First Monday

Pricing, Agents, Perceived Value and the Internet by Phillip G. Bradford, Herbert E. Brown, and Paula M. Saunders

Abstract
The Internet has changed the way people buy things. A pointed difference is the use of Internet auctions and bots. But, are these differences actually changing the role and function of price in the firm's marketing program? Are they possibly changing options for pricing, and perhaps even, the very notion of perceived value? Or in fact, does the new set of Internet pricing mechanisms merely require marketers to do what good marketers have always done, and that is to build customer-perceived value and use price to recapture it? The only difference may be that now, we can do it even better because we have better tools.

Contents

Introduction
The More Things Change, the More They Stay the Same
Looking for Low Prices on the Internet Does Not Make a Buyer Price Sensitive
Value-Driven Driven Pricing Is Still Feasible - and Desirable
Managerial Use of Fixed Prices
Value Selling with Bots and Auctions
Bots Can Do Good Work (Good Searches) for Either Side
Summary and Conclusions

 

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Introduction

Internet engendered price transparency and commoditization are putting pressure on the pricing function in all types of online and offline organizations. In fact, according to Priceline.com President Dan Schulman, it is turning things upside down: "For 100 years manufacturers have suggested the retail price. We've turned that upside-down, saying that consumers should recommend the retail price, in exchange for other tradeoffs - such as being brand indifferent among a selected set of brands." But has the Internet actually turned pricing and marketing upside down? Or will it do so in the future? Or is it possible that we are merely witnessing a logical extension of traditional offline pricing? Not according to IBM Information Economies researcher, Jeff Kephart, who predicts that "bots will soon take over the shopping process - managing our grocery lists, filling our pantries, and dickering over the price of every purchase we make. Agents," he says, "will become economic decision makers in their own right."

 

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The More Things Change, the More They Stay the Same

Several research groups [ 1] have done a great deal of quantitative (and theoretical) work on shopbots and salebots. A thesis of their work is that the use of these agents results in unintended and unforeseen negative consequences, including salebot price wars. We agree with the potential, but point to the use of bots in 'Programmed Trading' by many Wall Street firms as evidence that destructive price wars and other major negative consequences may not be the inevitable result of sale- and pricebot usage. Like any market, buyers and sellers in the stock market use attributes other than price in the final determination of a stock's price, even if the agents in use focus principally on price. Thus, we conclude that technology will no doubt evolve bots that use multi-attribute sales and buying approaches and, therefore, it is very unlikely that price will become the primary or only competitive marketing mix variable on the Internet.

The perspective offered in this article is much more managerial and complements rather than replaces the perspective of other researchers. Our perspective is one of total marketing strategy, involving high-tech pricing scenarios that include product branding and offer differentiation, while asserting that buyers look for both value and price. In our view, nothing about pricing, except the tools, has actually changed much at all. Price is still the marketing mix "P" that "extracts the value" out of the perceived value that sellers create through the product itself, and through the promotion and distribution of it. The purpose of price is still to recapture, consistent with growth and profitability objectives, the perceived value of a product or service that exists in the mind of the customer. Margin management is still as important as ever. The concern of customers is still for their money's worth, not for the seller's production cost, cash flow, target return on investment, markup/return on sales, etc. Further, the practice of unwittingly pricing below what buyers are willing to pay (and thus, leaving money on the table) is as much a problem as ever.

Good pricing still means setting the price high in the buyer's value continuum and offering discounts as a reward for taking less value - in other words, engaging in price segmentation. Furthermore, nothing has changed about the fact that price must cover costs and earn the pricer's organization a profit. In sum, the role of marketing strategy is still to create competitive advantages. Further, the role of pricing strategy, on or off the Internet, is still to reap the rewards of those advantages. Given this perspective, we see the Internet extending and expanding the role of nonprice variables on the Internet, not decimating them. This is especially true in the B2C world, where a good deal of Internet-enabled purchasing automation has been in place for some time now, at the same time that attribute-based purchasing is becoming increasingly significant.

 

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Looking for Low Prices on the Internet Does Not Make a Buyer Price Sensitive

Price has always been a confusing variable. It is confusing for both online and offline marketers because everybody wants a lower price, making everyone appear to be a price buyer. But not everybody who wants (or even demands a lower price) is a price buyer. A price buyer is someone willing to exchange perceived offer benefits for a lower price; in sum, someone willing to read restaurant menus from right to left and accept the consequences of choosing the lowest price item. Not many stay in the price buyer category when the results of price buying are in. In fact, one can use the fact that most people aren't price buyers to overcome sales objections. What salesperson hasn't tried "getting that price down" for a price complainer, by removing something of value from the offer, only to find the buyer saying, "No, I want that," thereby indicating a desire for value (as well as an apparent willingness to pay for it).

