Research opportunities in direct marketing

Introduction irect marketing an area that has received D very little attention from the academic marketing community. The reasons are: is is

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Research Opportunities in Direct Marketing ROBERT C. BIATTBERG ABSTRACT The purpose of this article is to describe why direct marketing offers academics the opportunity to do research on topics of interest to both direct marketers and the academic marketing community. The areas to be covered are: (1 J How Direct Marketing Works, (2) Data Availability, (3) Why Direct Marketing Offers Academics a Potential Area of Research, (4) Areas Needing Research, and (51How to Work with Direct Marketers. ROBERT C. BVIITBERG is the Charles H. Kellstadt Professor of Marketing at the University of Chicago Graduate School of Business. He is also director of the same university’s Center for Research in Marketing. He received his PhD and MS from Carnegie-

Mellon University and his f3A from Northwestern University. He has contributed widely to marketingjournals.

viewed by some as a channel of distqibution, and research in this area is just beginning to become popular among academics; (2) some academics consider direct marketing as a form of advertising which has not been researched because it is less glamorous and less pervasive than general media advertising; and (3) probably most important, the direct marketing community has not supported academic research in those areas as strongly as have general advertising agencies and packaged goods firms. The result is very few articles published in academic journals which study direct marketing issues or utilize direct marketing data.

Push-Button Marketing: How Direct Marketing Works Before proceeding with a discussion of research topics, it is useful to understand how direct marketing works. The description is simplified but covers the basic concepts. The early giants in the industry, such as Bob Stone, developed the basic concepts that are still used by direct marketers. The idea is quite simple; acquire new customers at a cost low enough so that their future purchases make the net present value profitable. Figure 1 shows the system many direct mail marketers use. Direct mailers recognize the importance of capturing data on the costs of acquiring a new customer in terms of the mailing costs, average order, and response rates. They then track future purchases made by these customers and calculate the lifetime value of a customer. This allows direct marketers to develop an economic analysis of these two separate phases of the business. Not all direct marketers know the exact future value of a customer, but most have a reasonable idea of thevalue of the first several repeat purchases. The reason this section is called “PushButton Marketing” is that, once a direct marketer develops the computer systems to track the information described above, most of the marketing activity is in fine-tuning the system. JOURNAL OF DfRECT MARKETING J / 1 WlNER 1987 7

FIGURE 1 ACPUISITION MAILING

Initial Mailing

Average

.I LIFETIME VALUE OF

Repeat Mailings

A CUSTOMER

1

1

Response Repeat

This fine tuning usually consists of testing sources of new customer acquisitions such as lists, media vehicles, offers, copy, and other tactical strategies. The same is true for their existing customers. How can they increase response rates and average orders from their existing customers?This takes the form of mailing frequency, offers, merchandise sold, pricing, and selection of customer file members to mail to or contact using other direct response vehicles (e.g., telemarketing). In contrast to practitioners of most other forms of marketing, direct marketers have far more information about their customers available on computer systems so that it can be analyzed. The availability of data has resulted in direct marketers’ ability to fine-tune their marketing system and to measure the effects of various marketing programs.

Data, Data, Data In direct marketing the abundance of data is good news and bad news. The good news is that 8 J O U R N N OF DIRECT MARKmNG 1/1 WINTER 1987

the data allows direct marketers to evaluate and analyze the marketing tools that are used. This in turn leads to the ability to “know” what works and does not work. The bad news is that the abundance of data causes direct marketers to focus on results, not on why a marketing tool works. The result is that the industry is almost “sub-tactical.” By always concentrating on results, direct marketers rarely develop new approaches to their business because they do not know the customer’s motivations. They understand only their response to the firm’s marketing activities. Thus, the direct marketing industry understands some aspects of consumer behavior better than other marketers but is far less sophisticated in its understanding of the general behavior of its customers. Because of the availability of data, direct marketers have created some very interesting concepts of how customers respond. For example, most direct marketers use “RFM” in analyzing which customers to mail. R stands for recency, F for freqaetzcy, and M for monetary. The more recently a customer buys, the more frequently he or she buys; and, the more he spends (monetary), the higher the response to the next mailing. The direct marketer develops an RFM matrix and measures response rates for each RFM cell. He then uses these results to determine the next mailing. Direct marketers can also develop response curves for different pricing strategies because they can test different prices (offers) and measure the relationship between price (offer) and response rates to estimate the cost of acquiring customers. The industry folklore is extensive because of measurement. The problem is that the folklore, while highlyvaluable, is not understood beyond results. It is felt that certain seasons or months result in higher response rates than others. Why? Some of the reasons given are related to vacations (summer) and holidays (Christmas), but more detailed explanations generally cannot be given. The result is that it becomes d a c u l t for direct marketers to create a new approach to the customer because they do not understand the cause of the phenomenon observed. This is the beginning point for how academics can help direct marketers.

