A profile of direct marketing television shoppers

E. LJNCOLN JAMES ISABELLA C. 1.CUNNINGHAM

A Profile of Direct Marketing

Television Shoppers

ABSTRACT The researchers used a national mail survey to gather data on the motivational, attitudinal, psychographic, and socioenvironmentalcharacteristics of consumers. Stepwise discriminant analyses of 886 usable responses revealed that significant differences between direct marketing television shoppers and non-shoppers could be attributed to ten variables. The two groups differed in their need for affiliation, need for convenience, and attitude toward risk. Other significant discriminamrs were: sex, race, age, the absence of children in the home, late night television viewing, and social isolation. The latter two variables helped provide support for two hitherto untested industry notions - the "theory of sales resistance," and the "isolation hypothesis." Identifiable differences were used to help the researchers develop a profile of direct marketing television shoppers.

E. LINCOLN JAMES is an assistant professor in the Department of Advertising at Michigan State University. and received his PhD from the University of Texas a t Austin. ISABELLA C. M. CUNNINGHAM is the EmeSt Sharp Centennial Professor in Communication at the University of Texas at Austin. Her PhD is from Michigan State. This study was supported by a grant from the University of Cincinnati Direct Marketing Policy Center.

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INTRODUCTION

There is very little about the behavior of inhome shoppers’to guide us. . . . data about direct response television shoppers are virtually nonexistent . . . we really do not know how people respond to response outside the gross data provided by sales figures, which are mostly unobtainable (38:130) irect response television is one of the fastest-growing areas of retailing. Industry reports show that purchases of goods and services sold this way rose from $212,000,000 to $339,000,000 between 1979 and 1982, an overall increase of about 60 percent (Stone 1984). While no current data are available, a conservative estimate based on past trends suggests that shoppers spent more than $660,000,000 in purchases via television during 1986. There has also been an increase in the number and quality of retailers engaging in this strategy. Whereas direct response television was once considered a specialty to be used only by record clubs, book publishers, and kitchen gadget merchants, the strategy is now being embraced by growing numbers of Fortune 500 corporations (26). Products ranging from jumper cables and fitness kits to sophisticated video home computers are now offered for direct sale to the consumer. A survey of the literature on advertising and consumer behavior, however, reveals a surprising dearth of empirical research that focuses on direct response television shoppers. The discussions of these shoppers in a recent spate of books have been mainly speculative in nature (1, 4, 15, 17, 27, 38). Sporadic investigations of in-home shopping behavior have focused mainly on mail order and catalog shopping (7, 29, 32), telemarketing (2, 6), and even direct selling (28). A few studies have also demonstrated an interest in comparative strategy analysis (13,31). This study seeks answers to three major questions. First, “What are the characteristics of direct response television shoppers?’; second, “Are there any significant differences between direct response television shoppers and non-shoppers?’; and third, “If there are significant differences, are they identifiable and explainable?”

D

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Study Objectives Practitioners agree that there are essentially three types of direct response television strategies. These are direct support, lead generation, and direct marketing. The focus of this study will be on consumers who respond to the latter strategy. As its name implies, direct support aims at reinforcing and building greater response to the promotional efforts for a particular product or service in the same medium or other media. Most direct support commercials are aired as ten-second station breaks. They do not carry the tag lines, telephone numbers, or mailing addresses characteristic of the pure direct response mode. The other form of direct response, lead generation, does not offer products or services for immediate sale. The immediate objective is to initiate either a written or telephone inquiry from the viewer. The initiation of a simple undemanding and uncommitted action serves as a kind of “foot-inthe-door” technique, whereby a marketer can build a personal contact list for his own sales force and establish a potential user database. The third form of direct response television is direct marketing. Direct marketing television (DMTV) is defined for the purposes of this study as an interactive system of marketing that makes use of the medium of television to effect a measurable consumer response in the form of a sale. Home shopping shows and videotex format are not included in this discussion. A typical direct marketing commercial delivers a sales pitch, makes additional premium offers, and invites the consumer to place an qrder through a toll-free number or to order by mail. There are two basic kinds of direct marketing commercials, the “one-shot’’ and the “continuity” spot. The “one-shot’’ promotes the one-time sale of a single product or service. The continuity type commercial promotes the sale of a single product or service through a series of installments. Book and magazine subscriptions and any form of negative option selling are generally of the continuity type. This study attempts to develop a profile of DMTV shoppers by comparing their motivational, attitudinal, and socio-environmental attributes with those of non-shoppers. Such an integrative profile can provide insights into the characteristics which direct response TV shoppers have in common, and thus facilitate the segmentation and TV scheduling strategies of practitioners. The selection of these attributes was based on a modified interdisciplinary paradigm VOLUME I NUMBER 4 AUTUMN 1987 13

