The measurement of consumers' coupon proneness and the prediction of their redemption behavior is important to the evaiuation of marketers' couponing ...
KAPIL BAWA, SRINI S. SRINIVASAN, and RAJENDRA K. SRIVASTAVA' The measurement of consumers' coupon proneness and the prediction of their redemption behavior is important to the evaiuation of marketers' couponing programs. Although considerable attention has been paid in the couponing literature to the identification of factors that influence coupon usage behavior, relatively little work has been done to develop models that can heip managers predict consumer response to specific coupons and design effective coupon promotions. The authors propose a model of coupon redemption that extends previous models of coupon usage by considering the joint effects of coupon attractiveness and coupon proneness on redemption, and does not require explicit measurement of these variables. Empirical application of the model shows that it correctly predicts redemption intentions for nearly 90% of consumers in a holdout sample and substantially outperforms a logit model that includes traditional measures of coupon proneness, coupon characteristics, and demographics. The proposed model also provides insights into consumer response to coupons that are not provided by the logit model. Overall, the model shows considerable promise as an aid to managers in designing coupon promotions and developing precision targeting strategies.
Coupon Attractiveness and Coupon Proneness: A Framework for Modeling Coupon Redemption Previous researcb on coupon redemption and usage examines it from two perspectives. One stream of researcb is devoted to understanding the factors that motivate consumers to use coupons and identifying the characteristics of consumers wbo are "coupon prone" (e.g.. Bawa and Shoemaker 1987a: Levedabl 1988; Narasimhan 1984; Teel, Williams, and Bearden 1980). Althougb mucb has been learned about coupon usage bebavior. one limitation of studies in this area is that they bave defmed coupon proneness on the basis of observed coupon use without considering the characteristics of the coupons available to eacb consumer. Arguably, a person's coupon usage behavior will depend not only on his or her inherent coupon proneness or desire to use coupons, but also on the attractiveness of tbe coupons encountered. For example, a consumer may be inclined to use coupons but exhibit low coupon usage if he or she fails to find coupons that are sufficiently attractive {i.e., coupons witb bigb face values or for a preferred brand). Thus, failure to include coupon attractiveness as a predictor of coupon usage can lead to an inaccurate assessment of coupon proneness and an inability to predict bow the consumer would respond to coupons with different sets of characteristics.
With 292 billion coupons distributed in 1995 in the United States and approximately 6 hillion coupons redeemed for a total savings of $4 billion (NCH Promotional Services 1996). coupons continue to be among tbe most important promotional vehicles used today. From a managerial perspective, predicting consumers' coupon redemption behavior is essential to tbe evaluation ol' couponing strategies and the identification of target segments for coupon promotions. Althougb considerable attention bas been paid in the couponing literature to the identification of factors tbat influence coupon usage bebavior, relatively little work bas been done to develop models tbat can belp managers predict consumer responses to specific coupons and design effective coupon promotions.
* Kupil Bawa is A.sstKiaie Professor of Murkcling. Faculty of Management. McGill Universily. Srini S. Srinivasan is Assisiani Professor of Marketing. College of Business and Administration. Drcxcl Universily. Rajendra K. Srivastava is Sam Barshop Professor of Marki;ting. University of Texas al Austin. The order of authorship is alphabetical and rellects equal contributions by all authors. The authors thank Mark Aipert, University of Texas at Austin, for supporting this study and the JMR editor and four anonymous JMR reviewers fur their comments and suggestions.