Why Direct Marketing Offers Academics a Potential Area of Research To begin, direct marketing is a natural laboratory for research because: 0 Direct marketers track individual customer histories in detail 0 Direct marketers keep excellent sales and promotional histories 0 No intermediary is involved in the buying process 0 Testing is a way of life The tracking of customer behavior has already been covered but it is important to know the type of data available. Direct marketers commonly keep customer fileswith the following information: (1) the date the customer is first acquired; (2) purchases and dollar expenditures; (3) source of acquisition; ( 4 ) demographics (if available); and (5) mailings and promotional campaigns sent in this type of format. Others summarize the information in various ways such as purchases by product type. Some do not keep extensive promotional histories, though most keep the results of their most recent mailing. More direct marketers are able to keep increasingly detailed histories because the cost of computer data storage is dropping rapidly. Not having intermediaries in the purchase process also means that measurement of results is far easier than for conventional retailers. For example, Procter & Gamble may offer a retailer a special price which is onlypartiallypassed on to the consumer. One needs to track both retailer and consumer prices and responses to both prices to measure the effect of that price feature. A direct marketer does not have the intermediary or sales force to track. Besides data, the most appealing factor to academics is the willingness to test. While consumer products firms design experiments, their ability to measure and execute the tests is suspect. If a consumer product firm wants to test a new mass advertising campaign, it must select x “representative” markets and x control markets. This selection is difficult. It must then run separate ads and measure the results.

The measurement is expensive and extremely dSicult, even using Behavior Scan or Nielsen’s Electronic Research for Insights into Marketing (ERIM), in which scanner panels are available. In contrast, a direct marketer simply selects a list or set of control lists and randomly selects names to mail the new copy or whatever is being mailed. Within weeks, the test is run and the results are available for analysis. The typical cost is in the tens of thousands of dollars, not millions. The difference in the cost of testing means direct marketers are far more willing to evaluate new marketing programs than are their counterparts at large consumer products firms. For academics this difference offers an opportunity to measure new theories and ideas at low cost, using reat consumers and not merely laboratory experiments. Obviously these experiments must have relevance to the direct marketer or they will not be willing to test them. This is the real challenge to the academic marketer.

Areas Needing Research In selecting areas of research, it is important to identify areas relevant to both direct marketers and academics. Thus, not all possible research topics of interest to marketing academics will be covered. Also, as a “quantitative, nonbehavioral” researcher, my own areas of interest and expertise will receive more discussion below.

Consumer Behavior It is incumbent upon me, as a card-carrying marketer, to begin a discussion of research with customer behavior. Direct marketing, in its most general form, will be at the forefront of responding to changing lifestyles. Because direct marketing is “highly convenient” for twoperson working households, analyzing,predicting, and understanding how the cost and time of purchasing influences the choice of channels of distribution will be at the core of most direct marketing strategies. Many experiments are being conducted throughout the United States, Europe, and Japan to see if teletext systems, home banking, and other computerized buying systems will work. In industrial purchasing, JOURNAL OF DIRECT MARKETING 1/1 WINTER 1987 9

computenzea oraenng systems have grown rapidly. The questions researchers must help direct marketers answer are: What are the inhibiting factors limiting the growth of computerized buying systems? When and how will these systems d f i s e through markets? What will the implications be for manufacturers, retailers, direct marketers, and consumer behavior? How does the complexity of learning these systems and the capital investment required by the household (e-g., microcomputers) offset the advantages of using the systems? Another important area of consumer behavior is psychographic and lifestyle research. Many consumer catalog companies are retailers with a Merent delivery system. Since the products being sold are frequently related to lifestyle (Sharper Image, L.L. Bean), it becomes important to take advantage of lifestyles in designing promotional strategies. Specialty catalogs can be designed for different lifestyle segments. The problem facing direct marketers is that data available to select mailings are demographic. Some firms, such as D O M e k y and Claritas, have created “lifestyle” cluster groups using censustract demographics.Segmentsare named “Tobacco Road,” ‘‘Gold Coasters,” etc. The underlying theory is that where you choose to live highly correlates with lifestyle. Thus, they believe that geographic area is a more reliable predictor of purchasing behavior than simple demographics. It is an intriguingbut unvalidated theory. Firmsselling the clustering systemscite customer success stories. However, for an academic the issues become Do differences in geographyrepresentIifestyle differences beyond standard demographics? Does an “Urban Affluent” in Chicago behave the same as an Urban Affluent in Houston? Why? Can more systematic validators of lifestyle systems be offered to the direct marketing community? The third consumer behavior issue relates to 10 J O U R N N OF DIRECT MARKETING 1/1 WINTER 1987