presented by Myers (25) for relating consumer characteristics to consumer behavior (Figure 1). The specific variables measured in this study were selected based on a review of the literature on shopping behavior in general and in-home shopping behavior in particular. The following figure summarizes the framework used for this purpose. I

1

FIGURE 1 CONCEPTUAL PARADIGM Personal

Wonpersonal

MEANING SYSTEM attitudes

Internal

NEED SYSTEM motives psychographics

OBJECT SYSTEM shopping behavior

External

SOCID-ENVIRONMENT social categories social relations

Myers (25) proposed that internaVexterna1 and personal/nonpersonal dimensions are the principal axes which can differentiate actor space and lead to the identification of meaningful differences in contextual influences on consumer behavior. While each space is itself a system with its own structure and function, it serves as part of a.total system of influence. It appears, therefore, that one should measure all of these dimensions in order to achieve a meaningful segmentation profile. In consumer behavior research the traditional approach is to assess the relationships between the object system, containing the dependent variable, and the other dimensions. The following section describes the independent variables measured by the research.

The Independent Variables Four different kinds of independent variables were measured by the research. These variables can be classified as shopping motivations, attitudes, pschographics and social environment. The dependent variable is DMTV shopping behavior which falls within the external/nonpersonal object system according to the Myers (25) formulation. Shopping Motivations

As early as 1923, Copeland proposed a product typology of convenience-shopping-specialty goods 14 JOURNAL OF DIRECT MARKETING

( 5 ) , but it was Martineau (20,21) who, three decades laser, drawing upon the early work of motivational psychologist Kurt Lewin (19), verbalized the presence of social-psychological motives for shopping. Researchers such as Cattel(31, Maslow (223, McGuire (23), and Murray (24), have attempted to identify and categorize human motives. However, it was Tauber (36) who inferred a number of specific shopping motivations based on the satisfactions that individuals derived from a particular action. His hypothesized shopping motivations were supported in a recent study by Westbrook and Black (37). Motivationscharacterize that part of an individual’s cognitive structure that drives him toward the attainment of satisfactions for perceived or unrecognized needs. This study examines five motivations. These are: (1) power and authority motivation, which is associated with satisfactions derived from acquiring momentary dominance over the activities of others in the marketplace; (2) filiation motivation, associated with the satisfactions derived from socially interacting, communicating, and identifying with others in the marketplace; (3) choice optimization motivation, associated with satisfactions derived from intensively searching for and finding the “right” products at the right price; ( 4 ) self-stimulation motivation, associated with satisfactions derived from encounters with new and interesting stimuli in the shopping environment; and (5) convenience motivation, - associated with satisfactions derived from saving shopping time. The first four motivations were hypothesized by Tauber (36) and supported by the Westbrook and Black study (37). The last motivation variable convenience motivation - will be included in the study because DMTV practitioners have often voiced the opinion that this is a basic characteristic of D W shoppers (10, 16). Further, the evidence shows that in-home shoppers generally display a high need for and place great value on convenience (6,7,13). Based on the consideration of shopping motivation variables, this study hypothesizes that 1. DMTV shoppers and non-shoppers will differ when classified respectively by their power

and authority motivation, affiliation motivation, cboice optimization motivation, and convenience motivation.