To think that Internet buyers are all price sensitive (willing to give up value for a lower price) is to assume that all products are perceived as commodities and that all buyers are equal and/or that they all face the same circumstances. How about the price of a good horse? We illustrate with the following example whose first use in modern marketing we have not been able to trace.

One would think a good horse should go for about what a good horse usually goes for. This is not necessarily always true as Shakespeare's literary figure, King Richard III, so amply demonstrated. Dismounted on the battlefield with his life in the balance, he cries out, "A horse! A horse! My kingdom for a horse!" At that moment, he was gladly willing to give up all his wealth and power in exchange for a practical means to survival. In a word, circumstances had made him very price insensitive. Like King Richard, customers (though perhaps less dramatically) will often agree to pay more (and sometimes not as much) because of their circumstances.

 

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Value-Driven Driven Pricing Is Still Feasible - and Desirable

Online and offline value propositions are usually different. As a result, Internet purchasers must always give up something in order to get something on the Internet. They have to give up, for example, the atmospherics and personal assistance found in retail stores as well as immediate use of non-digital products. But they also get something in return; for example, they experience lowered search costs and perhaps improved search outcomes. But whether online or off, most Internet buyers are still value buyers; i.e., they want a product or service that matches their requirements. This suggests that value-driven Internet pricing is a very viable option, especially considering that some exciting, enabling information technology is being phased in. According to Odlyzko [ 2]:

"... pricing on the basis of marginal costs is becoming untenable, and it becomes necessary to price on the basis of customers' willingness to pay. That calls for quality differentiation and price discrimination approaches such as those of airlines. Modern information technology is making such practices possible."

Value-driven pricing requires that sellers accomplish a difficult task. They must 1) find out customers' willingness to pay, and, 2) get those paying higher prices to accept paying different prices for the higher value. Both of these can be accomplished, according Odlyzko, if sellers understand "human preferences for simple, predictable, and fair pricing."

 

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Managerial Use of Fixed Prices

One way to accomplish simple, predictable, and fair pricing, is through the use of fixed pricing, a strategy that is becoming both fashionable and more feasible, due to the Internet. Fixed pricing doesn't mean that prices are all the same. Instead, it means that all buyers falling into a given classification pay the same price as all other members of their class who are buying at the same time. This form of price negotiation is actually going on in situations like this all the time because buyers who get a lower price are asked to give something up for the lower price, e.g., offer low-priced breakfasts at 10 A.M. for seniors and Saturday night stay - over restrictions for inexpensive airline tickets. This approach is widely used in the brick and mortar pricing world.

Firms go to fixed price for two major reasons: 1) in order to wean their organizations from entrenched tendencies to merchandise prices instead of products, and 2) to insure that price decision-making is done at a higher organizational level and informed by a broader perspective than a salesperson might have. To make fixed pricing work, sellers have to get into their buyers' business and use systems that know their needs as well as, or better than, the buyers themselves do. When they do, they will discover that their products are not commodities and that all buyers are not in the same circumstances, thus leading to differential willingness to pay. The ingression of the Internet into marketing has not changed the fact that buyers value things differently and are in different circumstances. And, it hasn't changed their desire for price simplicity and fairness. What it has the potential of doing is to make better buyers out of anyone who enters the market.

 

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Value Selling with Bots and Auctions

The immediate access to global information the Internet provides is making fixed, simple, predictable, and fair pricing more feasible (and possibly more required) than ever. Search engines and well-known Internet auction markets allow large numbers of geographically dissociated participants to focus on the price attribute for well-known items or commodities. But as we see it, the technology that is enabling these Internet auctions, and encouraging commoditization of products, is just as capable of encouraging value selling - and buying - on the Internet.

Such technological protocols as XML allow consistent ways of transmitting and agreeing upon detailed specifications, making it a natural for Internet auctions to grow from commodities and commoditization to value selling of more complex products or services. This goes against the conventional wisdom that high-tech price-setting mechanisms (such as auctions, name-your-own-price programs, and bots) would make it possible to sell every product at its precise market value and would thus lead to a highly "unfixed" approach to pricing. This threat appears real because agents can, indeed, be programmed to deal in complex worlds and deal with a plethora of constraints - including complex price negotiations. However, agents are equally capable of introducing value selling, simplicity and fairness into a pricing scheme.

