Category-based Applications and Extensions in Advertising: Motivating More Extensive Ad Processing

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1 Category-based Applications and Extensions in Advertising: Motivating More Extensive Ad Processing RONALD C. GOODSTEIN* Consumers watch a television ad at different levels depending on their motivation to process the ad. In this article, the fit between an ad and an evoked ad schema in memory is hypothesized to influence consumers' motivation to process. It is also hypothesized that this motivation is moderated by effects due to consumers' prior category affect and processing goals. Results from an advertising experiment suggest that ads typical of an evoked schema elicit relatively less extensive processing and evaluations, while those atypical of the schema motivate more extensive processing and evaluations. In an extension of previous research in the domain, the results imply that typicality effects are moderated by the extremity of prior category affect. Limited evidence also reveals that typicality effects may be moderated by ad-processing goals. The theoretical and practical implications of these results are discussed. H ow consumers perceive and process television ads is an important area of research that has fascinated consumer researchers, advertising professionals, and laymen alike. Early models of advertising processing assume that viewers notice and attend to many elements of an ad, including its words, music, scenery, and claims (see Macinnis and Jaworski [1989] for a review). In general, these models suppose that individuals view stimuli with great intensity and are highly motivated to process the material contained in persuasive communications (cf. Maheswaran and Chaiken 1991; McGuire 1972). However, other research illustrates that many ads are processed in a less effortful manner, perhaps because consumers are less motivated to process ad information (Macinnis and Jaworski 1989). In this case a subset of the available information may be used to form evaluations (Chaiken, Liberman, and Eagly 1989; Petty, Cacioppo, and Schumann 1983). Despite the critical role that motivation may play in determining the depth of ad processing, little research *Ronald C. Goodstein is assistant professor of marketing at the John E. Anderson Graduate School of Management at the University of California, Los Angeles, 405 Hilgard Avenue, Los Angeles, CA The author gratefully acknowledges support from his dissertation advisers Jim Bettman and Julie Edell; present and former Duke colleagues Marian Moore, Jennifer Escalas, Ajay Kalra, Kevin Keller, and Itamar Simonson; UCLA colleagues Meg Campbell, Deb Heisley, and Hal Kassarjian; and Julie Baker, Dhruv Grewal, and Mita Sujan. Special thanks are due to Julie Edell, whose feedback on alternate analysis plans was critical to the final article. Finally, I extend my appreciation to the three reviewers and to the editor for their helpful comments in revising this article. 87 has empirically tested variables that affect processing motivation. This article proposes that an ad's fit with an evoked category in memory influences the intensity of processing. In addition, individual difference variables, such as consumers' prior category affect and adprocessing goals, are proposed to moderate the impact of category expectations on the nature of ad processing. Categorization theory provides new perspectives for understanding how consumers' expectations about television ads motivate ad processing. Then, consumers' prior category affect and ad-processing goals are discussed in terms of how they moderate the relationship between category expectations and ad processing. The basic tenet underlying these propositions is that these three variables will influence consumers' motivation to process an ad. Hypotheses relating to each proposition are developed and supported in a classroom study. Finally, the results and implications are discussed from both an advertising and a categorization framework. CONCEPTUAL FOUNDATIONS Category-based Processing Research in psychology and consumer behavior indicates that categorization directly links people's expectations to their motivation to process and subsequent affective evaluations of stimuli (e.g., Fiske 1982; Sujan 1985). The category-based approach to processing was developed as an alternative to piecemeal models of attitude formation in which evaluations result from an integrative appraisal of individual stimulus character by JOURNAL OF CONSUMER RESEARCH, Inc. Vol. 20 June 1993 All rights reserved /94/ $2.00

2 88 istics (e.g., McGuire 1972). Categorization theory specifies a less labor-intensive method of evaluation in which organized prior knowledge related to a category is used in evaluations. This knowledge, referred to as a schema (see Fiske and Neuberg 1990), contains information about category attributes and their links, prototypic exemplars, and an affective tag assessing one's attitude toward members ofthe category. When confronted with a stimulus, the perceiver automatically attempts to match it with an evoked category description. When there is a match, the perceiver will evaluate the stimulus on the basis of the affect stored in the category schema. When there is a mismatch, the evaluation is conceptualized to be piecemeal. In other words, incongruity between the stimulus and category expectations motivates people to process a stimulus in greater detail in order to form an evaluation (Fiske and Taylor 1991, p. 5). "If relatively categoryoriented processes are successful, then the perceiver goes no further toward more attribute-oriented processes" (Fiske and Neuberg 1990, p. 3). Alternately, only when there is a mismatch will more extensive processes be evoked (Boush and Loken 1991). Empirical evidence illustrates that this relationship is heightened when task importance is low (Maheswaran and Chaiken 1991). The category-based approach to evaluation has been supported in a variety of consumer domains, including product judgments (Sujan 1985), brand extension judgments (e.g., Boush and Loken 1991; Keller and Aaker 1992), product category assessments (Loken and Ward 1990), and information search (Ozanne, Brucks, and Grewal 1992). Ad-related evaluations have also been conceptualized to follow a categorization and evaluation process, but this idea has not been directly tested (Krugman 1972; Sujan and Deklava 1987). This article provides that test by proposing that the motivation to process an ad is dependent on the ad's fit with a relevant category in memory, and that this motivation directly influences the nature of one's ad processing. In addition to testing the applicability of categorization theory in advertising, this article also addresses two important aspects of categorization theory that have received relatively little attention. First, this article assesses whether the valence of schema affect moderates the processes predicted by categorization. This is an issue that has been neglected in social cognition research and is viewed as a serious limitation in our understanding of motivation (Hewstone 1989). In a notable exception, Mandler (1982) conceptualizes affect extremity as linked to extent of processing. In the consumer literature, Meyers-Levy and Tybout (1989) and Stayman, Alden, and Smith (1992) find empirically that positive affect motivates more extensive stimulus processing. However, these researchers