholars have yet to put much study into the topic of online cross-selling, there have been several research attempts into similar fields. Cheng Yan (2007) has proposed a method to decide product mix for cross-selling to set a competitive bundled price 7. He also put forward a knowledge-driven Q-learning algorithm---k-q-learning. This algorithm attempts to solve the problems of dynamic cross-selling. In recent years, several scholars such as Shen Guilin (2009) have studied cross-selling in the insurance and financial industry. Her research centers on the feasibility of cross-selling in China Insurance Group 8 ; Xu Xiaoming and Jin Mingxing have proposed that cross-selling plays an important role in profit growth of the insurance industry, making it one of the strategies for increasing profit; Wu Renqiang suggests that the call center of China insurance industry already has the basic preconditions for implementing cross-selling 9. Other scholars have analyzed the 4 Netessine S, Savain S, Xiao W. Revenue management through dynamic cross selling in e-commence retailing. Operation Research, 2006,54(5): 893~913 5 Cheng Yan. Q-learning-based dynamic cross-selling approach in e-commerce[j].journal of Management Sciences in China, 2008,11(3): 106~113 6 Cao Yifeng, Xue jun. Survey of consumer online purchasing behavior. Modernization, 2006(477):146~147 7 Cheng Yan. Q-learning-based dynamic cross-selling approach in e-commerce[j].journal of Management Sciences in China, 2008,11(3): 106~113 8 Shen Guilin. Feasibility Study on cross-selling of Insurance Group. Insurance Vocational Institute of Technology, 2009(04): 38~41 9 Wu Renqiang. The application of cross-selling to call center in the insurance industry. Shanghai Financial,2009(12):

3 prospects of cross-selling, such as Guo Guoqing, Wu Jianfeng, Qian Minghui. They undertook a study on the outlook of applying cross-selling in the Chinese financial industry; Guo Guoqing analyzed the applications of CRM and cross-selling in the U.S. financial industry. In terms of consumer online purchasing behavior, domestic scholars have done various analyses from several aspects: (1) Factors that impact consumer online-purchasing behavior - Ni Qingran and Zhang genrong (2008) analyzed web-consumer behavior with regard to purchasing motivation and the purchasing process 10. (2) Internet marketing strategy based on web-consumer behavior - Several scholars such as Zhang Shaofeng, Zhang Cuifen, Xiao Lili, Ren Fuoqing, Luo Peng, have put forward internet marketing strategy with regard to consumer online-purchasing behavior and customer psychology. (3)Relationship between customer behavior and the service quality of e-commerce - Du Jintao and Song Tianyu described the relations in details; Chen Linfen and Wang Zhongming (2005) established a service quality model which affects consumer behavior. As can be seen from the researches and studies these scholars did, foreign scholars identified the cross-selling opportunities by various models, but the researches and studies on optimizing the effectiveness of online cross-selling are relatively less than the researches and studies on the identification of cross-selling opportunities; In respect of researches on consumer behavior, the factors such as purchasing convenience, the novelty and complexity of product information as well as online shopping environmental have an influence on web-consumer behavior, but the researches about the effect of webpage design on Consumer online purchasing behavior are rare. The studies of online cross-selling made by Chinese scholars, on one hand, are mainly focused on the applicability and feasibility analysis; on the other hand, the effect of webpage design on consumers online purchasing behavior are rarely studied. 2. Analysis on the influence of webpage design on consumer purchasing behavior Each consumer has multiple demands for different products at the same time.according to Marshall's consumer equilibrium theory; the web-consumers will determine what kinds of product they want to buy and how many products they need according to their income in order to maximize their utilities. Therefore, the webpage of an e-commerce website often recommend more reference products and other related products to consumers when they are making decisions. This kind of cross-selling method is well known in the domestic C2C e-commerce websites, take Taobao for example, if a consumer wants to buy a cell phone on when he determines to buy a phone and click the buy button or the collect button, another page will jump out and suggest that this cell phone is successfully purchased or collected. Meanwhile in the bottom half of the page, there will appear some mobile phone-related products (such as: battery, cell phone accessories, etc.), or inform the consumer of what else other consumers who purchased the same product also purchased, or show some related products that he might like. The main purpose of this cross-selling is to stimulate consumers' demand and raise the awareness of hidden needs into explicit needs, thereby increase purchasing, as shown in figure Qing Niran, Zhang Genrong. Analysis of consume online purchasing behaviors. Economist, 2008 (02):253~254(in Chinese) 58

