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GOR 2001 - contentThis is the http://kiwi.uni-psych.gwdg.de/congress/gor-2001/contrib/contrib/mcElroy-william/mcElroy-william Document. Main Author: MacElroy, William H. Co-Authors: ; Institution: Modalis Research Technologies, Inc., San Francisco Contribution Title: How The Internet Will Kill Three Of The Four Ps Of Marketing (And How Market Research Will Be Subsequently Changed Forever). Authors Email: bill.macelroy@us.modalis.com URLs:
Abstract German (version: 25/06/2002 - 07:47, size: 0) English: Most marketers are familiar with the "Four Ps" of Product, Placement, Promotion and Price (McCarthy, Kotler, et. al.). Indeed many papers have been written about how these fundamental concepts are being transformed by the Internet. This paper, on the other hand, will discuss how advanced technology is beginning to erase the traditional process of the Four Ps and how these changes may affect the marketing research industry. The traditional process may involve a number of steps including: Problem identification, Research objectives and design, data collection, analysis, recommended actions, management consideration and, finally, action in the form of broad policy implementation. The Internet, however, is creating what Thomas Kuhn (1962) would refer to as a "technological period of foment and discontinuity." The process, which used to take months, is now being conducted in milliseconds. The formation of policy is being replaced by instantaneous one-to-one modeling capabilities. All of these trends will lead to a major upheaval in the way the business of marketing research is conducted. This paper will show how advances in Web transactional technology will reduce many of the traditional Four Ps activities to a fraction of their original definition and scope. The major conclusion is that the only "P" that will be enhanced in importance in the new economy will be "placement" (or distribution.) Conclusions will be supported by results from a survey among leading Internet technology decision makers from around the world. Article (version: 25/06/2002 - 07:47, size: 16302)
Introduction McCarthy's Four P classification of marketing mix components has been widely discussed and accepted as a model for understanding the basic marketing processes (McCarthy,1960. Kotler, 1972. et. al.). In more recent years, a number of authors have expressed criticisms of the workability of the model, because of its vagueness with regard to the definition of some components (e.g., "sales promotion"), the lack of mutual exclusivity between components, and in total collective exhaustiveness (van Watershoot and Van den Bulte, 1992). But just as the taxonomical issues in defining marketing processes are difficult to articulate (Hunt and Hunt, 1982) in a static economic system, changes such as those brought about by the Internet may make the effort outdated. Of the many classification systems that have been proposed over the years, only McCarthy's has survived—It has become the "dominant design" or "received view" (van Watershoot and Van den Bulte, 1992, p.84). His model proposed four discrete, controllable functions: Product, Price, Place, and Promotion. Each of these functions is then "managed" to create the best overall application of techniques and technologies for the given market environment. The traditional process of market mix management may involve a number of steps including: problem identification, research objectives and design, data collection, analysis, recommended actions, management consideration and, finally, action in the form of broad policy implementation. The Internet, however, is creating what Thomas Kuhn (1962, p 76) referred to as a “technological period of crisis and discontinuity.” He added that the significance of the crisis is the indication that the “occasion for retooling has arrived.” The retooling in this instance may involve a change in the way marketing mix policies are created and implemented. The primary reason for this change is that the marketing process, which used to take months, is now being conducted in milliseconds online. The formation of marketing mix policy is being replaced by instantaneous one-to-one modeling capabilities. These trends will contribute to a major restructuring of the way the business of marketing research is conducted. This paper will outline these changes and the direction of marketing research in general and as it relates to investigating issues associated with each of the 4Ps. Product The main objective of the product element of the marketing mix strategy is to optimize the product for sale to meet the requirements of the potential customer. Of course, this also includes product updates as necessary, and when feasible, in order to keep up with the changing needs of the consumer. By employing the advantages of technology, "ideal products" can be configured in real time in a one-to-one marketing environment. Configuration offers a marketing organization the potential to finally be armed with the “right” product for each customer. An example of this type of process and technology can be seen at work in companies like Dell Computer, where customers “build” a computer for their specific needs from a set of optional components. Figure 1. Dell Computer’s online product customization www.dell.com As marketing professionals become more comfortable with the power of the Internet as forum for one-to-one marketing, the real time configuration of