assume that affect is the result of the ease with which an object is categorized rather than from the prior category affect stored in the schema (e.g., Fiske 1982). JOURNAL OF CONSUMER RESEARCH This article proposes that as schema affect becomes more positive consumers become more motivated to process an ad. Affect, under this conceptualization, is directly linked to the schema rather than to a predisposition of the individual (lsen 1984) or the ease of categorization (Mandler 1982). Although affect is not the focus of her study, Fiske (1982) finds that subjects' evaluations of both politicians (negatively evaluated category) and "old flames" (positively evaluated category) are category based when an individual matches the appropriate schema. However, in a follow-up study using the same subjects she observes that participants are more likely to meet someone fitting the description of an old flame than a politician. One interpretation of this data is that the positive affect associated with the old-flame schema motivated further interaction than predicted by the match between the stimulus and the category. Note that this indicates that, although the evaluation is predicted by categorization, the nature of the nonevaluative processing is more extensive. Meyers Levy and Tybout (1989) make a similar interpretation of Fiske's data and assume, without testing, that prior category affect may motivate processing beyond the levels predicted by successful categorization. My study proposes and tests whether positive prior category affect motivates processing when a stimulus matches an evoked category in memory. Another aspect of categorization theory receiving little attention in the consumer literature relates to goals. Fiske and Neuberg (1990) illustrate that one's goals related to impression formation will moderate schemabased processing. Consumer researchers have examined how the fit between the stimulus and the category influences processing but have not examined how consumers' goals might influence this process. The effect of goals on ad processing has been studied elsewhere in the consumer domain (e.g., Gardner, Mitchell, and Russo 1985; Keller 1987, 1991; MacKenzie and Spreng 1992). Findings indicate that subjects given the task of evaluating brands process ads more extensively than do those evaluating ads. This article investigates how adprocessing goals influence category-based processing of television ads. Motivation, Opportunity, and Ability Social psychology provides a framework for testing the nature of one's message processing that is dependent on an individual's motivation, opportunity, and ability to process the information contained in a persuasive message (e.g., Chaiken 1987; Chaiken et al. 1989; Petty and Cacioppo 1986). Macinnis and Jaworski (1989; Macinnis, Moorman, and Jaworski 1991) extend this framework to advertising and propose that factors that influence a consumer's motivation, opportunity, or ability to process an ad will influence the nature of that processing. In particular, these authors conceptualize five levels of processing that are dependent on knowl-

3 CATEGORY-BASED EXTENSIONS IN ADVERTISING edge of consumers' antecedent combinations of mot i vation, opportunity, and ability. These levels range from feature analysis, in which all are at extremely low levels, to constructive processes, in which all are at very high levels. This article focuses exclusively on factors that influence consumers' motivation to process ad information. By narrowing the focus to this single construct, three levels of processing described by MacInnis and Jaworski are germane. The first two levels are category related but are differentiated by the degree to which consumers focus on message elements. The first level, basic categorization (see their level 2), is hypothesized to occur when motivation to process an ad is low. The second level, meaning analysis (see their level 3), is predicted to occur when motivation to process an ad is low to moderate. While category judgments guide evaluations in both cases, message-relevant responses are more likely under this level. The third level, information integration (see their level 4), is likely to occur when motivation to process an ad is moderate to high. Here, attitudes are formed through a systematic evaluation of message-relevant arguments. At this level, categorybased responses to salient ad cues will have little impact on ad and brand evaluations. To date, the category-based levels of processing have not been directly tested in the advertising domain. Furthermore, while recent research has suggested factors that might influence consumers' motivation to process ad information, little empirical research has explicitly examined these factors or the specific nature of the processing they evoke (MacInnis et al. 1991). (See MacKenzie and Spreng [1992] for a notable exception.) This article proposes that motivation to process (and hence processing of) an ad is affected by factors inherent in the ad (i.e., its typicality). In addition, individual factors (e.g., consumers' processing goals and prior category affect) are predicted to moderate the impact of ad typicality on the nature of processing. In particular, it is demonstrated that relatively higher levels of processing occur (1) when an ad is atypical (vs. typical), (2) when an ad is typical and prior category affect increases, and (3) when an ad is typical but brand (vs. ad) processing is encouraged. In essence, atypical ads will motivate analytical processing, while positive prior category affect and brand goals will lead to more elaborative processing of typical ads. Advertising Schemas Before extending category theory to advertising one must ask whether consumers have schemas for ads. Schemas are developed through repeated exposure within a domain, and advertisement repetition and regularity (e.g., redundant semantic, physical, and structural features) theoretically suggest that ad-related schemas exist (Stoltman 1991). Empirical data support that television advertising schemas exist and are pre- dominantly exemplar based (Goodstein, Moore, and Cours 1992). Although ad-related schemas might exist at many different levels, it is believed that ad schemas organized around product types represent the basic level at which these schemas are organized (see Meyers-Levy and Tybout 1989; Sujan 1985). Evidence for this organizational scheme is supported both empirically (Goodstein et al. 1992) and managerially. For instance, the president of one of the leading advertising agencies in the United States stated that his company's goal was to "make commercials that are unique relative to others in the product class." HYPOTHESES Effects of Ad Typicality Television ads, because of constraints on opportunity to process their information, are typically low involvement in nature and stimulate relatively low levels of processing (e.g., MacInnis et al. 1991). The general principle studied in this article is that a television ad discrepant from category expectations motivates relatively more elaborate ad processing than does an ad that matches category expectations. While category-based comparisons have not been examined within the advertising domain, incongruity between the visual and verbal elements within a print ad has been shown to increase ad recall and claim recognition, which indicates deeper processing (Heckler and Childers 1992; Houston, Childers, and