pSyCW-=PhiCS Psychographics have emerged as an important ‘VOLUME 1 NUMBER 4 AUTUMN 1987

aspect in the development of consumer profiles. This approach, usually referred to as backward segmentation, profiles consumers by integrating consumer lifestyle, activities, interests and opinions into dimensions that reflect broad behavioral types. The only psychographic variable that will be examined in this study is television viewing activities. This variable will be investigated because practitioners have often voiced the opinion that late night television and other non-prime-time viewing audiences are more likely to respond to DMTV because they are less resistant to advertising messages (10, 16, 38). This hypothesis, first voiced by Al Eicoff (10) has come to be known in the industry at the “theory of sales resistance.” Because there are no published empirical studies the confirm Eicoff’s theory, the television viewing activities of respondents were included in the study to establish their importance for DMTV shoppers. TV viewing has been divided into four time periods. They are: (1) 6:OO a.m.-12 noon, (2) 12 noon-6 p.m., (3) 6 p.m.-midnight, ( 4 ) midnight-6:00 a.m. This study hypothesizes that 2. DMTV shoppers and non-shoppers will differ when classified respectively by television viewing between 6 0 0 a.m.-12noon, 12 noonGp.m., Gp.m.-midnight, midnight-G:OOa.m.

shopping may display a more positive attitude toward risk in general. Attitude toward credit is defined in this study as the extent of an individual’s favorable evaluation of credit and credit cards. The most pervasive form of payment used by DMTV shoppers is the credit card. Indeed, one can infer a relationship between DMTV shopping and the ability to use credit by observing the parallel development of DMTV and the credit card system. Findings have shown that in-home shoppers when compared to non-shoppers generally tend to have a more positive attitude toward credit ( 6 7 , 13, 29). Impulsiveness in this study refers to an individual’s engagement in unplanned behavior. Practitioners have suggested, but provided no support for, the notion that this is a characteristic of DMTV shoppers. However, there is some support from other areas of research for the belief that when compared to non-shoppers in-home shoppers are more likely to have a positive attitude toward impulsiveness (7). This study hypothesizes that 3. DMTV shoppers and non-shoppers will differ when classified respectively by their attitude toward risk, attitude toward credit, and attitude toward impukiveness.

Attitudes Attitudes have played a very important part in profiling and segmentation studies. This study defines a shopping attitude as an enduring organization and evaluation of affect and behavior around a shopping mode that predisposes an individual to react in some preferential manner. While a number of attitudes have been investigated by consumer behaviorists, this study will confine itself to the examination of three which have appeared in inhome shopping research - attitude toward risk, attitude toward credit, and attitude toward impulsiveness. Research evidence suggests that, while individuals may perceive risk in in-home shopping, it is the positive or negative attitude toward risk that is a significant determinant of engagement in in-home shopping (2, 6, 13). One might expect that since there are uncertainties associated with DMTV shopping, such as non-delivery and poor quality of merchandise, that those who engage in this type of

Socio-environment Socio-environmental influences in this study are dealt with in terms of social categories and social relations. Social categories refer to traditional sociodemographic variables. The socio-demographic variables to be investigated are sex, age, marital status, income, education, occupation, presence of children in the home, region of residence, and race. These variables have all been used by other in-home shopping researchers, and appear to have some relationship to shopping behavior. Social relations refer to reference-group influence. Social influence has been posited as having a significant impact on human behavior. Social influence is seen to operate as a function of contextual group situations as demonstrated in the findings of role theory. Findings have shown that the spheres of influence exerted by reference groups on an individual is informational, comparative, and normative. Social relations provide a point of comparison which helps the individual define his own beliefs, values, attitudes, and opinions.

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Sociologists have consistently demonstrated that the extent of an individual’s social ties or lack of ties is shaped by the society in which he lives and which impacts on his behavior. These scholars have further argued that a major dysfunction of urbanized society is the high incidence of lack of social ties or lack of group identification among individuals. This lack of ties is defined as social isolation. Seeman (30), and Srole (33), among others, have noted that social isolation is reflected in feelings of anonymity, low social participation, low membership in social groups, and few visits from friends. This variable has not been totally ignored in marketing and advertising research. Stone ( 3 9 , for example, was able to identi€y a socially isolated type of urban shopper in his study of consumer behavior and urban identification. Researchers have also ob-

served the importance of the socially isolated individual in the diffusion and adoption of innovation process. The reason for including this variable in this study is the recent argument by Eicoff (10) that this condition exerts a positive influence on DMTV shopping behavior. This study hypothesizes that 4. DMTV shoppers and non-shoppers will differ when classified respectively by their sex, age, mariral status, income, education, occupation, presence of children in the home, region of residence, and race. This study also hypothesizes that 5. D W shoppers and non-shoppers will differ when classified respectively by their social isolation.