A second stream of researcb focuses on modeling coupon redemption rate as a function of tbe cbaracteristics of the
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Journal oJ Marketing Research Vol. XXXtV (November 1997). 517-525
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JOURNAL OF MARKETING RESEARCH, NOVEMBER 1997
coupon promotion (e.g., Bawa and Shoemaker 1987b; Reibstein and Traver 1982; Ward and Davis 1978). Although these models have shown .several coupon characteristics, such as face value, to be related to the redemption rate, the aggregate-level nature of the analysis has typically precluded consideration of such individual-level characteristics as coupon proneness. This makes it difficult to predict how consumers with different levels of coupon proneness will respond to a specific coupon promotion. The foregoing discussion suggests tbat there is a need for developing models of coupon redemption that can capture the interaction between coupon proneness and coupon attractiveness and help managers predict how a given consumer will respond to a specific coupon. The objective of this study is to propose such a model. The mode! is drawn from tbe Item Response Tbeoretic (IRT) literature and has been used widely in educational measurement and testing. Used in tbe context of coupon promotions, the model enables us to estimate coupon attractiveness and coupon proneness as unobserved variables tbat are inferred from consumers' redemption intentions for a set of coupon stimuli, which obviates the need for explicit measurement of coupon proneness and coupon attractiveness. Predictive testing of the model with our data indicates that it has a predictive accuracy of nearly 90% in holdout samples and significantly outperforms a logit model with traditional measures of coupon proneness, coupon characteristics, and demographics. We seek to contribute to the literature on couponing in two principal ways. First, we extend previous models of coupon usage by considering tbe joint effects of coupon attractiveness and coupon proneness on redemption and provide a methodological framework that does not require explicit measurement of tbese variahles. Second, we provide managers with an effective tt>ol for predicting consumer response to coupons, which can be used for a variety of applications ranging from design of coupon promotions to development of precision targeting strategies. Given the low redemption rates and unprofitable nature of coupons in general, the model appears to bave the potential for making an itiiportant contribution to tbe practice of couponing. PRIOR RESEARCH Many researchers have sought to identify tbe cbaracteristics of coupon-prone or deal-prone consumers (e.g., Bawa and Shoemaker 1987a; Levedabl 1988; Narasimban 1984; Teel, Williams, and Bearden 1980; Webster 1965) and typically bave measured coupon proneness in terms of the consumer's observed (or self-reported) coupon redemption bebavior. Although tbese studies have contributed much tt) our understanding of coupon usage behavior, tbe measures of coupon proneness in tbese studies do not consider tbe cbaracteristics of tbe coupons encountered and tbus bave limited usefulness as predictors of coupon usage behavior. Because different consumers may be exposed to coupons witb different cbaracteristics. a consumer's observed redemption bebavior witb respect to specific coupons does not necessarily retlect his or bcr underlying coupon proneness if coupon attractiveness is not taken into account. Similarly, the observed response to a given coupon among a group of consumers does not necessarily reflect the coupon's inherent attractiveness if the consumers' coupon proneness is not considered.
Other researcbers have examined the impact of coupon characteristics on redemption rates. Reibstein and Traver (1982) found that bigher face value coupons and in-pack coupons are associated witb higher redemption rates. Ward and Davis (1978) also reported higher redemption rates for bigber face value coupons and direct mail coupons. Sboemaker and Tibrewala (1985) and Bawa and Sboemaker (1987b) found that redemption rates increase with face value and that tbe consumers wbo are most likely to redeem coupons are those wbo are most likely to buy the brand in the first place. Neslin and Clarke (1987) und Krishna and Shoemaker (1992) also reached similar conclusions. These studies do not consider coupon proneness as a predictor of redemption bebavior but nevertbeless provide important insigbts into the factors tbat determine coupon attractiveness. Taken togetber, tbese studies suggest tbat coupon attractiveness varies with (1) tbe coupon face value, (2) the type of coupon or delivery vehicle (e.g., free-standing insert |FSI| or direct mail), and (3) wbetber the coupon is for a preferred brand. To tbe extent that tbe coupon has a higher face value, requires less effort to obtain or use, and is for a preferred brand, the coupon is likely to be perceived as more attractive and hence more likely to be redeemed, ceteris par thus. Prior research also shows that coupon redemption bebavior varies witb the product category. Sucb variation may arise because of category characteristics, sucb as average price level, purchase frequency, coupon availability, and brand loyalty (Bawa and Sboemaker 1987a; Webster 1965). Blaltberg and Neslin (1990) note tbat category redemption rates vary widely and thus managers must study coupon proneness at tbe product category level before formulating promotional strategy. We address this issue by estimating our model separately for each category and obtaining category-level measures of coupon proneness. Two product and two service categories are considered in the analysis. Our review of tbe literature suggests tbat tbere is a need for developing more general models of redemption bebavior that include botb coupon proneness and coupon attractiveness as predictors. In the next section we present sucb a model tbat is based on IRT. Tbe model estimates latent or unobserved values of coupon proneness and coupon attractiveness, unlike tbe multi-item measures based on classical measurement tbeory tbat bave been used traditionally. Tbis is advantageous not only because of the difficulty of measuring coupon proneness independently of coupon attractiveness, a.s noted previously, but also because it makes tbe model easier to implement as model estimation requires data only on consumer response to tbe coupon (i.e., redemption intentions or bebavior). For a more comprehensive discussion of tbe relative advantages of IRT and classical measurement tbeory measures, we refer the reader to Hamblcton and Swaminatban (1985). A MODEL OF COUPON REDEMPTION The basic premise of the model is that consumers have an unobserved tendency io use coupons (termed coitpoti proneness). whicb interacts with the intrinsic attractiveness of the coupons encountered to determine their redemption behavior. The response to a given coupon is assumed to vary among consumers because of variations in coupon proneness if coupon attractiveness is constant; similarly, varia-