Heckler 1987). Incongruity between a television ad and a cued ad category in memory should also lead to more extellsive processing. Although more extensive processing motivated by schema incongruity has been found in other consumer research (e.g., Keller and Aaker 1992), advertising presents a conceptually different application. Specifically, ad categories may contain many "core" personalities (exemplars; Goodstein et al. 1992) while a brand consists of a single core personality (prototype; e.g., Keller and Aaker 1992). Thus, if the model extends to advertising, then its applicability in consumer behavior is broader than previously conceptualized. Novel aspects of advertisements are reported to enhance attention (Alsop 1988), and it is fair to claim that schema-inconsistent ads enhance novelty at a holistic level (Stoltman 1991). Novelty relating to ads can be claim related (substantive) or execution related (cosmetic), though cosmetic variation is hypothesized as more likely to affect consumers' motivation to process television ads (Schumann, Petty, and Clemons 1990). Under low motivation conditions, cosmetic variation has been shown to affect attitudes (Schumann et al. 1990), though no evidence verifies whether cosmetic atypicality motivates more extensive processing oftelevision ads. The effect of schema incongruity on processing has been examined in nonadvertising domains in terms of 89

4 90 processing outcomes. In addition to recall and claim recognition, more extensive processing has been exemplified by increased cognitive responses and decreased category-related responses (Sujan 1985; Sujan, Bettman, and Sujan 1986), a weaker relationship between prior category attitudes and subsequent evaluations (Pavelchak 1989), and less rapid impression formation (Boush and Loken 1991; Ozanne et al. 1992). Researchers have hypothesized that patterns among these outcomes (multivariate tests) indicate the extent of consumers' evaluative processing (Sujan 1985; Sujan et al. 1986). This implies that the direct test of the extent of overall ad processing is a multivariate analysis. Thus, HI: When an ad is discrepant (atypical) from the product type ad schema, relative to when it is consistent with the schema, (a) more cognitive responses are generated, (b) fewer categoryrelated cognitive responses are generated, (c) the valence of cognitive responses is less consistent with prior category affect, (d) overall evaluations are less consistent with prior category affect, (e) the ad is watched longer, and (f) ad information is better recalled. Moderating Effects of Category Affect Although research in social perception illustrates that stimulus affect may exert a significant influence on information processing, this influence has been relatively ignored in the schema literature (Hewstone 1989). In a notable exception, Mandler (1982) asserts that affectladen.schemas may have effects on processing beyond those predicted by typicality assessments depending on the ease with which an object can be categorized in memory. Meyers-Levy and Tybout (1989) test Mandler's assertion in the product extension domain. They find that positive affect leads to increased cognitive responses and better recall of brand information. Although not directly tested, Fiske's (1982) results suggest that both positive and negative schema affect may be transferred to new stimuli but that positively valanced stimuli tend to be approached and negatively valanced stimuli avoided. The discussion indicates two ways that a schema may invoke more intensive ad processing: through a mismatch between the schema and the stimulus or through positive affect associated with a matched schema. When an ad is atypical of an evoked category, processing is already high, so schema affect will have minimal additional effects on processing (Fiske and Pavelchak 1986). With typical ads, however, as schema affect increases it is expected to motivate more extensive ad processing. This processing will be exemplified by better recall of advertised brands and brand claims, more cognitive responses (Meyers-Levy and Tybout 1989), longer ad-viewing times (Fiske 1982), and fewer category-related cognitive responses (Sujan 1985). Note that this JOURNAL OF CONSUMER RESEARCH hypothesis does not include Pavelchak's (1989) measure of the relationship between prior category affect and postexposure affect. These indicators are not relevant in the test of Hypothesis 2 because the typical ad is likely to evoke a category-based response (Fiske 1982) and the hypothesis tests simple main effects within the typical ad condition. Pavelchak (1989) finds that all explainable variance in the evaluation of a matched stimulus will be accounted for by the category predictor (schema), while this hypothesis tests for differences in nonevaluative processing. Prior category affect should, therefore, moderate processing of typical ads such that, H2: When an ad is consistent (typical) with the product type ad schema and as the valence of the affect of the schema increases, (a) more cognitive responses are generated, (b) fewer category-related cognitive responses are generated, (c) the ad is watched longer, and (d) ad information is better recalled. Moderating Effects of Processing Goals Impression formation is dependent not only on interactions between the category and the stimulus, but also on the perceiver's judgmental goal (Fiske and Neuberg 1990). In this article the moderating effect of two common ad-processing goals (Gardner et al. 1985; Keller 1987, 1991) on category-based predictions are examined. Specifically, subjects with brand-processing goals, relative to those with ad-processing goals, are hypothesized to process typical ads more extensively. According to Keller (1991), consumers with nonbrand (ad) evaluation goals focus on ad-related elements of the ad, while those with brand evaluation goals focus on both ad-related and brand-related elements of the ad. As a result of this additional focus, brand-processing goals evoke better recall by subjects than do ad-processing goals, indicating more extensive processing. Similarly, Gardner et al. (1985) find brand goals to be related to equal recall of ad elements and to better recall of brand elements. They also note that subjects with brand goals list more cognitive responses to the ads than do subjects with non brand goals. The discussion indicates that the use of more extensive processing should be related to atypical versus typical ads, and brand versus ad-processing goals. Differentiating between these two systematic approaches is not the purpose of this study, as the overall rate of processing should be uniformly high under both scenarios (Maheswaran and Chaiken 1991). However, when an ad is typical, subjects with a brand evaluation goal, relative to those with an ad evaluation goal, should demonstrate more extensive ad processing. In terms of the measures used in this study, when viewing typical ads, subjects with brand goals (vs. nonbrand goals) will better recall advertised brands and brand claims (Keller 1991), generate more cognitive responses (Gardner et al. 1985), and view ads longer since more information must be