TABLE 1 SUMMARY OF VARIABLES __

~~

~

~

Dependent Variable

DMTV Shoppers and Non-Shoppers Independent Variables ~~~

~

Motivations(‘)

Psychogaphics~b~

Attitudes(c)

Soclo-environmentcd)

Power and authority

(TV viewind activities)

toward risk

sex@)

affiliation

6:OO a.m.-12:OO noon

toward credit

education levella)

choice optimization

12:OO noon-6:00 p.m.

toward impulsiveness

income(e)

self stimulation

6:OO p.m.-midnight

occupation(d1

convenience

midnight-6:00 a.m.

age(0 marital statudd) employment status(4 presence of children in the homefl region@) race@) social isolation(c)

Likert scaled responses assumed interval. Continuum was “gives great satisfaction,” “gives satisfaction,” “gives some satisfaction,” “gives a little satisfaction:’ “gives no satisfaction at all.” Coded I ,2,3,4,5. {bl Scaled responses assumed interval. Respondents were instructed: “For the 4 time periods put a ‘1’ next to the period you are most likely to watch, a ‘2’ for the second most likely period, a ‘3’for the third most likely, and a ‘4’ next to the period you are least likely to watch.” Ic) Likert scaled responses assumed interval. Continuum was “strongly agree:’ “agree;’ “uncertain:’ “disagree,” “strongly disagree.” Coded 1,2,3,4,5. (0 Categories dichotomously coded 110 based on membershiplnon-membership. ‘*I Classified as highllow and dichotomously coded 110. (0 Classified as younger/older and coded 011. 10) dichotomously coded (1) yes (0) no. (1)

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Methodology A four-part, four-page questionnaire was developed

for gathering the research data. Questionnaires combined items from scales used by past researchers with items generated for the purposes of this study. Afier pretesting the questionnaire with a convenience sample of 32 non-academic subjects the researchers again pretested the questionnaire on a random sample of 200 residents of a medium-size Southwestern city. Results were used to refine the wording of a few questions. Subjects for the final study were then drawn from a national random sample. This was done in order to provide a representative sample of American consumers to allow broad generalization of the results. The names of 2,250 known DMTV shoppers plus the names of 2,250 other residents were randomly selected by a direct mail broker from two separate amalgamated consumer lists. This sampling procedure promised to deliver adequate numbers of both DMTV shoppers and non-shoppers, since the incidence of DMTV shopping was unknown. The sample of 2,250 known DMTV shoppers was randomly drawn from a database of over 175,000 individuals who had purchased a DMTV product or service at least once between February 20 and March 30, 1986. The other half of the sample was randomly compiied by matching and purging utility listings, voters’ registration listings, college listings, and automobile purchase listings. All likely respondents were at least 18 years old or older and lived in one of 1,551 zipcode areas. A premailer was sent out four days before the questionnaire in order to alert individuals about the upcoming survey. The survey mailing comprised a cover letter explaining DMTV, the questionnaire itself, and a postpaid reply envelope coded for state and subject identification. A reminder post card was sent out four days later. Data were collected over a five-week period. A standardized statistical program was used to analyze responses. Stepwise discriminant analyses were performed on 50 percent random splits of the sample in order to allow the researchers to efficiently locate the best set of variables that could discriminate between DMTV shoppers and non-shoppers. This was done in order to avoid a possible upward bias in the predictive accuracy of the discriminant function, which could occur if the same individuals were used both to derive the discriminant function JOURNAL OF DIRECT MARKETING

and to develop the classification matrix (12, 14). The significance of the classificiation procedure was tested by means of the ‘T’statistic.