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Modeling Coupon Redemption lions in response across different coupons for a given consumer are assumed to be a function of coupon attractiveness if coupon proneness is constant. We use the well-known two-parameter model derived from IRT (Bimbaum 1968; Hambleton and Swaminathan 1985) that has been used in the context of attitude scaling in the marketing literature (e.g., Balasubramanian and Kamakura 1989). The model estimates the unobserved coupon proneness and coupon attractiveness from stated redemption intentions.' In this model, the probability of a consumer j redeeming a coupon i is represented as a logistic funetion of the consumer's coupon proneness and coupon characteristics such that -
(I)
Figure 1 COUPON CHARACTERISTIC CURVES
b,)
1 + exp[ai(9j - b,) Coupon Proneness (61
where P,j = probability that consumer j intends to redeem coupon i, 9j = the (unobserved) coupon proneness of con.sumer j , bj = the (unobserved) attractiveness of coupon i, and aj = the (unobserved) ability of coupon i to discriminate among consumers with different levels of coupon proneness. This model places consumers and coupons in the same unobserved continuum. Consumers are represented by 9j, which can be interpreted as coupon proneness. The larger the 6.. the higher the likelihood of redemption for given aj and b,. The coupon "position parameter" b, is inversely related to the unobserved coupon attractiveness of coupon i, because a lower bj yields a higher redemption probability for a given 9j. This is illustrated in Figure I, which shows plots of the function in Equation I lor each of three coupon stimuli. We term these plots cimpon characteristic cun'es, analogous to "item characteristic curves" in the IRT literature. Note that the characteristic curve for the $1 coupon is to the left of (and therefore represents higher attractiveness than) the characteristic curves for the 75- and 4()-cent coupons. Hence, more attractive coupons—those with smaller values of bj—are likely to be redeemed even by consumers with low levels of coupon proneness. But less attractive coupons with high b,'s will be redeemed only by highly couponprone consumers (i.e., consumers with large latent 9j's). On the basis of past research, we expect that coupons with higher face values, those that are easier to use (e.g.. FSI or onpack coupons, which require less effort to use than mail-in coupons), and those for the buyer's favorite brands will be more attractive and thus have lower values of bj. The parameter a,, which represents the ability of coupon i to discriminate among consumers with different levels of coupon proneness, is defined as the tiiaximum slope of the function in Equation 1. The maximum slope of the function occurs at the midpoint of the curve shown in Figure 1, when a consumer's coupon proneness 9j is numerically equal to bj. From Equation 1 it can be observed that this occurs when 'The mcHlet can be applied to eilher intentions dala or actual redempiiun behavior. We use intentions data here because our resources did not permit us to conduct a large-scale Held experiment on coupon usage where Ihe Louptin stimuli eould be maniptilated as needed. We discuss subsequently the limitiitioiis due lo the use of intentions data.
the probability of redemption, Pjj, is .50. When the discrimination (or slope) parameter aj is equal to zero, the coupon characteristic curve is represented by a flat, straight line, irrespective of the coupon proneness of consumers. The higher the value of aj, the steeper the slope of the curve and the better the ability of the coupon to discriminate among consumers who have coupon proneness levels above and below the midpoint of the curve. For a coupon with a high aj value, a small change in Sj in the vicinity of the midpoint (i.e., when 8, is close to bj) will result in a large variation in the likelihood of coupon redemption. Hence, the slope parameter aj can be said to capture the discriminating ability of the coupon. For example, it is easy to see in Figure 1 that though the 40-cent coupon is the least attractive (has the largest value for bj) and is likely to be redeemed only by consumers with high levels of coupon proneness, it has the highest discriminatory power, because small changes in 9j around b^ result in a large change in the probability of redemption from almost zero to one. Similarly, the 75-cent coupon has the least discriminating ability because its characteristic curve is less responsive to changes in coupon proneness. Note that the model only requires data on the dependent variable (redemption intentions or behavior) to estimate coupon proneness and coupon attractiveness. In other words, as long as a manager has household-level data on whether a set of coupons was redeemed, he or she can estimate coupon attractiveness and coupon proneness. If in addition, information on the characteristics of each coupon (e.g.. face value) is available, the relationship between these characteristics and model parameters also can be analyzed, as we demonstrate subsequently.METHODOLOGY
Data for this study were obtained from a survey of grocery shoppers in a Southwestern city. Respondents were contacted at two stores of a major grocery chain in the city. -In some respects the iRT approach to the analysis of coupon preferences may appear similar to a tull-prntlle eonjoint analysis. Both approaches are based on lhe measurement of responses to lull priiflle stimuli and estimale model parameters using decomptisitional methods. In conirust to conjoinl analysis, however. IRT docs nol require stimulus attributes and levels to be known in advance and accounis lor heterogeneity tbrimgh tbe B, parameter.