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5 Figure 1 Cross-selling model of Tao Bao website Source: Online cross-selling can provide more choices to existing customers excavate the potential demand of consumers as well as increase cross-selling opportunities. The results of the general condition of online shopping Survey show that the design of the online cross-selling page has a significant impact on consumers' decisions making process. 2.1 A huge variety of displayed cross-sold products on webpage make it hard for consumers to make purchasing decisions Although 40% of the respondents think that the online cross-sold products help them to make purchasing decision, there are still at least 60% of the respondents think the recommended cross-sold products do not promote purchasing behavior, even have a negative effect on purchasing decision making, as shown in figure 2. One third of the respondents think that the huge range of displayed cross-sold products on webpage makes it hard for consumers to make purchasing decisions. 60

6 Figure 2 Evaluation of consumer on cross-sold products Source: Conclusions of this research 2.2 Insufficient relation between consumers requested product and suggested product to cross-sell. Among all respondents, 16% do not believe that the cross-sold products will add benefit to their targeted purchase. They negatively perceive the website to be 'pushing' goods which would earn them a high-profit margin, products which are too niche, or simply a list of many unrelated products without proper consideration for the consumer's needs. 2.3 Uncertainty about product quality and lack of in-depth information about product properties hinder consumer purchasing. When discussing the advantages and disadvantages of online shopping, 80% of respondents state that due to the characteristics of online shopping, the uncertainty and cognitive delay will put customers into many troubles, such as the low quality problems and fake commodity problems. Furthermore, over 40% of respondents believe that there exist credibility problems with e-commerce websites, and the resulting purchasing risk stops customers from buying products online. 3 Establishing the consumer online purchasing behavior model for cross-sold products According to impact of webpage design on consumer purchasing decisions as well as the characteristics of the internet, we establish consumer online purchasing behavior model for cross-sold products: Where is the consumer i purchases product j at time t; Variety is the range of products on the webpage for cross-selling, including the targeted products and cross-sold products; Relativity is the correlation between the targeted products and the cross-sold products ; Tangibility is the tangibility of cross-sold products, including the perceived nature of the products, such as color, quality and the overall effectiveness of the targeted products and cross-sold products ; Demography is the statistical variables of consumers, including the risk preference of online consumers, purchasing decision path, income and education level; is other unpredicted factors that influence consumer purchasing behavior. (1) 61

7 The results of equation (1) will be used to determine the rate of cross-sold products. The greater the value is, the greater the likelihood for a customer to buy the cross-sold product. 4 The principles of cross-selling page design 4.1 Appropriate type and number of displayed products to cross-sell The webpage which displays details of products has two main functions: 1) first is to present as much product information as they can to consumers, such as the product's features and quality; 2) the second is to display what other competitive products consumers can buy in addition to their requested product. This provides an alternative choice when the customer finds that his requested product cannot meet his needs. To achieve these two goals, a balance between displaying alternative products and products to cross-sell is needed. For example, if we do not appropriately allocate products to cross-sell properly or display a suitable product range, what might happen is that - 1) products to cross-sell will take most of the space which might distract the consumer from the targeted product; 2) the consumer might give up purchasing because there are too many recommended products so that he cannot make a purchasing decision Shopping cart