Results There was a 21.2 percent response to the survey. Only 905 of the 956 responses were usable. Possible non-response bias was assessed by comparing firstweek to fifth-week respondents. This was in keeping with past research logic, which holds that those who respond during the latter part of a survey are likely to most closely resemble non-respondents. Fifth-week respondents differed from first-week respondents on two demographic variables: age and income. Late respondents were much older and reported higher earnings than early respondents. The demographic distribution of the sample is shown in Table 2. When compared to a national sample, these respondents seemed to have a higher level of income and education. In addition, there seemed to be a lower proportion of blacks and Hispanics in this sample when it was compared to national averages. The accuracy of the scaled items as measures of the nine concept variables used in this study was determined by assessing the reliability of their weighted sums as estimates of each case’s true score. The higher the resultant alpha values for each set of items used to measure a concept variable, the more confident we are that they are measuring what they are supposed to measure. The results in Table 3 indicate substantially high levels of measurement accuracy for the nine concept variables. Multivariate stepwise discriminant analysis was performed on the data in order to test the several hypotheses about statistically significant differences between DMTV shoppers and non-shoppers. In the stepwise discriminant analysis the independent variable with the greatest power to predict differences between DMTV shoppers and non-shoppers was first selected. The variable with the next-highest predictive power was next included in each successive step of the selection process. The stepwise selection criterion was Rao’s V which is a generalized distance measure allowing only the inclusion of variables which maximized the distance between DMTV shopper and non-shopper groups. The standardized discriminant function coefficients, group means, and the results of a univariate F test for the final group of twenty variables selected by VOLUME I NUMBER 4 AUTUMN 1987 17

TABLE 2 DEMOGRAPHIC DISTRIBUTION OF THE SAMPLE D M N Non-Shoppers

D Y N Shoppers W=613 Frquency

Percent

N=292 Frequency

Percent

Male

217

35.4

146

50.

Female

396

64.6

146

50.

Variable

Sex

Highest Education level Grade School

49

7.99

17

5.82

High School

297

48.45

120

41.10

CollegelTrade School

210

34.26

111

38.01

57

9.30

44

15.07

Less than $9,999

78

12.73

25

8.56

Graduate School

Income

$10,000-$19,999

126

20.55

69

23.63

$20.000-$29,999

147

23.98

74

25.34

$30,000-$39,999

102

16.64

49

16.78

$40,000-$49,999

65

10.60

32

10.96

Over $50,000

95

15.50

43

14.73

0ccupation

209

34.09

97

33.22

Clerical/Sales

61

9.95

35

11.99

Skilled laborer

88

14.36

42

14.38

Farmer

17

2.77

9

3.08

Military

15

2.45

9

3.08

Homemaker

86

14.03

38

13.01

Student

51

8.32

23

7.88

Some other

86

14.03

39

13.36

ProfessionallManagerial

Age Group (years)

18-24

122

19.90

42

14.38

25-34

221

36.05

96

32.88

35-44

174

28.38

62

21.34

45-54

63

10.29

37

12.67

55-64

19

3.10

33

11.30

older than 64

14

2.28

22

7.53

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TABLE 2 - Cofffiffue~ DEMOGRAPHIC DISTRIBUTION OF THE SAMPLE

Variable

DMTV Shoppers

DMTV Non-Shoppers

N=613

N-292 Frequency

Frequency

Percent

Percent

363 145 64 19 12 10

59.22 23.65 10.44 3.10 1.96 1.63

166 59 23 19 17

56.85 20.21 7.88 2.74 6.50 5.82

367 101 27 118

59.87 16.48 4.40 19.25

173 37 31 51

59.25 12.67 10.62 17.46

359 254

58.56 41.44

136 156

46.58 53.42

28 58 121 73 93 50 54 67 69

4.57 9.46 19.74 11.91 15.17 8.16 8.81 10.93 11.25

16 23 65 36 35 34 16 37 30

5.48 7.88 22.26 12.33 11.99 11.64 5.48 12.67 10.27

496 39 38 13 11 6 10

80.91 6.36 6.21 2.12 1.79 .98 1.63

217 37 18 7 4 5 4

74.32 12.67 6.16 2.40 1.37 1.71 1.37

Marital Status Married Single Divorced Separated Widowed

Some other marital arrangement

8

Employment Status

Full time Part time Retired Unemployed Presence of Children in the Home

Yes No

Repion New England Mid Atlantic East North Central

West North Central Atlantic East South Central West South Central Mountain Pacific Race White Black Hispanic Asian American Indian Pacific Islander