direct marketing folklore. Most direct marketers have been taught that there are direct marketing buyers and non-direct marketing buyers. The issue is: What do direct marketing buyers have in common?Obviously some factors are related to convenience and geographical location. Most direct marketing companies recognize these differences but also know that lists from other direct marketing firms have much better response rates than “cold’ mailings to non-direct marketing buyers. Obviously, there are some factors which prevent non-direct marketing households from buying through direct marketing. Strategically this is an important issue to direct marketers. The universe of non-direct marketing customers is larger than is the universe of direct market customers. If direct marketing firms can develop tactics to “activate” non-direct marketing customersefficiently, they can signiticantly increase their sales.

Advertising Beyond consumer behavior, obviously, direct marketers spend time on questions relating to advertising. The major difference is that, in general, direct marketers can measure the results of tests. Some of the issues raised are longstanding issues which most general agencies face. The critical question is: Can results found in direct marketing translate to general advertising? One of the critical questions relates to alternative copy strategies. More specifically, does “image” advertising have a greater return than “benefit” advertising?Time magazine ran alternative campaigns several years ago. One campaign positioned the magazine as an important news and information source. The other campaign had copy relating to subscription price, free goods, etc. Tracking the image campaign was not easy but it appeared to increase subscription sales above their break-even point. However, the results were preliminary and may not have held up with more careful analysis. By using direct marketing sales data, which is more accurate than standard packaged goods sales data, it may be possible to compare image campaigns to hard benefit campaigns to see relative payouts.

Another topic direct mailers can evaluate is frequency. l k o competing hypotheses are (1) threshold effects, and (2) diminishing returns. Threshold effects mean that the first time one sees an ad, it is not remembered. After reinforcement (several ads seen), the message is understood and then consumers respond. The competing hypothesis is that the first ad seen is the most productive and the subsequent ads are less productive. Direct marketers act as if “diminishing returns” is the superior hypothesis, because they go to great lengths to avoid sending “duplicate”ads or promotions to the same customer. General advertisers believe repetition is critical and therefore “flight” ads (run ads in clusters), particularly firms with smaller budgets. One explanation of these different approaches could be the differences in the medium used. A second explanation is that direct marketers have observed behavior indicating a reduction in response to repetition, but that general advertisers cannot measure these results. A third explanation is that repeat purchasing is prevalent in many products advertised on television, radio or in magazines but not in most direct marketing categories. While explanations can be given, the question is: Is there any way to study this issue using direct marketing as a laboratory? Pricing An area of marketing that will become increas-

ingly understood is pricing. Part of the reason is scanner data from supermarkets. Direct marketers also have the ability and the need to understand pricing decisions. Several issues relate to price points for items and why price points “work.” The “psychological” issue of pricing is not well-documented or well-understoodby marketers or economists. Why does an advertised subscription price of 89U per week for 52 weeks sell more magazines than one of $44.50 per year, when $44.50 per year is a lower total price? How do consumers process information that makes them prefer one price over another?How do they anchor on specific values that determine price points? Direct marketers are always comparing alternative prices and offers that lead to “anomalies” in response. Yet, certain price displays work