 

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Bots Can Do Good Work (Good Searches) for Either Side

If value selling and buying depend on the seller meeting the requirements of the buyer and the buyer making tradeoff decisions, the shopbots and salebots can be perfect solutions for arriving at the perfect price. A shopbot (purchasing agent) focuses on satisfying the constraints of the purchaser while a salebot focuses on satisfying the constraints of the seller. The constraints of purchasers are trade-offs of different values for their specific needs, whereas the sellers' constraints are trade-offs among cost coverage, marketing margins and other needs. The Internet is ideal for simplifying complex negotiations for products from computers to cars, making one-of-a-kind configurations for individuals potentially routine.

Salebots and shopbots can search equally well if price is the only issue. But when price is the only issue, the result is losses for everyone. According to Whinston et al. [ 3], "Historical battles show that a policy of competition based only on price is often ineffective because profits for all competition are sacrificed in each round of struggle for market share." Fortunately, as buying bots become better at satisfying the constraints of the purchasers they represent, they will (unless their principals are true price buyers) lessen their focus on price and train it instead on value - a good thing for both buyers and sellers.

Thus, assuming the existence of both a fixed price seller and a willingness to offer discounts in exchange for buyer concessions (the ultimate in price segmentation), price simplicity and fairness can be imagined. Bots doing the selling know the cost of the total product and all of its individual components. Bots serving the buyer can be programmed to know detailed specifications and to engage in true negotiation. True negotiation involves a quid-pro-quo for your negotiating partner's movements (Price concession in the absence of value concession is haggling over price, not over value). The sale and shop bots can be programmed to search out each other and "negotiate" value until the configuration best meeting buyer and seller constraints has been found. Price in these cases, as in brick and mortar transactional settings, is a 'marker' of value. The multiple specific trade-offs in this salebots-shopbot interaction scenario are essentially mini-auctions of the different value propositions found in 'configurators' of the selling bot and its competitors. In fact, assuming that the marketers dig into buyer needs and configure value propositions and offers that match them, this approach can even work for complex digital products with a plethora of configurations and pricing alternatives.

 

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Summary and Conclusions

Although price is frequently the only aspect of an offer that is merchandised, buyers don't buy price, they buy perceived value. Perceived value is certainly not a fixed notion, for it varies over a host of ever-changing attributes. In view of this, any scenario that takes value out of Internet buying, as is often implied whenever digital buying agents are considered, is unlikely to be in our future. Digital buying agents will play a major part in our future, however, because they can take much of the pain out of searching for value. Accordingly, those sellers who articulate and provide value on bot-friendly purchasing sites will be the competitive winners in this scenario. End of article

 

About the Authors

Phillip G. Bradford is a Visiting Associate Professor of Accounting and Information Systems at Rutgers Business School, Rutgers the State University, in Newark and New Brunswick, N.J. He earned his Ph.D. in Computer Science from Indiana University and was a Post-Doctoral Fellow at the Max-Planck-Institute for Informatik in Saarbruecken, Germany. He then worked on Wall Street building financial analytics and in a startup.
E-mail: pgb@andromeda.rutgers.edu

Herbert E. Brown is the Director of the Massey Center for Business Innovation and Development at Robert Morris University in Pittsburgh, Penn. He has taught pricing and a variety of other marketing courses at Miami University, Ohio State University, Southern Illinois University, Rutgers University, and Wright State University. His Ph.D. is from the Ohio State University.
E-mail: hebrown@dayton.net

Paula M. Saunders is Professor of Marketing at Wright State University, where she teaches pricing and other marketing courses. She earned her Ph.D. at Miami University. Her background includes extensive industrial experience in strategic planning and distribution management.
E-mail: paula.saunders@wright.edu

 

Notes

1. J. O. Kephart, J.E. Hanson, and A.R. Greenwald, 2000. "Dynamic Pricing by Software Agents," Computer Networks, volume 32, number 6 (30 May), pp. 731-752.

2. Andrew Odlyzko, 2001. "Internet pricing and the history of communications," Computer Networks, (to be published); see also http://www.research.att.com/~amo/doc/networks.html

3. Andrew B. Whinston, Dale O. Stahl, Soon-Yong Choi, 1997. The Economics of Electronic Commerce. Indianapolis, Ind.: Macmillan Technical Publishing.


Editorial history

Paper received 8 May 2001; accepted 28 May 2001.


Contents Index

Copyright ©2001, First Monday

Pricing, Agents, Perceived Value and the Internet by Phillip G. Bradford, Herbert E. Brown, and Paula M. Saunders
First Monday, volume 6, number 6 (June 2001),
URL: http://firstmonday.org/issues/issue6_6/bradford/index.html