5 CATEGORY-BASED EXTENSIONS IN ADVERTISING attended to. More extensive processing should also be indicated in terms of the percentage of cognitive responses that are category related. Based on the same rationale given in Hypothesis 2, Pavelchak's (1989) analysis of the relationship between prior category affect and subsequent affective reactions is not applicable to Hypothesis 3. Thus, goals should moderate the processing of typical ads such that, H3: When an ad is consistent (typical) with the product type ad schema and processing goals are brand oriented, relative to nonbrand oriented, (a) more cognitive responses are generated, (b) fewer category-related cognitive responses are generated, (c) the ad is watched longer, and (d) ad information is better recalled. METHOD The hypotheses were examined in a repeated-measures experiment that tests how consumers' prior expectations about advertisements influence impression formation. The experiment also examined whether prior category affect and processing goals affect processing intensity for typical ads. Subjects for the experiment were recruited from undergraduate marketing classes, ranging in size from 20 to 45 students. A total of302 students at three major southeastern universities participated in the study. The data were collected in two phases. The first phase measured subjects' general affect toward particular categories of advertisements (byproduct class) as well as their descriptions of typical ads from these categories. The second phase tested the hypotheses. The two phases of data collection were disguised to appear unrelated. Processing instructions were a between-subjects factor, and ad typicality and prior category affect were withinsubjects factors. The design is based on Winer's (1971) plan 7.3 for repeated measures. Phase 1 Product type ad schemas and their associated affect were measured in a survey that subjects completed during the first week of classes. The students' professor informed the class that the results would be used to design future class lectures. The author was not involved with the distribution or collection of these materials. Phase 1 was designed to obtain a description and associated affect of ad schemas for eight product types that, in a pretest, elicited positive reactions from some students and negative reactions from others. These product types included ads for airlines, bar soap, breakfast cereal, computers, dog food, fast-food restaurants, shampoo, and toothpaste. Students were asked to sign and complete a survey that contained 13 scale items and one open-ended question for each of the eight product types (see App. A). The scales included eight items capturing category affect (alpha =.93). Schema affect scores were formed by adding scale item responses, with reverse scoring where necessary, and ranged from eight (most negative) to 56 (most positive). This was done so that subjects' prior ad category affect within each product class could be included in the main study as a measured variable. The open-ended question asked subjects to provide a general description (schema) of television ads for each product type. Phase 2 Four weeks after phase 1 the author came to the same classes and asked students to participate in a marketing research study. Those participating were promised a chance to win a cash prize. Participants were given a questionnaire and asked to sign it and complete a series of scales describing their familiarity with and attitude toward two brands each of dog food, fast-food restaurants, and shampoo. These were product types from phase 1 for which schema descriptions were elicited from subjects and for which subjects evidenced both positive and negative affect within a product class. They also completed these scales for two brands of diet cola, a decoy leading to the anticipation of seeing more ads than would actually be shown. After subjects completed these scales, they read twice instructions asking for their impressions of the ads (brands) they were about to see. The instructions also asked them to watch the commercials as if viewing them at home (e.g., "If the ad is not of interest to you, feel free to tune it out"). Further, as soon as they had formed an impression of a given ad, they were to turn to the next page of the questionnaire, record the time showing on a 24-inch by 24-inch stop clock, and write all of the thoughts and feelings they had while watching the ad no matter how insignificant or irrelevant the thoughts and feelings seemed. This task preempted their watching the rest of the ad. After reading these instructions, subjects were shown one 30-second ad and completed the time and thought measures for that ad. Subjects had two minutes, timed from the end of an ad, to complete these measures before the next ad was shown. The process was repeated for six ads with order of ad presentation counterbalanced across classrooms. After completing thought listings for the sixth ad, subjects filled out ad and brand attitude scales pertaining to each ad. Finally, subjects were asked to indicate whether they had focused on ad or brand information while watching the ads. Five minutes after collecting the questionnaires, the author asked students to complete a second questionnaire. First, subjects spent two minutes listing all of the brands or companies that they remembered being advertised. Next, they completed an aided recall task measuring their memory for specific claims made in the two dog food advertisements. Subjects then watched each ad again, in its entirety. After each ad participants 91

6 92 filled out a 28-item description list comparing this ad to others for the product type. Finally, the questionnaires were signed, collected, and the cash prize awarded. Subjects were debriefed, and the experiment and its applicability to ad testing were discussed. Only eight of the 302 participants surmised that phases 1 and 2 were interconnected, although they were unsure of the nature of that connection. The experiment lasted 45 minutes, and discussion went until the end of the class. Independent Variables Ad Typicality. The stimuli were 30-second television ads for six different brands. Two were for dog food, two for fast-food restaurants, and two for shampoo. The product type was prominently displayed in the opening scene of each ad, encouraging the elicitation of the product type ad schema (Edell and Anderson 1990). Ads included in the study varied with respect to subjects' familiarity with the advertised brands, but none of the commercials had been shown locally. The ads were "typical" in terms of the claims each made but differed in terms of cosmetic typicality (cf. Schumann et al. 1990). For instance, the cosmetically typical shampoo ad featured a scene of a woman washing her hair, while the atypical ad featured an interview with a French foreign-exchange student and used subtitles for interpretation. Both ads made similar substantive claims about how the products left hair soft and manageable. Candidate ads were preselected on the basis of how well they compared to the phase 1 descriptions. Then in a pretest a panel of 15 experts (marketing faculty and doctoral students) rated how typical or atypical ads were relative to others from the product class. On the basis of this process the six ads were identified for the study.. A manipulation check confirmed that participants' ratings of the ads matched those of the panel of experts. Each pair of ads was roughly equivalent in terms of the claims made and other substantive factors. However, the ads still could not be matched exactly given that they were for real brands. Therefore, individual ad differences were controlled for by including a