webpages are used for consumers to pay for the products. The aim of cross-selling on the shopping cart webpage is to sell more products to one consumer by offering complementary products and spare parts, etc. However, alternative competitive products should not appear on this webpage. Because it might draw the customer who is about to pay back to the initial stage of decision-making and re-consider those alternative products. In addition, the products to cross-sell on this webpage must be those which can be easily added to the shopping cart. In other words, consumers can make an easy purchasing-decision on those products. In addition, the products to cross-sell should often be those which can stimulate impulse buying. In this respect, spare parts are most suitable for cross-selling, because they are part of targeted product meant to prolong service life, and can be bought at a reasonable price. In comparison with complementary goods, complementary goods are not as suitable for cross-selling because they require the customer to make a new purchasing decision. 4.2 High correlation between customers requested product and products for cross-selling Low correlation between targeted products and products to cross-sell is an important factor which impedes buying cross-selling products. Customers will have no interest in a product which is unrelated to the original requested product because it would not be able to improve the utility of their primary product. Therefore, initial customer targeted product and products to cross-sell must be highly correlated, for example, pen and ink. If a customer has bought a pen, it would be highly likely that he would also buy a bottle of ink if it can be found on the shopping cart webpage. Hence, the potential demand for ink is changed into practical needs immediately and cross-selling is achieved. 4.3 Enhance the tangibility of cross-sold products by creating a virtual experience space One of the shortcomings of online shopping is uncertainty. E-commerce websites can establish a space for virtual experience to reduce the risk and uncertainty of shopping online. For example, when a customer finds a product that he wants, he can enter into the virtual experience space by clicking the link to use this product. In this virtual space, there is a virtual character and a proper number of cross-sold products which are highly correlated with the targeted product. The virtual character can help the customer use this product together with any other cross-sold products available on this webpage. Then the websites will give a utility score for different product mix which assist consumers to decide which product mix can provide maximum utility. This virtual experience space will not only reduce the risk of uncertainty, but also help the website collect information about customer preference, which can help the website devise more effective strategies. 5 Conclusion 62

8 There are many factors which influence consumers to buy cross-sold products. The design of the cross-selling webpage can affect customer purchasing behavior immensely. Therefore, a suitable design of the cross-selling webpage can increase online cross-selling rates and optimize the user experience. Furthermore, if a customer purchases several different products from a single website, it not only increases the profit of the website, but also strengthens the relationship between the web-company and its customers. According to the consumer online purchasing behavior model for cross-sold products, the design of webpage should follow three principles. 1) An appropriate type and number of products to cross-sell should be displayed on the webpage; 2) The initial customer requested product and products to cross-sell should be highly correlated; 3) Maximizing tangibility of a product by creating a virtual experience space which enhances customers' understanding of the product. However, there are two areas which require further research, namely, further data testing, and more comprehensive consumer behavior study. Although the article has constructed a consumer online purchasing behavior model for cross-sold products, this model has not been tested by actual data. Also, due to space limitation, two additional factors - purchasing path and consumer psychology, are not considered. These two perspectives would be studied further. References [1]. Kamakura, W A, Wedel, M, Rosa, F, & Mazzon, J A. Cross-selling through database marketing : a mixed data factor analyzer for data augmentation and prediction. International Journal of Research in Marketing, 2003(20): 45~65. [2]. Kamakura, W A, Ramaswami, S N, & Srivastava, R K. Applying latent analysis in t he evaluation of prospect s for cross-selling of financial services. International Journal of Research in Marketing, 1991(8): 329~349. [3]. Paas, L, Kuijlen, T. Acquisition pattern analyses for recognizing cross-selling opportunities in t he financial services sector. Journal of Targeting, Measurement and Analysis for Marketing, 2001(3): 230 ~240. [4]. Harrison, Tina, and Jake Ansell. Customer retention in the insurance industry Using survival analysis to predict cross-selling opportunities [J]. Journal of Financial Services Marketing, 2002(3): 229~239 [5]. Kamakura, Wagner A, Michel Wedel, Fernando de Rosad, Jose Afonso Mazzon. Cross-selling through database marketing: a mixed data factor analyzer for data augmentation and prediction. International journal of research in marketing. 