Some other race

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TABLE 3 SUBSCALE ANALYSIS

Scaled Variable

Number of Items

Alpha

Attitude Toward Risk

.73

Attitude Toward Credit

.69

Attitude Toward Impulsiveness

.72

Social Isolation

.a1

Power and Authority Motivation

.62

Affiliation Motivation

.7 1

Choice Optimization Motivation

.73

Self Stimulation Motivation

.65

Convenience Motivation

.72

the stepwise discriminant analysis are shown in Table 4. The standardized discriminant fimction coefficients index the contribution of each variable toward the development of the discriminant score, rather than a variable’s ability to significantly discriminate between groups. The significance of a variable to discriminate between groups is assessed by the value of the univariate F-ratio. The Hypotheses Tested The first set of hypotheses made by this study were that DMTV shoppers and non-shoppers would differ when classified respectively by their power and authority motivation, affliation motivation, choice optimization motivation, and convenience motivation. There was no support for the power and authority and choice optimization hypotheses. However, findings did show that there was a Statistically significant difference between DMTV shoppers and non-shoppers when classified by affiliation (p = .OOOO) and convenience motivation (p = .0198). The second set of hypotheses were that DMTV shoppers and non-shopperswould differ when classified respectively by television viewing between 6 0 0 a.m.-12noon, 12 noon- Gp.m.,Gp.m.-midnight, and midnight - 6 0 0 a.m. The hypotheses for differences in TV viewing for all time periods, excepting midnight to 6:OO a.m. were rejected. The findings supported the hypothesis that there was a significant 20 JOURNAL OF DIRECT MARKETING

difference between DMTV shoppers and non-shoppers when classified by TV viewing between midnight and 6:OO a m . (p = .0007). It was also hypothesized that DMTV shoppers and non-shoppers would differ when classified respectively by their attitude toward risk, attitude toward credit, and attitude toward impukivenes. Only attitude toward risk (p = .009) was found to be significant. All other hypotheses about attitudinal differences between the two groups were rejected. A fourth set of hypotheses were that DMTV shoppers and non-shoppers would differ when classified respectively by their sex, age, maritalstatus, income, education, occupation, presence of children in the home, region of residence, and race. Research evidence partially supported the hypothesized differences in sex (malep = .0117), age (olderp = .0151), marital status (some othq i.e. nontraditionat, marital arrangement,p = .OOOI), presence of children in the home (none, p = .0446), and race (black, p = .0067). The hypotheses that DMTV shoppers and non-shoppers would differ along the dimensions of income, education, occupation, and region of residence were rejected. The final hypothesis that DMTV shoppers and nonshoppers would differ when classified by their social isolation (p = .OOOO) was not rejected. There was a statisticallysignificant difference between the groups when classified by this variable. The signs on the discriminant function coefficients and values of the group means for DMTV shoppers and non-shoppers were used to interpret the results. For the reverse coded variables the lower values indicate possession of higher attributes.The findings show that when compared to non-shoppers individuals who engage in DMTV shopping are more likely to be guided by convenience and affiliation motivations. They tend to be females, younger, and highly socially isolated. They also are more likely to watch TV between midnight and 6:OO a.m. and to have a positive attitude toward credit. Further, DMTV shoppers are less likely to be black and less likely to have a nontraditional marital arrangement.

Implications This study supported some of the long-held beliefs of DMTV practitioners. Mainly, there was support for Eicoffs (10) theory of sales resistance which argues for non-prime-time scheduling of DMTV commercials. DMTV shoppers seem to engage in viewing VOLUME I NUMBER 4 AUTUMN 1987

TABLE 4 DISCRIMINANT ANALYSIS OF DMTV SHOPPERS AND NON-SHOPPERS*** Means lor Shoppers

Means for Non-Shoppers

Univariate F-Ratio

P

.42

1.91

2.21

22.48

.OOOO"

-.23

2.00

1.a5

5.84

.0198"

-.12

2.14

1.91

11.28

.0009"

-.32

3.47

3.1 0

11.76

.0007"

-.42

2.08

1.77

22.34

.oooo**

Sex (male)

.26

.38

.53

6.43

.0117"

Age (older)

.30

2.41

2.77

5.96

.0151"

.27 .30

.02 .07

.48 .20

16.12 2.95

.0001"

(separated) (widowed)

.26

.13

.35

3.8

(married)

.24

.59

.54

.69

.4100 NS

Educatlonal Level (higher)

.26

2.49

2.67

3.61

,0582 NS

0'

Variable 'Motivation (convenience) (affiliation) 'Attitude (toward risk)

'TV Viewing Activities (midnight8:OO a.m.) 'Social Isolation

Marital Status

(some other)

,0867 NS .0530 NS

Occupation (proflmgr)

-.41

.38

.33

.79

.3731 NS

(skilled laborer)