specific ad factor in all analyses. Processing Goals. Viewers' processing goals were manipulated in the instructions subjects received. Subjects in the brand condition were directed to evaluate the quality of the advertised brands. Those in the nonbrand condition were directed to evaluate how entertaining they found the ads (Keller 1991). Prior Affect toward Ads in the Product Category. Prior category affect was included in the study as a measured factor. Subjects' schema affect scores for ads from the three product categories were included in the analysis, which resulted in a mixed design (Sujan 1985). Scores ranged from eight to 56, with neutral affect represented by a score of 32. Dependent Variables JOURNAL OF CONSUMER RESEARCH Viewing Time. Viewing time was used as a measure of the amount of attention given to ads (cf. Olney, Holbrook, and Batra 1991). Viewing time was measured with a stop clock that counted down from 45 seconds to zero in one-second intervals. The clock was reset at the beginning of each ad, running from 45 to 15 for each 30-second ad. Subjects recorded the number appearing on the clock when they had formed their impression of the ad (brand). Cognitive Responses. Immediately after subjects recorded how long they watched the ad, they wrote down all of the thoughts and feelings they experienced while viewing the ads. SUbjects' responses were separated into individual thoughts and coded by two independent judges. Individual thoughts were coded as category references (alpha =.73), ad or brand focused (alpha =.70), simple versus complex (alpha =.57), and by their valence (alpha =.94; Sujan 1985). Interjudge reliability was greater than 70 percent for categories included in the analysis (cf. Nunnally 1978). Disagreements were resolved by discussion. The proportion of specific thoughts to total thoughts was analyzed to control for differences explained simply by viewing time. Evaluations. Attitudes toward the ads (Aad) and toward the advertised brands (Ab) were measured on three seven-point semantic differential scales anchored by good and bad, likable and dislikable, and favorable and unfavorable. Scale scores were formed by averaging the values of these items. The coefficient alpha was.98 for both Aad and Ab. Memory Performance. Brand name or company recall was measured by having subjects write down all of the brands or companies they remembered from the ads. Recall was coded as incorrect if an advertised brand or company was not listed or if a nonadvertised brand or company was listed. Ad claim recognition was measured for eight attributes on a seven-point semantic differential (-3 = definitely not mentioned; + 3 = definitely mentioned). Because of classroom time constraints claim recognition was assessed only for the two dog food advertisements. The scales included several attributes mentioned in the ad and several that were not. Those not mentioned were judged in a pretest as typical of brands in the category (schematic foils) to provide a measure analogous to that used in signal detection applications in consumer research (Heckler and Childers 1992). The typical ad contained slightly more information; therefore, a dummy variable for each ad was included in the analysis to control for this difference. This difference, however, would work against the hypothesis. Recognition scores were computed for each attribute by multiplying subjects' responses by one for advertised attributes and by negative one for foils. Overall recognition was computed by adding up the scores for the eight attributes and

7 CATEGORY-BASED EXTENSIONS IN ADVERTISING ranged from -24 (perfectly incorrect) to +24 (perfectly correct). Control Variables Four control variables captured differences that might obscure the effects related to the dependent variables. As mentioned earlier, real ads were used in the study, which made it impossible to match them exactly on all nonmanipulated factors. Therefore, an ad factor was included in all analyses to control for individual ad differences, as well as their interactions with the independent variables. Brand-related control measures included subjects' familiarity with the advertised brands (1 = not at all familiar; 7 = very familiar) and their prior brand attitudes (Prior Ab). Prior Ab was measured by summing responses on three seven-point scales anchored by good and bad, likable and dislikable, and favorable and unfavorable (alpha =.97). Finally, a control factor was included to account for the effects of counterbalancing the order of ad exposure. RESULTS The general propositions concerning the extensiveness of one's ad processing were examined according to a MANCOVA design. Univariate relationships were examined according to an ANCOVA design, and effect sizes (1/ 2 ) were estimated according to Cohen's (1977) criteria. I In this study the between-subjects factor is processing goal (two levels: brand and nonbrand). Tests involving this factor used the between-subjects error term. The within-subjects (repeated-measures) factors and variables are ad typicality (two levels: typical and atypical), prior category affect, the ad factor that was nested within typicality, and the other control measures. Tests of these variables used the within-subjects error term. Manipulation Checks After completing the ad and brand evaluation measures, subjects were asked to describe their processing using a single-item, seven-point scale (1 = I concentrated only on the advertisements; 7 = I concentrated only on the brands). Analysis of covariance indicated that all subjects concentrated on the ad information, but those with brand goals indicated significantly more brand concentration than did those with nonbrand goals (brand = 3.17, ad = 2.77; F(l,286) = 6.70, P <.01; 1/ 2 =.02). Additionally, analysis of the cognitive responses revealed that subjects with brand goals listed significantly more brand-related comments (brand =.416, ad lcohen's formulation of effect sizes (1/2) is adopted here since he provides guidelines about the "significance" of an effect. If.0 I < 1/2 <.06, then the effect is small; if.06 :s; 1/2 <.14, then the effect is medium; and if 1/2 ~.14, then the effect is large. =.270; F( 1,286) = 17.12, p <.001; 1/ 2 =.06), rendering the processing goal manipulation successful. Ad typicality was assessed by analyzing subjects' responses to three of the 28 ad descriptors: "different," "typical," and "unique" (alpha =.88). Subjects rated how well each adjective described an ad, relative to other ads from the product category (1 = not at all well; 5 = very well). By summing these items, with reverse scoring where necessary, a typicality score for each ad was determined. Scores ranged from three (most typical) to 15 (most atypical). Pairwise I-tests indicated that the mean typicality score differed for each pair of ads. 2 The basic ANCOV A model confirmed that the mean typicality score for the typical ads was significantly lower than the mean score for the atypical ads (typical = 7.17, atypical = 12.17; F(1,286) = , p <.001; 1/ 2 =.68). Thus, subjects viewed the ads in the intended manner, supporting the typicality manipulation. Multivariate Analyses Multiple analysis of covariance was used to examine the effects of ad typicality on the set of nine dependent measures and to analyze within the typical ad cell the overall effect of prior category affect and viewing goals on the set of five dependent measures. These analyses