2003(20): 45~65 [6]. Ngobo, Paul Valentin. Drivers of customers cross-buying intentions. European Journal of Marketing, 2004,(38) (No.9/10) :1129~1157 [7]. Verhoef, Peter C, Philip Hans Franses, and Janny C. Hoekstra. The impact of satisfaction and payment equity on cross-buying: A dynamic model for a multi-service provider.journal of Retailing. 2001(77) :359~378 [8]. Bolton, Ruth N, Katherine N. Lemon, and Peter C. Verhoef. The Theoretical Underpinnings of Customer Asset Management: A Framework and Propositions for Future Research. Journal of the Academy of Marketing Science, 2004(03) :1~20 [9]. Bolton, Ruth N.P K Kannan, Matthew D. Bramlett. Implications of loyalty program membership and service experiences for customer retention and value. Journal of the Academy of Marketing Science, 2000(1):95~108. [10]. Knott, Aaron, Andrew Hayes, Scott A Neslin. Next-product-to-buy models for cross-selling applications. Journal of Interactive Marketing Summerb, 2002(16):59~75. [11]. Netessine S, Savain S, Xiao W. Revenue management through dynamic cross selling in e-commence retailing[j]. Operation Research, 2006,54(5): [12]. Guo Guoqing. New Development in Marketing: From CRM to Cross-selling. Management Review, 2003(02): 40~45(in Chinese) [13]. Wang Tao, Cui Nan. Research on cross-selling in foreign countries. Foreign Economies and Management, 2005(04): 43~49(in Chinese) 63

9 [14]. Peng Zuohe, Zhang Jinglin. Research On conflict and coordination in the channel of cross selling. Shanghai insurance, 2008 (01): 30~31,44(in Chinese) [15]. Li Yingshuang, Li Yuhong, Zhou Guolong. Research on the effectiveness of applied cross-selling based on customer relationships. China Market, 2008(40): 32~33(in Chinese) [16]. Wang Haiyan, Liu Zhijun, Yao Shusheng. Fully utilizing the advantage of cross selling. Market Modernization, 2007(14): 129(in Chinese) [17]. Ren Xiyuan. Analyses on the Affecting Factors During the Process of Cross-selling. Journal of China Women s University, 2007(05): 83~87(in Chinese) [18]. Sun Xiaojia, Mi Hongli. how to conduct cross-selling successfully. Modern business, 2008(21):112(in Chinese) [19]. Sun Qingbo, Meng Wei, Sun Yu. Research on clustering model Based on customer cross-selling. Fujian computer, 2008(04):32~33(in Chinese) [20]. Gao Chongyan, Liu Jiannan. Cross Selling Approach in the Banking Industry. Management Review, 2006(08):28~32(in Chinese) [21]. Dai Wen Sheng, Yuan Wei, Xie Bangchang. What's the next big thing? - determining cross-selling opportunities from research data. China Statistics.2005(08):42~45 (in Chinese) [22]. Gao Jinghui, Wang Junge. The trend of commercial web interface design. Economic Forum,2004(15):104~105(in Chinese) [23]. Li Shumei, Wei Maobin. Application of elements which affect the webpage design. Technology Square,2007(11):161~162(in Chinese) [24]. Tian Min, Gao Liu. Research on the Factor s of Effect the Consumer Sequentially Purchasing and the Choice of the Purchase Path. Future and development,2008(01):26~30 [25]. Tian Liyan, Lu Yanjuan, Li Xin, Chen Yuxi. Applying psychology to online shopping. Modern business,2010(03):98~99(in Chinese) [26]. Chen Xia. What page does the audience want? - Several principles on Network News. News Practices,2010(10):50~52(in Chinese) [27]. Yan Jiaqiong. Home layout design. Computer study,2010(02):51~54(in Chinese) [28]. Cheng Yan. Q-learning-based dynamic cross-selling approach in e-commerce. Journal of Management Sciences in China, 2008,11(3): 106~113(in Chinese) [29]. Cao Yifeng, Xue jun. Survey of consumer online purchasing behavior. Modernization, 2006(477):146~147(in Chinese) [30]. Shen Guilin. Feasibility Study on cross-selling of Insurance Group. Insurance Vocational Institute of Technology, 2009(04): 38~41(in Chinese) [31]. Wu Renqiang. The application of cross-selling to Call center in the insurance industry. Shanghai Financial,2009(12):89~92(in Chinese) [32]. Qing Niran, Zhang Genrong. Analysis on consume online purchasing behaviors. Economist, 2008 (02):253~254(in Chinese) [33]. Chen Linfen, Zhong Mingwang. The relationship between Internet consumer behavior and e-commerce service quality. Consumer Economics, 2005(in Chinese) 64