better than others. Why? The answers will be advantageous not only to direct marketers but also to other types of retailers in setting price. Statistical Modelling Direct marketing is highly statistical.Because of the vast quantities of data, direct marketers use statistical models to make promotional and tactical decisions. There are four major areas in which statistical models are used: Testing Customer file modelling 0 Outside list segmentation Future value of a customer In each area there are unanswered methodological questions. Testing is the lifeblood of direct marketers. Tests range from colors ofpaper to new product offerings. The testing methods of most direct marketingfirms are very unsophisticated. While being sophisticated is not the purpose of testing, more advanced test designs and analysis systems can lead direct marketers to make better decisions at cover costs. In the area of test analysis several issues arise. In analyzing response rates to a test mailings, the standard procedure used’isto assume that the responses come from a binomial distribution. Thus, the variance of a test cell is simply pq/n where p is the probability of a response, q = 1-pand n is the sample. The problem arises that, when testing multiple variables (e.g., lists), one needs to worry about multiple comparisons. For example, suppose 10 new lists are being compared. The usual method is to see if they are superior to a cut-off value. A statistical test is applied to each list to see if it is significantly above the cutoff. If it is, then it will be included in the next mailing. The lists that are well above the cutoff are mailed with larger quantities. The problem that arises is that in remailing, the best lists often do not do as well. The response rate drops. Thus, the underlying model of a binomial needs to be modified. l k o possible modifications are to recognize the “regression to the mean” effect and to make appropriate adjustments or use some type of shrinkage estimate. Supplying direct marketers with these corrections will improve their JOURNAL OF DIRECT MARKETING 1/1 WINTER 1987 11

planning and reduce their risks. In the area of test design, most direct marketers test all cells rather than using a test design which reduces the number of cells tested and uses the information from other cells to estimate the effect of a given variable. The payoff to direct marketers will be more accurate test results at a lower cost. Customer file modelling is used by most direct marketers. The more sophisticated direct marketers use regression analysis or AID (automaticinteraction detection). The purpose of the models is to predict the probability that an individual will buy from a new offering,given specific historical data about that individual. The modelling problem is to design techniques that can improve upon current methods. So far techniques such as regression are reasonably predictive. Yet many of the assumptions of regression are violated. Are there methods which can be designed for the specific problems direct marketers face that predict better than regression or AID? One of the largest expenditures most direct marketersmake is on promotion to outside lists to improve the response from those lists. Savings attained through the use of a statistical technique to improve outside list response greatly increases the firm’s profitability. Currently, the primary approach is adding demographic data at the zip code level and then measuring which demographic variables improve response rates. The steps used in outside list segmentation are: 0 Determine the number of pieces mailed for each zip code for each mailing. a Measure response rates by zip code. Use some source of data to create demographic data by zip code. 0 Run a regression (or customer multivariate technique) with the dependent variable being response rate for a zip code and the explanatory variables being demographic data for the zip code. Predict response rates for each zip code. Rank the zip codes in order from best to worst. Create deciles (or another set of fractiles) 12 JOURNAL OF DIRECT MARKETING 1/1 WINTER 1987

to “bucket” (or categorize) the zip codes from best to worst. This approach to zip code analysis is commonlyused by many direct mailers. Once deciles (“buckets”) are formed, the mailer then decides which deciles to mail for each outside list. For example, for list x, the top five deciles might be mailed, and for list z the top eight deciles might be mailed, depending upon the response rate for the list. The problems facing direct marketers in using these techniques are: Zip codes are too broadly defined and encompass too many different segments. 0 Some zip codes receive too few mailings and hence require statistical adjustments. The differencesbetween the highest decile and lowest decile is not large (2 times) and, therefore, the savings for a direct market by mailing only the top buckets is less than desired. These limitations offer academics opportunities to develop new approachesand techniques to assist in outside list segmentation. In developing these new methods if is essential to understand how a direct marketer can implement the approaches developed. The final modelling area is the computation of the future value of a customer. Direct marketers are in the enviable position of being able to compute the acquisition cost of a customer and compare it to the anticipatedfuture value of the customer. The result is that in acquisition mailings they can compare the cost per order or cost per customer versus the future (or lifetime) value of a customer. The model used to estimate lifetime values is usually some form of Markov chain or a decision tree. The key is measuring whether a customer moves to the next “transition” or state. The critical question is: What is the probability that a customerwill buy again?The answer depends upon what is the customer’s current state and what is the frequency of mailings received. For example, a customer has bought once from the company and spent $50. If this customer is mailed three times in the next year, what is the probability that he or she will respond? If the customer does respond, then what is the prob-

ability he or she will buy again? The major problem in modelling the future value of the customer is combining the mailing strategy (how many pieces the customer receives) into the transaction matrix or decision tree used to estimate the probability of buying again. Clearly,the greater the mailing frequency, the higher the chances of buying again. In summary, there are many unanswered statistical modelling issues. If academics can bring new techniques and approaches to direct marketing, it should offer practitioners higher response rates and greater efficiencies than they currently have.