provide the direct test of the hypotheses concerning overall processing differences since these processes cannot be directly observed (Sujan 1985). That is, the multivariate analyses test whether the overall extent of processing differs in the predicted manner. The mean value for each of the levels of the factors is presented in Table 1, and the regression coefficient of the prior affect measure on the dependent variables is shown in Table 2. Effect sizes (1/ 2 ) are estimated by the appropriate transformation for multivariate tests (Rao and Monroe 1989). The MANCOV A supports a main effect of advertisement typicality on impression formation (F(9,243) = 22.69, p <.001; 1/ 2 =.46). The cell means and coefficients indicate that atypical ads are processed more extensively than are typical ones, which supports the general hypothesis. The particular effects pertaining to processing instructions and prior category affect, however, were stated in terms of simple main effects. Winer (1971, p. 384) suggests that "specific comparisons that are built into the design or suggested by the theoretical basis for the experiment can and should be made individually, regardless of the outcome of the corresponding overall Ftest." The simple main effects analysis revealed that as prior category affect increased, subjects processed ads significantly more extensively 2The pairwise t-test results were significant for dog food (typical = 9.28, atypical = 12.80; t(600) =' 16.80, P <.001), shampoo (typical = 5.76, atypical = 11.58; t(594) '" 28.96, p <.001), and fast-food restaurants (typical = 6.44, atypical = 11.97; t(592) = 26.60, p <.001). 93

8 94 JOURNAL OF CONSUMER RESEARCH TABLE 1 CELL MEANS OF DEPENDENT VARIABLES Dependent measures Ad typicality Conditions Processing goal Total Thoughts Category Positive (%) (%) Negative Ad (%) (%) Aad Viewing time Brand name recall Ad claim recall Typical Typical Atypical Atypical Brand Nonbrand Brand Nonbrand (F(5,243) = 4.36, p <.001; Tl2 =.08), supporting the hypothesized relationship. The simple main effects test also indicated that subjects with brand instructions process typical ads moderately more extensively than do those with ad-related instructions (F(5,243) = 2.13, p <.06; Tl2 =.04). Although planned comparisons do not require a test of the interaction effects, examining the significance of the interactions is interesting. The interaction of ad typicality and prior category affect was highly significant in the analysis (F(5,243) = 4.60, p <.001; Tl2 =.09), further supporting the hypothesis. The interaction of ad typicality and processing instructions was not significant (F(5,243) < 1, NS). The mixed evidence on processing instructions suggests that simple main effects also be examined for the atypical cell. This analysis supported the original hypotheses in that no simple main effect on processing was found in the atypical cell for prior category affect (F(5,243) = 1.24, NS) or processing goals (F(5,243) = 1.62, NS). In summary, two of the three hypotheses were strongly supported in terms of overall processing. Although the processing instruction hypothesis was only marginally supported, evidence for the simple main effect suggests that the effects of goals on processing may be limited to typical ads. To examine the nature and extent of this processing at a more micro level, univariate analyses were conducted. Univariate Analyses 3 Advertisement Typicality. Hypothesis I proposed that subjects would process atypical ads more exten- 3Covariate effects were controlled for before concluding on the hypotheses. The ad factor was significant (p <.00 I) in all of the equations. Prior Ab was significant (p <.00 I) and positively related to Aad and A b, percentage of positive thoughts, time watched, and recall, and negatively related to percentage of negative thoughts. Brand familiarity was related (p <.00 I) to reductions in total thoughts and time watched, and to increases in the percentage of category thoughts, A b, and brand name recall (p <.00 I). Order of ad exposure was marginally significant (p <.10) in the time watched, percentage of positive thoughts, and percentage of negative thought equations. All univariate F-tests had 1,286 degrees of freedom. sively than they would typical ads. Analysis of covariance indicated that when viewing atypical ads subjects generated significantly more total thoughts than they did in response to typical ads (typical = 2.58, atypical = 2.77; F = 7.69, p <.01; Tl2 =.02), supporting Hypothesis lao Additional analysis indicated that a significantly greater proportion of thoughts were ad related when ads were atypical (typical = 82.25, atypical = 92.27; F = 36.83, p <.001; Tl2 =.11). So, although the ads were processed more extensively, the focus was on the ad rather than on piecemeal processing of the brands. In addition, the percentage of category references was higher for the typical ads than for the atypical ads (typical = 40.62, atypical = 24.85; F = 46.13, p <.001; Tl2 =.14), supporting Hypothesis 1 b. Hypothesis lc stated that the relationship between prior category affect and the valence of cognitive responses would be less consistent for atypical ads than for typical ones. The test of the hypothesis was made by examining whether the prior category affect coefficient was higher for typical ads than for atypical ads in both equations for valence of thought. Analysis indicated a greater relationship between prior category affect and the percentage of positive comments for the typical ads than for the atypical ads ({3typical =.007, (3atypical =.002; F = 15.10, p <.001; Tl2 =.05). Prior category affect also had a greater influence on negative comments when ads were typical than when they were atypical ({3typical = -.007, (3atypical = -.002; F = 13.53, P <.001; Tl2 =.05). Subsequent analysis showed a significantly lower percentage of positive thoughts in response to the atypical ads (typical = 47.81, atypical = 43.33; F = 8.40, p <.01; Tl2 =.03) and a significantly higher percentage of negative thoughts in response to the atypical ads (typical = 46.01, atypical = 48.88; F = 5.08, p <.05; Tl2 =.02). Atypical ads were also less well liked in terms of both Aad (typical = 4.54, atypiqll = 4.39; F = 5.09, p <.05; Tl2 =.02) and Ab (typical = 4.60, atypical = 4.00; F = 38.60, p <.001; Tl2 =.12). Further, subjects' prior category affect had a significantly greater influence on Aad in the typical condition than in the atypical condition ({3typical =.047, {3atypical =.010; F = 20.29, p