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JOURNAL OF MARKETING RESEARCH. NOVEMBER 1997
Customers waiting in the checkout line were selected randomly and requested to participate in the survey. They were given u copy of the survey instrument, a prepaid return envelope, and one dollar as a token of appreciation. Of five hundred questionnaires distributed, three hundred forty-five completed questionnaires were received, which represented a response rate of 69%. The final sample consisted of 78% women, had an average age of 39 years, and an average household size of 2.8 people, and the mean number of hours worked per week was 37. Research Instrument Early versions of the questionnaire were pretested on over one hundred students and randomly selected grocery shoppers. In the final version of the questionnaire we measured respondents' redemption intentions with respect to coupons in four categories: two grocery product categories—coffee and detergent—and two service categories—beauty salon/barber shop and oil change for automobiles. For each category, we constructed a set of coupon profiles by systematically varying the type of coupon, the coupon face vaiue, and preference for the couponed brand. Respondents' redemption intention for each coupon was measured as a dichotomous variable by asking whether they would redeem the coupon; each respondent evaluated all coupon profiles. Profiles were constructed on the basis of three types of coupons {FSI, on-pack, and mail-in), three face values (40 cents, 75 cents, and $1 in the case of FSI and on-pack coupons, and 75 cents, $1, and $1.50 in the case of mail-in coupons),-'' and two brands ("most frequently purchased brand" and "occasionally purchased brand"). The most frequently purchased and occasionally purchased brands in the questionnaire referred to the respondent's favorite brand and a brand occasionally purchased by the respondent in the category.* We also obtained other information related to coupon usage. A multi-item explicit measure of coupon proneness was obtained using the .scale developed by Lichtenstein, Netemeyer, and Burton {1990). Mode! Estimation The basic problem in estimating the parameters of the model is to find consistent and sufficient estimators for coupon proneness of consumers (9i) and parameters that define the coupon characteristic curves (aj and b|). An iterative approach is used to estimate and refine the two sets of parameters. Starting values of 6j are obtained through summated -'Free-standing insert coupons were described in ihc i|iie;.tioniiaire as manufacturer coupons printed in the Sundiiy newspaper ihat ciitild he used in any store carrying Ihe briind. Mail-in coupons were described as those ihal customers must mail to the manufaeturer wiih a proof of purchase. Onpack coupons were described as those that appeared on the oulside of the package and eould he used for a subsequent ptirchaso. For mail-in coupons, a $l..^n face value was selected fcir testing instead of the 40-eenl coupon, because pretests showed that y 40-cent lace value for mail-in coupons was nut realistic and was unlikely lo generate any response given mailing cosls. ^For the two service categories, the profiles were constructed differently because lhe eoupiining environment is differeiil for services. For example, on-pack coupons are noi applicable for services. Similarly, inaii-in coupons are not applicable because a discounl on the curreni purchase is typically given by lhe service provider at the time of purchase, if at all. Coupon profiles for services were therefore based tm lhe type of service provider (provider normally patronized and occasionally patroni/ed) and the face value of the eoupon. For the beauty salon service, coupon face value was described in lhe form of a percentage off the regular price.