products may allow marketing research to fully embrace the product element of the marketing mix equation. While a few companies are currently taking advantage of the ability for real time product configuration, it is clearly not widespread. There is encouragement that the power of real time product configuration will be embraced and become more popular. This approach may be particularly useful to organizations that are converting other, more traditional product-related research techniques to the online environment. Survey data used throughout this paper to illustrate trends in online marketing research practices were collected in a year 2000 SIRCUS study of 341 marketing research providers and consumers. This study was jointly sponsored by the A.C. Nielsen Center for Market Research at the University of Wisconsin-Madison, Modalis Research Technologies, and the Institute of International Research. Among research organizations included in the 2000 SIRCUS survey that also conduct product concept testing, nearly one-third had conducted a concept test online. A fair number of these organizations have also used online methodologies in conducting other product testing related research
(see Figure 2). Figure 2. Use of the Internet for product testing related marketing research Price Pricing "policies" are being replaced by “smart intercepts.” In this model, each consumer who is purchasing a product or service online is offered any one of a number of initial price points. By tracking which prices lead to a consummated sale, an optimal price point (or set of price points) is determined. With each iteration, or consumer, the data upon which price is determined grows and the price being offered stabilizes at the price that has proven to increase revenue margins. Currently, 17% of research organizations are using the Internet for general pricing research (SIRCUS, 2000). However, as is the case with product-related marketing research on the Web, few companies in the study had fully embraced the power that the online environment provides in terms of the ability to constantly monitor consumer responses to stimuli and make adjustments accordingly. Price sheets, which are the deliverable outcomes of fixed pricing policies, are being replaced by what some are describing as a "digital bazaar" economy. This refers to situations in which customers with semi-perfect knowledge of multiple sources conduct real time negotiations in order to obtain the best prices. The ability to evaluate vendors (which can be compared, side-by-side on many easily accessible Web sites) is leading to something resembling "perfect price competition," in which the customer has an ability to constantly monitor and adjust purchase behavior. Vendors, on the other hand, can also monitor and adjust pricing strategies, tailoring them to specific individuals based on any number of criteria (e.g., estimated lifetime value of purchases, total past purchases, competitive sites visited, etc.). Figure 3. Dell real-time pricing and promotion example www.dell.com Promotion Traditional promotional strategy is being replaced online by navigation sensing technologies. This new type of tracking technology can identify “lost souls” online in the same way a good retail clerk can tell when to ask a customer if he or she needs help by simply observing whether his or her behavior appears to be seeking something that cannot be found. The key to this technology is identifying navigational patterns and previously observed outcomes to identify—in real time—those individuals who may be likely to become frustrated or confused and thus abandon the purchase. The ability of technology to optimize online promotion is similar to the application of technology used to determine the perfect price, as described in the previous section. Initially, the system can be preloaded with users’ click-stream data in order to determine patterns that lead to undesirable outcomes. Systems can be programmed to send a message offering to help the shopper who needs help if it (the system) detects a consumer who is “lost”—i.e., on a path that has been shown to lead to a no-sale. If the shopper does need assistance, that help can be delivered through either an automated response or with a live customer service representative. (Live customer service reps on the Web may be cost-effective if their presence convinces frustrated customers not to abandon their transactions on the site. See Figure 3.) Figure 4. Lands’ End live personal shopper www.landsend.com Over time the system can become “smarter” by learning which intercepts offering assistance work and which do not. Smart intercepts help create a more conversational environment between the online shopper and the e-tailer and they allow for the same sorts of beneficial consumer feedback that have worked well for retailers over the years. Smart intercepts can also offer suggestions and alternatives that are directly related to the visitors’ requests. By creating short, focused data input forms, the program can generate suggestions based on what others have historically found satisfactory. Once again, the systems can become smarter over time by “learning” what makes something appropriate for particular types of shoppers. This technology has been particularly effective when the shopper is buying for someone else and needs suggestions. The use of smart intercept technology not only has benefits in terms of custom delivery of promotional materials, it can also be used to enhance