9 CATEGORY-BASED EXTENSIONS IN ADVERTISING 95 TABLE 2 BETA COEFFICIENTS OF REGRESSION OF PRIOR CATEGORY AFFECT ON DEPENDENT VARIABLES Dependent measures Thoughts Brand Ad Category Positive Negative Ad Viewing name claim Ad condition Total (%) (%) (%) (%) Aad Ab time recall recall Typical Atypical NOTE.-The prior category affect scale ranges from eight (most negative) to 56 (most positive). Blank spaces indicate an effect which was nonestimatable. <.001; 1]2 =.07). Similarly, subjects' prior category affect had a significantly greater influence on Ab when ads were typical (!3typical =.022,!3atypical =.006; F = 14.82, p <.001; 1]2 =.05), and thus Hypothesis 1 d was strongly supported. On average, subjects watched atypical ads significantly longer than they did typical ads (typical = 17.41, atypical = 23.10; F = 77.81, p <.001; 1]2 =.21), confirming Hypothesis Ie. Finally, although ad typicality was significantly related to brand name recall, brands advertised in typical ads were better recalled than those advertised in atypical ads (typical =.962, atypical =.887; F = 14.02, p <.001; 1]2 =.05).4 In terms of ad claim recall, subjects recognized ad claims marginally better when exposed to the atypical ad (typical = 6.15, atypical = 6.75; F = 2.68, p <.10; 1]2 =.01), providing mixed evidence for Hypothesis If These results are summarized in Part I of Appendix B. In general, the prediction that ad typicality directly influences the impression formation process was strongly supported by the multivariate analyses. The univariate analyses indicate that the strongest effect is in terms of time watched, and that eight of the nine effects confirm that atypical ads are processed more extensively than are typical ads. Prior Category Affect. Hypothesis 2 predicted that subjects would process typical ads more extensively as the valence of the category affect increased. Multiple analysis of covariance supported the hypothesis, and univariate analyses were used to explain these relationships. Hypothesis 2a proposed a positive relationship between subjects' prior ad category affect and the total number of cognitive responses they generated in response to the typical ads. Although the coefficient was positive, it was not significant in the model (F < 1, NS). Prior category affect was also not significantly related (F < 1, NS) to differences in the percentage of categoryrelated thoughts, failing to support Hypothesis 2b. 40ne ad was an outlier in terms of brand name recall. When it is removed from the analysis, the hypothesis is supported (p <.01). However, Hypothesis 2 was supported in terms of the other measures. Hypothesis 2c predicted a positive relationship between prior category affect and how long subjects watched typical ads. The analysis indicated a strong positive relationship between prior category affect and time watched (13 =.183; F = 23.14, p <.001; 1]2 =.07), supporting Hypothesis 2c. Similarly, Hypothesis 2d proposed a positive relationship between prior category affect and memory for information relating to the typical ads. Analysis of covariance indicated no relationship between prior category affect and brand name recall (F < 1, NS), perhaps because of the uniformly high levels of recall. The analysis did show a significant effect of prior category affect on ad claim recall (13 =.127; F = 9.18, p <.01; 1]2 =.03). Thus, Hypothesis 2d was supported by one of the two measures. Additional analyses supported category-based predictions (Fiske 1982; Pave1chak 1989). More positive prior category affect was associated with a greater percentage of positive thoughts (13 =.007; F = 38.32, p <.001; 1]2 =.12) and a lower percentage of negative thoughts (13 = -.007; F = 33.02, p <.001; 1]2 =.10). More positive prior category affect was also associated with higher Aad (13 =.047; F = 60.39, p <.001; 1]2 =.17) and Ab «(3 =.022; F = 32.63, p <.001; TJ2 =.10). The evidence that prior category affect influenced processing of typical ads was strongly supported in the multivariate analysis, and the univariate tests indicated the specific nature of the relationships. These results are summarized in Part II of Appendix B. As expected, affective responses and evaluations support that typical ads are evaluated by category-based methods (Pave1chak 1989). However, as affect increases there is a strong tendency for subjects to process typical ads more extensively. Processing Goals. Hypothesis 3 proposed that subjects given brand (vs. nonbrand) processing goals would process typical ads more extensively. The multivariate analysis was marginally significant for the five measures. The univariate results for those measures are reported below.

10 96 Subjects with brand goals watched typical ads marginally longer than did those with non brand goals (brand = 17.77, nonbrand = 17.08; F = 2.68, p <.10; 1']2 =.01), directionally supporting Hypothesis 3c. For brand name recall, the hypothesis received directional support but failed to reach traditional levels of significance (brand =.974, nonbrand =.952; F = 2.18, p <.15; 1']2 =.01). Subjects with brand goals also recalled the ad claims marginally better (brand = 6.55, nonbrand = 5.78; F = 2.99, p <.10; 1']2 =.01), directionally supporting Hypothesis 3d. There was no significant difference in terms of the number of cognitive responses or the percentage of those comments that referenced the category (F < 1, NS). Hypotheses 3a and 3b were not supported. Additional analyses indicated that brand goals were associated with a greater percentage of positive thoughts (brand = 50.49, nonbrand = 45.31; F = 5.10, p <.05; 1']2 =.02) and a lower percentage of negative thoughts (brand = 43.27, nonbrand = 48.57; F = 4.67, P <.05; 1']2 =.02). Goals, as expected, also significantly influenced the percentage of ad-related (brand-related) thoughts (brand = [20.57], nonbrand = [15.11]; F = 5.74, p <.01; 1']2 =.02). Goals had no significant effects (F < 1, NS) on Aad or A b The proposition that processing goals differentiate impression formation was marginally supported for the set of dependent measures, and the univariate tests indicate the specific nature of those relationships. These relationships are summarized in Part III of Appendix B. Effect sizes confirm small tendencies for subjects with brand goals to better remember brand names, ad claims, and to watch typical ads longer than those with nonbrand goals. Together the analyses provide only limited evidence that ad and brand processing goals differentially influence the intensity of processing for typical ads. DISCUSSION Summary of the Main Findings Subjects' processing goals were either to evaluate how good the advertised brands were (brand goal) or to evaluate how entertaining the ads were (nonbrand goal) as they viewed both typical and atypical ads from three different product categories. The multivariate findings confirm that (1) ad-related impression formation is less extensive when ads are typical, and more extensive when they are atypical, (2) typical ads are processed more extensively by subjects as prior ad category affect increases, and (3) typical ads are processed marginally more extensively by subjects with brand evaluation goals. Atypicality results are significant according to both statistical and effect size criteria. Simple main effects related to prior category affect and processing goals illustrate medium and small (as defined by Cohen [1977]) shifts toward more extensive ad processing of typical ads, respectively. JOURNAL OF CONSUMER RESEARCH The results suggest several interesting theoretical and practical implications. Theoretically, this work supports previous work applying Fiske's (1982) schema-triggered affect model in consumer behavior. This study shows television advertisements are processed in more detail when they are cosmetically atypical of ads from the product category. Thus, this study introduces ad typicality as an additional cue that motivates ad processing up to analytical levels (MacInnis et al. 1991). In addition, the results imply that Fiske's model extends to categories represented by either exemplars, as ad schemas are organized (Goodstein et al. 1992), or by prototypes, as is the case for brand schemas (e.g., Keller and Aaker 1992). This study extends prior research by showing that category-based predictions are moderated by the extremity of subjects' prior