scores (e.g., proportion of positive responses to the coupons). The distrihution of respondents is then divided into fractiles or groups whose members are likely to have similar levels of coupon proneness, and the proportion of each fractile or group responding to (i.e.. intending to redeem) each coupon is determined for purposes of formulating a log-likelihood function. Parameter estimates of a, and bj are then obtained through maximum likelihood procedures. Given the individual responses to coupons, the coupon proneness level 9j is then reestimated on the basis of the estimates of aj and bj, and the iterative process is continued until it converges. The model was estimated by the maximum likelihood method implemented in MULTILOG (Thissen 1991). Let Ujj 0 = '• •••' ^) denote consumer j's intention to redeem coupon i (i = I, ..., n), with U,j = I if he or she intends to redeem it, and 0 otherwise. Let u be the Nn dimensional vector of responses of the N consumers for the n coupons. The likelihood of observing the response vector u, given the coupon parameter vectors a, b and the individual parameter vector 6, is (2)
where Pjj is the probability that consumer j intends to redeem coupon i, as defmed in Equation I, and Q|j = 1 - Pjj. The log-likelihood is maximized with respect to the parameters a, b, and 6. To eliminate indeterminacy in the model, the 0j parameters in each category are standardized with zero mean and unit standard deviation across the sample. Hambleton and Swaminathan (1985) discuss details of the procedure. RESULTS AND DISCUSSION The redemption intentions data obtained from the survey were u.sed to estimate the modei for the four categories. The coupon parameters b; and a, for coffee and detergent are shown in Table I. For ease of exposition, face values in the table are reported as low, medium, and high. These correspond to face values of 40 cents, 75 cents, and $1, respectively, for FSI and on-pack coupons, and 75 cents, $1, and $ 1.50, respectively, for mail-in coupons. Because bj is inversely related to coupon attractiveness, it should decrease with face value and preference for the couponed brand and increase with effort required to use the coupon. Table I, Part A, confirms these expectations. Coupons with high face values have the lowest bj values, whereas coupons with low face values have the highest b, values. Mail-in coupons, which require more effort to redeem than FSI or on-pack coupons, have substantially higher b, values than FSI and on-pack coupons. Finally, coupons for the favorite brand have lower values of b, than coupons for occasionally purchased brands after controlling for coupon type and face value."^ These results are intuitively ap^An anonymous reviewer poinied out that the impact of the "most frequently purchased brand"" versus "occasionally purchased brand" manipulation may vary across categories wiih the level of brand loyalty in the eategory. We measured brand loyalty for the coffee and detergent categories and found category diflerence.s (o be small {wiih means of 5.1 and 4.9 on a seven-poinl scale lor the two categories, respeclively), whieh implies tbal any differences in lhe impact of the manipulation across these categories may nol be signillcant in the aggregate.
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Modeling Coupon Redemption TABLE 1
PARAMETER ESTIMATES BY COUPON TYPE. CATEGORY, PREFERENCE FOR COUPONED BRAND. AND COUPON FACE VALUE (COFFEE AND DETERGENT CATEGORIES)a Part A: Estimates ofh, Parameters Occasionally Purchased Brand
Favorite Brand High Face Value
LowFace Vatue
Medium
High Face Value
Category
Low Face Value
Medium Face Vatue
I'SI
Detergeni Coffee
-.79 -.69
-1.31 -1.04
-6.20 -2.92
.20 .15
-.57 -.50
-1.45 -1.36
On-Pack
Detergent Coffee
-.71 -.68
-1.09 -.98
-!.49 -1.72
.25 .11
-.39 -.40
-.94 -1,10
Mail-In
Detergent Coffee
2.30 1.45
.9!
.63 .32
2.30 1.52
1.19 .89
.82 .58
.68
Face
Vii/ue
Part B: Estimates of a, Parameters Occasionally Purchased Brand
Favorite Brand Low Face Value
Medium face
Value
High Face Value
H'Kh Face Value
1.59 2.55
2.12 3.92
.54 1.38
1.42 2.13
l,9() 8.70
1.68 1.83
Delergent Coffee
2.22 2,95
2.95 4.81
3.58 2.56
1.64 2.45
2.53 3.89
2,53 2.18
Detergeni Coffee
1.33 2.07
1.66 1.85
1.32 1.35
2.49 4.91
2.47 3.95
i.8O 1.60
Medium Face
Category
Low Face Vatue
FSI
Detergeni Coffee
On-Pack Mail-In
^Low, medium and high face values correspond to 40 cents, 75 cents, and $1. respectively, for FSI and on-pack coupons, and 75 cents. $1. and $1.50 for mail-in coupons.