-.26

.42

.48

.22

.6332 NS

.29

1.39

1.52

4.06

(Atlantic)

-.20

.89

.75

.39

(Mid Atlantic)

-.17

.22

.20

.15

.7007 NS

(West North Central)

-.16

56

.44

55

.4601 NS

Children in the Home (none)

.0446"

Region

~~~

S300 NS

~

Race (black)

(some other)

.22

.17

.45

7.44

-.13

.09

.07

.04

.0067" A346 NS

*reverse coded variable "significant at p < .05 **'cross classification accuracy 72.56%; T 91.50; p < .05 D1 chi-square = 87.34. df 20; Rz = 26.7

- -

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between the hours of midnight and 600 a.m. This is the time period traditionally used by most practitioners who believe by and large that prime time ratings are overstated. However, some large corporations such as Time/Life Books have tended to move toward prime time advertising. This may not seem to be the most effective strategy in light of the evidence provided by this survey. Future research should conduct a more rigorous examination of the television viewing habits of DMTV shoppers. One good area to explore would seem to be the relationship between viewing days, television viewing time, television viewing intensity, television program choice behavior, and DMTV shopping behavior. This survey also provided evidence to support Eicoff’s (10) isolation factor hypothesis. DMTV shoppers do indeed tend to be more socially isolated than others. The results show that in addition to a tendency toward social isolation DMTV shoppers are also likely to display a greater need for affiliation. When considered together these two attributes imply that there may be some qualitative aspect to DMTV commercials, perhaps the personal nature of the sales presentation, that promises to satisfy the affiliation needs of the socially isolated. If this is true, then practitioners may need to adopt creative strategies that maximally personalize product offerings. Future DMTV investigations should consider the interrelationship between various message elements such as the use or non-use of visible presenters, presenter and viewer sex, voice-overs, and regional dialects. The social isolation factor also suggests possible experimentation involving social isolation, and the effectiveness of newer home shopping television formats versus traditional DMTV product sponsored commercials. Further, the role of affiliation motivation in characterizing DMTV shoppers suggests the importance of “relevant others” as shopping influences. Future researchers can contribute to the understanding of DMTV by examining the relationship between market influences, socializing behavior and DMTV shopping. The importance of affiliation also suggests research into the feasibility of video kiosks as a DMTV tool. The finding that DMTV shoppers when compared to non-shoppers seem to have a more positive attitude toward risk is not surprising. The history of DMTV has been a history of broken promises - low quality merchandise, late delivery, or non-delivery of orders. Those dangers still exist, but to a lesser 22 JOURNAL O F DIRECT MARKETING

degree than before. The entry of giant corporations into the business has given some stronger credibility to DMTV The fact that DMTV shoppers tend to be younger seems to suggest a generation gap effect, wherein older individuals perhaps still remember the past and view this shopping mode with a healthy dose of scepticism. Products targeted toward younger individuals, who were defined for purposes of this study as under 44, seem more likely to be successfully marketed. This study also suggests that femaledirected products would more likely do better than more male-oriented products. Finally, the findings suggest that future studies need to look beyond the direction or nature of DMTV shopping motivations and consider the importance of these motivations to the individual as well. Since conceptually the ego-based dimension of motives comprises internal motivations as well as psychographic influences, future studies should consider these dimensions in tandem.

Study Limitations Although the findings show that motivational, psychographic, attitudinal, and socio-environmental variables can provide insight into the characteristics of DMTV shoppers, the generalizability of these results is limited in a number of ways. First, this investigation was concerned with DMTV shoppers and the results cannot be projected to cover other types of response television shoppers such as those who respond to home shopping shows. Second, although a national sampling frame was used and respondents were drawn from 1,551 zipcode areas, there was no distinction made between urban and rural dwellers as in the case of many other investigations of inhome shopping behavior. Third, in the interest of time and money limitations, only a limited set of variables was analyzed. It is recognized that there could be other variables which exert important influences o n D W shopping behavior. Fourth, inferences drawn about some of the attributes must be taken with a word of caution since there was low representation in some of the cells, especially on the attribute of race. A final and very important limitation is the lack of a comparative basis for these results since there is no prior published work on DMTV shoppers. However, despite these limitations, the results can facilitate a general understanding of the determinant characteristics of DMTV shoppers.

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