A cost-plus trap: Pricing heuristics and demand identification

Cost plus pricing is a common pricing heuristic. We investigate whether a firm, following cost plus pricing in a simple environment, will eventually have enough information about demand conditions to switch to an optimization-based pricing approach. We find that with unsophisticated statistical approaches this is unlikely, and even with a Bayesian decision theoretic approach there can be what we call a cost plus trap.     

The e-marketing mix: A contribution of the e-tailing wars

In the context of the wars between the upstart Internet retailers and the existing bricks-and-mortar retailers, many e-marketing techniques were invented. This article develops a single unifying and theoretically based taxonomy for e-marketing techniques: the e-marketing mix. Drawing on the paradigms of exchange, relationships, and digital interactions in networks, 11 e-marketing functions are identified that form the elements of the e-marketing mix. Nine of the 11 e-marketing functions are considered basic, while 7 functions moderate the effects of others and are termedoverlapping. The 11 e-marketing functions provide a categorization of the e-marketing techniques. Compared to the conventional marketing mix, the e-marketing mix has more overlapping elements and directly represents personalization, an aspect of segmentation, as a basic function. The existence of multiple elements that are basic and overlapping in the e-marketing mix indicates that integration across elements should be more commonplace compared to the traditional marketing mix. Kirthi Kalyanam is the J. C. Penney Research Professor in the Department of Marketing and the director of E^*Business Initiatives at the Leavey School of Business at Santa Clara University. The Leavey School offers the premier M.B.A. program for working professionals in Silicon Valley. He teaches e-business, channel marketing, and retailing in the EMBA, M.B.A., and undergraduate programs. His research interests are in e-business, retailing, and pricing. His publications have appeared as lead articles inMarketing Science, Journal of Marketing Research, Marketing Letters, Journal of Retailing, andJournal of Interactive Marketing. His research paper, published in theJournal of Marketing Research on GeoDemographic Marketing, was selected as a finalist for the American Marketing Association’s Paul E. Green Award for impact on the practice of marketing. Professor Kalyanam has received the dean’s award for outstanding teaching and/or research contributions. He has also taught at the Graduate School of Business at Stanford University, the Krannert School of Management, and the Department of Consumer Sciences and Retailing at Purdue University and at DePaul University in Chicago. He received his Ph.D. in business administration from the Krannert School of Management, Purdue University. Shelby McIntyre is a professor of marketing at the Leavey School of Business, Santa Clara University. He is also a research associate at the Retail Workbench, a research and education center dedicated to applying advanced information technology to the problems of retailing. He earned a B.S. in engineering (1965), an M.B.A. (1973), and a Ph.D. (1979), all from Stanford University. He has subsequently published more than 50 articles in leading marketing journals, including 5 in theJournal of Marketing Research, 2 inManagement Science, and 11 in theJournal of Retailing. He is on the editorial board of theJournal of Marketing. He has twice received the annual award from theJournal of Retailing for the article “Best Contributing to Theory and Practice in Retail Marketing.” He teaches marketing information systems, marketing research, brand management, and marketing management and was the chair of the Marketing Department at Santa Clara University from 1983 to 1991. His research interests currently focus on decision support systems, retail-related decision models, and e-commerce.     

Cross channel effects of search engine advertising on brick & mortar retail sales: Meta analysis of large scale field experiments on Google.com

We investigate the cross channel effects of search engine advertising on Google.com on sales in brick and mortar retail stores. Obtaining causal and actionable estimates in this context is challenging: Brick and mortar store sales vary widely on a weekly basis; offline media dominate the marketing budget; search advertising and demand are contemporaneously correlated; and estimates have to be credible to overcome agency issues between the online and offline marketing groups. We report on a meta-analysis of a population of 15 independent field experiments, in which 13 well-known U.S. multi-channel retailers spent over $4 Million in incremental search advertising. In test markets category keywords were maintained in positions 1-3 for 76 product categories with no search advertising on these keywords in the control markets. Outcomes measured include sales in the advertised categories, total store sales and Return on Ad Spending. We estimate the average effect of each outcome for this population of experiments using a Hierarchical Bayesian (HB) model. The estimates from the HB model provide causal evidence that increasing search engine advertising on broad keywords on Google.com had a positive effect on sales in brick and mortar stores for the advertised categories for this population of retailers. There also was a positive effect on total store sales. Hence the increase in sales in the advertised categories was incremental to the retailer net of any sales borrowed from non-advertised categories. The total store sales increase was a meaningful improvement compared to the baseline sales growth rates. The average Return on Ad Spend (ROAS) is positive, but does not breakeven on average although several retailers achieved or exceeded break-even based only on brick and mortar sales. We examine the robustness of our findings to alternative assumptions about the data specific to this set of experiments. Our estimates suggest online and offline are linked markets, that media planners should account for the offline effects in the planning and execution of search advertising campaigns, and that these effects should be adjusted by category and retailer. Extensive replication and a unique research protocol ensure that our results are general and credible.     

Strategic Online and Offline Retail Pricing: A Review and Research Agenda

In the increasingly complex retailing environment, more and more retailers operate in more than one channel, such as brick-and-mortar, catalogs, and online. Success in this dynamic environment relies on the strategic management and coordination of both online and offline pricing. This article provides an overview of findings from past research in both offline and online domains and presents an organizing framework, as well as an agenda to spur additional research.     

The perfect message at the perfect moment

Marketers planning promotional campaigns ask questions to boost the odds that the messages will be accepted: Who should receive each message? What should be its content? How should we deliver it? The one question they rarely ask is, when should we deliver it? That's too bad, because in marketing, timing is arguably the most important variable of all. Indeed, there are moments in a customer's relationship with a business when she wants to communicate with that business because something has changed. If the company contacts her with the right message in the right format at the right time, there's a good chance of a warm reception. The question of "when" can be answered by a new computer-based model called "dialogue marketing," which is, to date, the highest rung on an evolutionary ladder that ascends from database marketing to relationship marketing to one-to-one marketing. Its principle advantages over older approaches are that it is completely interactive, exploits many communication channels, and is "relationship aware": that is, it continuously tracks every nuance of the customer's interaction with the business. Thus, dialogue marketing responds to each transition in that relationship at the moment the customer requires attention. Turning a traditional marketing strategy into a dialogue-marketing program is a straightforward matter. Begin by identifying the batch communications you make with customers, then ask yourself what events could trigger those communications to make them more timely. Add a question or call to action to each message and prepare a different treatment or response for each possible answer. Finally, create a series of increasingly urgent calls to action that kick in if the question or call to action goes unanswered by the customer. As dialogue marketing proliferates, it may provide the solid new footing that Madison Avenue seeks.