the manufacturers’ understanding of market behavior. The marketing research efforts that are employed to assess a promotion’s effectiveness, for example, are drastically improved by this technology. The data that would traditionally be collected after a promotion campaign ends, and therefore be subject to respondent and measurement errors associated with self-reports, is collected as behavioral data—including both the system’s “decision” to deliver a particular intercept/promotion and the consumer’s behavior of making a purchase or not. Placement (Distribution) Regardless of the automation that technology allows for in one-to-one marketing with respect to product configuration, pricing, and promotion, goods eventually must be delivered. Placement, then, is the only "P" in McCarthy's mix that remains a significant offline policy issue for the online marketplace. In terms of the traditional marketing mix, distribution therefore becomes a critical consideration and a point of competitive differentiation. In a recent study by UCLA (Jeffrey I. Cole, et. al. 2000. p.43), shipping issues topped the list of concerns superceded only by the concern of privacy of personal data. “Ease of returning or exchanging goods,” “delivery charges,” “product damage in shipping,” and similar issues related to distribution are significant barriers to e-commerce and possible sources of competitive distinctiveness. While technology does not provide the same opportunities with regard to distribution related research as it does for the other areas of the marketing mix, 17% of research organizations that took part in the 2000 SIRCUS survey are using the Internet to conduct distribution channel research. Even though distribution itself remains firmly seated in the offline environment, those who are conducting distribution channel research online are mostly satisfied with their experiences in testing that experience online—mean score of 4.0 (SD = 0.6) on a 5-point scale of satisfaction (where “5” means being “completely satisfied with the use of the Internet for testing this subject.”) (SIRCUS, 2000). The Outlook For Online Marketing Research The shift in the importance of marketing mix elements in the e-commerce environment is also changing the research industry in its wake. Recent survey data indicates that online marketing research can expect to see large-scale growth over the next year. Among research suppliers and consumers who currently utilize online research, 70% report that they expect to increase their reliance on online research in the future. These data also indicate that online marketing research will experience an 11% growth in penetration to those who have never utilized online research over the next year (SIRCUS, 2000). This expected growth is likely due to the consensus among marketing research providers and consumers that online research is both more cost- and time-effective than traditional research. These same survey data do, however, seem to indicate that some debate continues on the overall quality of online research as compared to traditional market research methods (see Figure 5). Figure 5. Importance of various research characteristics and the performance of online research in these same areas (SIRCUS, 2000). Conclusions This brief overview of the impact of e-commerce on traditional marketing mix strategies and procedures is, of course, merely an observation of phenomenon that are continuing to evolve. The eventual impact of online technology on the industry as a whole, and on the marketing research industry specifically, is yet to be seen and is far from being quantifiable as an effect. More research on the subject and an in-depth study of how these changes are affecting businesses is needed. The major conclusions based on the authors’ observations include: · Web transactional technology (in which consumers’ behavior at an online e-tailer is collected and analyzed in real-time) holds the promise to reduce the time spent managing the marketing mix from weeks and months to minutes and seconds. · When used to its fullest potential, this technology unifies the process of marketing research with the process of policy implementation. · As demonstrated in this paper, one-to-one modeling can drastically reduce the need for post hoc research on product development, pricing, and promotional issues. References:
Cole, Jeffrey I., et. al. (2000.) The UCLA Internet report: Surveying the digital future. University of California Los Angeles, Center for Communication Policy. [On-line] Available: http://www.ccp.ucla.edu/pages/internet-report.asp Hunt, Shelby D and Kenneth A. Hunt (1982). Bartels’ metatheory of marketing: a perspective. In the proceedings of the 11th Paul D. Converse Symposium, David M. Garner and Frederick W. Winter, eds. Chicago: The American Marketing Association, 50-58. Kotler, Philip, et. al. (1972). A generic concept of marketing. Journal of Marketing, 36, 46-54. McCarthy, E. Jerome. (1960). Basic marketing: a managerial approach. Homewood, IL: Richard D. Irwin, Inc. Miller, T. & Gupta, A (2001). Studies of information, research, and consulting services (SRICUS): Fall 2000 survey of organizations. University of Wisconsin Madison: A.C. Nielsen Center for Market Research. Kuhn, T. (1962). The structure of scientific revolutions, third edition. Chicago, IL: University of Chicago Press. van Watershoot, W. & Van den Bulte C. (1992). The 4P classification of the marketing mix revisited. Journal of Marketing, 56, 83-93. |
