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A model for supporting Business and Consumers within an Internet Retailing Environment

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Global Networked Organizations Twelfth International Bled Electronic Commerce Conference Bled, Slovenia, June 7 - 9, 1999 Utilizing Information Processing for Enhancing Value: towards a model for supporting Business and Consumers within an Internet Retailing Environment Adam P. Vrechopoulos Brunel University, Information Systems & Computing Uxbridge, Middlessex UB8 3PH, UK Tel/Fax: +30 1 8203160, 8203154 email [email protected] Katherine C. Pramataris Athens University of Economics & Business, Information Systems Department 76 Patision Street, 104 34, Athens, Greece tel/fax: +30 1 8203160, 8203154 email [email protected] Georgios I. Doukidis Athens University of Economics & Business, Information Systems Department 76 Patision Street, 104 34, Athens, Greece tel/fax: +30 1 8203160, 8203154 email [email protected] Adam Vrechopoulos, Katherine Pramatari, Georgios Doukidis Abstract Information processing composes a critical success factor for business effectiveness. Consumer and Sales data comprise the core concept for supporting businesses to apply personalized Marketing/Sales strategies to satisfy consumers and gain competitive advantage. Towards this strategic objective, businesses are facilitated by the huge technology capabilities incorporated in an Electronic Commerce environment, facing an attractive business opportunity. Internet, as an "information intensive" trading channel, offers the appropriate framework for realizing such an objective. This paper1 defines an Internet Consumer Behavior Framework (ICBF) or in other words the information that a virtual retail store must collect (consumer, sales and navigation data). Furthermore, based on this information/data, it introduces a framework for providing Consumer (Consumer Support Model) and Business (Business Support Model) support. Finally, it examines the way that the various virtual store components contribute to this framework, by providing and exploiting the available information. 1. Introduction Web as a virtual hypermedia environment incorporating interactivity with people and computers (Hoffman and Novak, 1996) represents a revolution in marketing. The Electronic Commerce model requires a very different approach to customer acquisition, support, promotion, merchandising and distribution (Aldridge and Borehamwood, 1998). Evidence shows that the Internet and Electronic Commerce with all their new developments will redefine the meaning of the Marketing 4 P's (Stil and Zimmerman, 1996). ...read more.


C. Navigation Data refer to the consumer's behavior through the store, the consumer navigation habits, "click-throughs" etc. While the cost of collecting these data in a traditional store is very high, in a virtual store environment this cost is minimized, based on the capabilities offered by technology. More specifically, a traditional store has to use techniques like video tapping in order to monitor consumer behavior within a store, while a virtual store can monitor this in many different ways, which are more effective, accurate, quick and low in cost. Using these data, we can monitor, analyze, predict and finally guide consumer through a shopping activity. The Navigation data are divided in the following categories: Visits, Entrance, Exit, Response to Promotions, First Visit, Last Visit and Searching. 3.2. Consumer Support Model (CSM) The fact is that Web-Consumers are well informed and very demanding regarding services offered to them and seek for high quality information and treatment. So, once we have defined the Internet Consumer Behavior Framework (ICBF), we need to understand how to use these data to offer better services to Web Consumers, i.e. to support consumers at every stage of their buying process. For this purpose we use the Five Stages Consumer Buying Process Model (Kotler, 1992), as described above, in order to define a Consumer Support Model (CSM) within an electronic shopping environment. This model defines the phases of the shopping activity that need support and how can this be implemented by the processes of the virtual retail store. For example, it defines which methods of advertising should be employed in the need recognition phase for a specific customer, based on his/her personal characteristics and preferences. Figure 2 illustrates the support provided to customers by the electronic retail store environment (Sales and Marketing strategies) during their shopping process. FIGURE 2 The input for the effective operation of the Consumer Support Model (CSM) is the data provided by the Internet Consumer Behavior Framework (ICBF). ...read more.


allocation of advertising displays => income - Monitor Consumer Behavior/navigation to increase effectiveness - Monitor consumer behavior to measure shelf placement effect/to achieve better "shelf" positions - Identify ideal/best place for product advertisement - Need Recognition - Information Search Product Recommendation - Consumer Data - Sales Data (past sales) - Sales Data - Marketing/Sales correlation - Increase Sales - Alternative advertising medium sold to Supplier => increase in come - Value added services to consumer => build store loyalty => competitive advantage - Means of effective promotion => increase sales, awareness of new products and consumer enthusiasm for the brand - Measure advertisement/promotion effectiveness - Need Recognition - Information Search - Purchase Decision Intelligent Searching - Consumer Data - Consumer/Store search criteria - Product Data - Promotion Data - Sales Data - Consumer/Store Search Criteria - Marketing/Sales correlation - Searching Data - Added value services - Analyzing store search criteria => optimizing store marketing - Personalized store marketing based on consumer profile and store search criteria - Category Management/shelf structure - Analyze consumer profile/product category /search criteria to optimize marketing strategy - Possibility for personalized marketing - Identify consumer needs => efficient product introduction/promotion - Optimize marketing mix program (product, price, place, promotion, packaging) - Category segmentation - Information Search - Evaluation of Alternatives Shopping Facilitation - Consumer Data - Navigation Data - Service Usage - Consumer/Service requests - Consumer Basket Data - Sales Data - Introduce/modify effective store services to support consumers - Analyze basket data and plan effective in-store promotions - Category Management based on sales data - Consumer Basket analysis => effective promotion/marketing strategy - After sales support - Category management & Market analysis based on sales data - Information Search - Evaluation of Alternatives - Purchase Decision - Post-Purchase Behavior Consumer Data Gathering - Consumer Questionnaire Content - Observation Parameters - Navigation Data for showing questionnaires - Consumer Data - Navigation Data - Understand store consumer profile, behavior and preferences => support BSM and CSM (eg. Pricing, store promotion, etc. ...read more.

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