New Products and Services New Products or services are the lifeblood of firms. Direct marketing is no exception. Recently the Discovers card was launched by Sears. Every week new catalogs appear, each attempting to gain a foothold in a market segment. While direct marketers are heavy users of testing, they do limited or no research on new product introductions. Consider this in contrast to packaged goods firms who do extensive product research before launching a new product. Direct marketing introductions are usually much less costly than a packaged goods intro-

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FIGURE 2 Direct Marketing ProducVService

Packaged Goods

Working with Direct Marketers

Media Weight Awareness

Kl Price, Distribution

Customer Satisfaction

duction. Cost may range from $500,000 to 510,000,000 (as in the case of Discovers card). Given smaller investments for new product introductions, “simulators” such as Assessor can be developed for direct marketing. These simulators could then estimate response rates, average order, and other key financial statistics used by direct marketers. In many respects, the same models used by packaged goods marketers can be applied to direct marketing. The concepts are similar. Figure 2 shows an example of a packaged goods new product model and a direct marketing model. The major difference between direct marketing and packaged goods is developing low cost “prototypes”which can be used to test the concept. For example, the cost of producing a catalog is greater than its mailing costs. Hence once it is developed, it is less expensive to mail it than to test it. Therefore,some mechanism to develop low-costprototype products/services, which allow customers to go through simulated buying situations, is necessary. If pre-introductory estimates could be developed, it would then be fairly easy to develop financialmodels to estimate sales and profits for several years because of the highly standard RFM systems most companies use. In summary, direct marketing offers many interesting research issues for academics. The critical issue is learning to work with direct marketing firms on these research topics. This is the focus of the next section.

Inquiries

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Acquisition Mailings, Pricing, Merchandising .)

Trial

J Product Ouality, Customer Service Repeat Buying

As is obvious,significant research opportunities are available in direct marketing. The problem academics face is getting started. To help, it is important to understand the “culture” of direct marketing. The culture of direct marketing can be summarized in three words: 0 Pragmatic 0 Short-Run 0 Test-Test-Test If one is aware of these words, then it may be easier to work with direct marketers. JOURNAL OF DIRECT MARKETING 1/1 WINTER 1987 13

Pragmatic Direct marketers are highly pragmatic, almost to a fault. They have very little interest in theories or concepts unless they can be shown to increase sales and profits. Most direct marketers do not understand why their business is successful. They have serious problems when the world changes. It is therefore important for academics to recognize that direct marketers want to understand their current business environment only if they see a payout. For academics, the critical issue is understanding the direct marketer’s problem, helping to solve it, but at the same time using theories or concepts that have academic relevance. Direct marketers do not think in academic concepts. They do have problems to be solved. Thus, the research strategy has to be q u i d p quo. Each side must receive a benefit from the project.

Short-Run The direct marketing industry, in spite of the importance of the future value of a customer, is very short-runand results-oriented.This means that projects which take several years to complete are unlikely to be agreeable to most direct marketers. The orientation of direct marketing also implies that direct marketers must be “managed” differently than a university research project. Deadlines are not as critical in academic research but are veryimportant to direct marketers. It is essential to design projectswith deadlines that can be realistically met. Test-Test-Test The major problem facing academics is that direct marketers believe that, through testing, they understand their business. The result is that academic research may appear to be of little value to a direct marketer. It is essential that the research proposal appears to do more than the direct marketer believes can be learned from trial and error through testing. Testing is a means towards an end in academic research. It is critical that the end justifies the means. The questions academics must constantly ask are: 14 JOURNAL OF DIRECT MARKETING 1/1 W I N T E R 1987

What value am I bringing to the direct marketer’s business? How can 1 communicate this value in concepts and language the direct marketer can understand?

Conclusions Direct marketing offers academics an interesting environment in which to test theories and develop new methodologies because it has extremely good promotional and customer sales histories. It is diflCicultto find as good a marketing environmentwithin the “real world.” Over the next five to ten years, variants of direct marketing are going to grow in importance to both advertisers and marketing firms. Therefore, research into how direct marketing “works” will also become important to the general understanding of marketing. Direct marketing firms are beginning to recognize the importance of academic research. Academics should take advantage of this opportunity and begin developing research projects that can use direct marketing as a natural laboratory and simultaneously contribute to the profitability and efficiency of the firms in the industry..