pealing and suggest that the model and the parameter estimates have face validity. Table I. Part B, shows that low-value eoupons tend to have higher values of a, compared with high-value coupons, which implies that coupons with low face values provide more infonnation ahout the coupon proneness of the consumers they attract. This is understandable hecause redeemers of low-value coupons tend to be highly couponprone consumers and thus a relatively homogeneous group. However, the relationship between face value and the aj parameter does not appear to be uniformly monotonic, because some medium-value coupons have higher values of aj than the corresponding low-value or high-value coupons. These
particular coupons also tend to have bj values ranging from -1.30 to -.40; that is, they tend to attract consumers with Gj values of -1,30 or higher. The implication is that the medium-value coupons used in this study may have been at the threshold of acceptability for such consumers, so they discriminated well between consumers who were above and below this level.^ Table 2 shows the a^ and b; estimates for the beauty salon and oil change services. In general, the fmdings for these categories are similar to those for coffee and detergent. ''We are grateful to an anonymous reviewer for suggesting this explanation.
TABLE 2 PARAMETER ESTIMATES BY CATEGORY PREFERENCE FOR SERVICE PROVIDER. AND COUPON FACE VALUE (OIL CHANGE AND BEAUTY SALON CATEGORIES)a Ser\'ice Provider Occasionally Patronized
Service Provider Normatlx Patronized Lnw
Parameter h.
Category
Face Value
Mi'diiiiii Face Value
High Face Vatue
Low
Face Value
Medium Face Value
High Face
Vahif
Oil Change Beauty Salon
-.47
-.94
-.86 -1.09
-1.85 -2.04
1.46 1.39
.26 .33
-.50 -.44
Oil Change Beauty Salon
1.8S 1.50
3.45 3.14
3.04 3.13
2.98 4.62
7.18 8.48
3.96 7.06
^Low. medium, and high lace values correspond to $2, $4, and $6, respeetively, for the oil change eategory. and 10%. 20%, and 30% discount for the beauty salon eategory.
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JOURNAL OF MARKETING RESEARCH, NOVEMBER 1997
Coupon attractiveness increases for higher face values and the consumer's usual service provider. As before, medium face value coupons appear to discriminate best between varying levels of eoupon proneness. An Interesting aspect of the data here is that the a, values for these services are generally higher than for coffee and detergent. This suggests that response to coupons for these services tends to be more sensitive to small changes in coupon proneness. Alternatively, it may he that coupons for services are more informative because they discriminate between users and nonusers of these services. To gain further insights into the relationship hetween coupon attractiveness and coupon characteristics, ordinary least squares regression models were estimated with the parameters aj and bj as dependent variables and coupon characteristics and category dummies as predictors. The analysis was conducted for the 36 coupon profiles in the coffee and detergent categories (the hcauty salon and oil change categories were not included hecause the coupon profiles were defined differently). Table 3 shows the coefficient estimates for the regression models. As can be observed from the table, h, is related significantly to several coupon characteristics. The b, parameter decreases with coupon face value and preference for the couponed brand and is higher for mail-in coupons relative to FSI and on-pack coupons. Further, there is no significant difference in b, values hetween 40-cent and 75 cent coupons, but coupons with face values of $1 and higher are significantly more attractive. These results are consistent with our previous observations and indicate that coupons with higher face values and those for favorite brands are more attractive, whereas mail-in coupons are less attractive compared with FSI and on-pack coupons. The small positive coefficient for on-pack coupons indicates that they are marginally less attractive than FSI coupons. The insignificant coefficient for category implies that there is no difference between coffee and detergent coupons in b; values.
TABLE 3 COUPON PARAMETERS AS A FUNCTION OF CATEGORY, FACE VALUE, COUPON TYPE, AND PREFERENCE FOR THE COUPONED BRANDS Dependent Variahle Independent Variahle
l>.
a.
Face Value (75 cents)^ Face Value ($1)'^ Face Value ($1.50)^ Calegory-' Favorite Brand*! Mail-In Coupon'^^ On-Pack Coupon ^
-.58 -1.81*** -2.01*** -.04 -.81*** 3.18*** .62*
1.47** .If -.25 -L07** -.52 -.16
.80
.4S
Model ft-'
.38
"Based on parameter estitnate.s for cotTee and detergent categories. •"Dummy variable. '^Ecjuals I tor detergent cDupuns, 0 {ithei wise, tor coupons lor lhe favorite brand. 0 otherwise. tor mail in coup