ad category affect when ads are typical. In keeping with earlier studies, prior category affect directly influences subsequent evaluations for typical ads (e.g., Pavelchak 1989), and successful categorization under all conditions leads to positive evaluations (Meyers-Levy and Tybout 1989). In addition, the proposition that positive prior category affect motivates processing (Hewstone 1989) was tested and supported. Prior category affect had a greater influence on processing when associated with typical ads than with atypical ads. This suggests that cognitive motivation to process ad information was dominant when the ads were atypical, while subjects' prior category affect motivated additional, nonevaluative processing when ads were typical. Therefore, schema affect may have a greater influence on processing than previously conceptualized in social psychology (e.g., Fiske 1982) and consumer research (e.g., Ozanne et al. 1992; Sujan 1985). In fact, increases in prior category affect lead to more extensive processing for both typical and atypical ads, although the effect is significantly more pronounced for typical ads. The results also reflect that category-based predictions might be related to one's processing goals, although the evidence was limited. The marginally significant MANCOV A for simple main effects suggests that the effects of processing goals on processing intensity may be qualified by how typical an ad is. For instance, the ads described in Keller's (1987, 1991) work appear to fit consumers' expectations for ads from the product categories tested. However, in the current study there were no simple main effects of goals on extent of processing when ads were atypical. Directly replicating Keller's work using atypical ads may indicate the pervasiveness of the effects found in these studies. Overall, the results support that unique ads are watched longer and processed in more detail than are more typical exemplars. Although advertisers have long sought differentiation, this approach should be adopted with care. The findings imply that being unique does not equate to being more well liked and suggests that caution should be used in determining how distinctive

11 CATEGORY-BASED EXTENSIONS IN ADVERTISING an ad should be. This conclusion, however, does not incorporate a discussion of degrees of atypicality. Some evidence shows that evaluations are most positive when stimuli are moderately incongruent with an evoked category (Meyers-Levy and Tybout 1989). Therefore, the relationship between congruity and subsequent attitudes might be described by an inverted U-shaped curve. It is also possible that extreme incongruity can sometimes curtail processing (Ozanne et al. 1992; Stayman et al. 1992). The moderating effects of prior category affect and, to a lesser extent, processing goals also have practical relevance. When given brand evaluation goals, subjects watch typical ads somewhat longer and remember slightly more ad claims. This suggests that advertisers can include more information in typical ads without worrying about how this additional information will affect consumers' evaluations, since these judgments are category based. This information may be processed and remembered by those in the market but will not affect those viewers that are watching the ad to be entertained. Similarly, as prior category affect towards an ad increases, subjects watch typical ads significantly longer and better remember ad claims. This suggests that one way of communicating new product claims and solidifying positive evaluations is to include additional brand information in typical ads from positively evaluated categories. Limitations and Future Research Directions This study illustrates the conditions under which ad typicality, schema affect, and individual processing goals motivate more extensive processing. This study, however, was conducted in a classroom setting necessitating a trade-off between experimental control and external validity. Therefore, retesting the hypotheses under more naturalistic viewing conditions, perhaps those that include programming along with the ads, is suggested. If the goal of an ad is to change attitudes through exposure, then the suggestion is to be unique. The degree of atypicality, however, must be carefully decided, as consumers may assimilate ad information that is only slightly discrepant from category expectations. They are more likely to contrast or reject information that is too incongruent with these beliefs (Sujan and Bettman 1989). This discussion relates to both substantive and cosmetic typicality, although substantive differences may not be noticed if ads are not initially being processed beyond category-based levels. This appears to be an interesting issue for future research. Evaluations formed through systematic processes may be more stable than those formed through heuristics (Petty and Cacioppo 1986). Ad and brand evaluations formed for atypical ads may, therefore, be less susceptible to change. Understanding the durability of evaluations in the face of time and future communications seems to warrant further investigation. Finally, it is important that future investigations of consumers' ad processing consider category-based approaches. As advertising expenditures continue to rise, the issue of how consumers process ads and the factors that may discourage them from mentally "zapping" a commercial become crucial (Olney et al. 1991). This article supports that category-based reactions occur rapidly and are essentially perceptual. Therefore, if not drawn in immediately either by an ad's unique qualities or by a positive category evaluation, consumers may form schema-triggered impressions and ignore the rest of an advertiser's message. Phase 1 Questions APPENDIX A "The following statements pertain to television ads for (product type). Think about your general impressions of television ads for (product type), not your impression of a specific television ad for any particular (product type), and indicate how much you agree with each of the following statements" (1 = strongly disagree; 7 = strongly agree). 1. When it comes to television ads for (product type), I know exactly what an ad will be like before I see it. 2. I like television ads for (product type) very much.a 3. Television ads for (product type) are all alike. 4. It's very easy to dislike television ads for (product type).a,b 5. When I notice that a television ad is for (product type), I am quick to shift my attention away from the ad.a,b 6. My opinion about television ads for (product type) is very positive.a 7. Once you've seen one television ad for (product type), you've seen them all. 8. Television ads for (product type) are very bad.a,b 9. When it comes to television ads for (product type), I have no idea of what to expect. 10. Television ads for (product type) are very good.a 11. I think that there is a lot of variation among television ads for (product type). 12. Television ads for (product type) are among my favorite television ads.a 13. My attitude about television ads for (product type) is very negative.a,b 14. Now, please use the space below to describe what you think television ads for (product type) are like. (Use the back of the page if additional space is needed.) For statements followed by superscript a, factor loading>.5; alpha =.93. Statements followed by superscript b were reverse scored to compute schema affect scores. 97