Measuring Emotional Responses to Advertising

ABSTRACT - Traditional measures of cognitive response, attitude toward the ad, and attitude toward the brand fail to include adequate emotional measures of consumer response. Emotional responses to ads can be assessed by coding verbal protocols for positive and negative affect. Also, the emotional component of attitude toward the ad (ATTA) and toward the brand (ATTB) can be measured through "emotional" attitude scales. The current study shows that emotional measures of cognitive response, ATTA, and ATTB are needed to evaluate the effects of emotional advertising.

Citation:

Ronald P. Hill and Michael B. Mazis (1986) ,"Measuring Emotional Responses to Advertising", in NA - Advances in Consumer Research Volume 13, eds. Richard J. Lutz, Provo, UT : Association for Consumer Research, Pages: 164-169.

Advances in Consumer Research Volume 13, 1986      Pages 164-169

MEASURING EMOTIONAL RESPONSES TO ADVERTISING

Ronald P. Hill, The American University

Michael B. Mazis, The American University

ABSTRACT -

Traditional measures of cognitive response, attitude toward the ad, and attitude toward the brand fail to include adequate emotional measures of consumer response. Emotional responses to ads can be assessed by coding verbal protocols for positive and negative affect. Also, the emotional component of attitude toward the ad (ATT_") and toward the brand (ATT_B) can be measured through "emotional" attitude scales. The current study shows that emotional measures of cognitive response, ATT_", and ATT_B are needed to evaluate the effects of emotional advertising.

INTRODUCTION

Until recently, consumer behavior researchers have relied on cognitive information processing models of consumer decision making and have neglected the emotional side of human behavior (Holbrook and Hirschman 1982, Rook and Levy 1983, Zajonc and Markus 1982). This "man-as-computer" perspective regards consumer behavior as a series of rational decisions through which the buyer processes attribute information to make a purchase decision from available alternatives (Holbrook 1984).

Although cognitively-based models have been useful in the prediction of consumer behavior, they have been unable to completely explain the processes underlying advertising effects. This may be due, in part, to the failure to include "emotional" variables in these models. If emotion is considered at all, it is usually operationalized as a simple affect measure that deals with only one emotional dimension (e.g. like-dislike). This perspective ignores the multidimensional nature of emotion (i.e., love, hate, anger or joy).

The purpose of this paper is to identify and to discuss the role of emotion in the sequence of steps that intervene between exposure to an advertising message and eventual purchase of a product. The study presented is an attempt to improve understanding of the measurement of emotional advertising effects.

BACKGROUND

The Traditional Approach

The traditional model of consumer decision making has its roots in Plato's original distinction among cognition, affect and behavior (Holbrook 1984). This paradigm was first introduced in the marketing literature as the hierarchy-of-effects concept (Lavidge and Steiner 1961). This perspective, consisting of a causal flow from cognition (C) to affect (A) to behavior (B), dominated subsequent attitude research.

Recent research has suggested that the C-A-B sequence of decision stages may not always take place. For instance, Zajonc and Markus (1982) have conducted extensive research which concludes that affective judgements may be independent of, and precede in time, cognitive operations.

Changes in the traditional C-A-B approach are also based on evidence which suggests that a consumer's level of involvement in a particular advertising message may influence his or her processing strategy (Krugman 1965, Rothchild 1979, Vaughn 1980).

Petty, Cacioppo and Schumann (1983) have expanded the level of involvement approach through the development and testing of their "two routes" theory. Following this theory, Shimp (1981) has suggested that most ads use one of two possible approaches that he terms "ATT_B" and "ATT_"." Under the ATT_B (attitude toward the brand) approach, purchase behavior is influenced by developing favorable consumer attitudes toward the advertised brand. This is accomplished by structuring ads to influence consumers' beliefs and evaluations regarding the favorable consequences of purchasing a particular brand. This approach is consistent with the high involvement/central route perspective (Petty Cacioppo and Schumann 1983).

Under the ATT_" (attitude toward the ad) approach, a message is not directed at specific product attributes or benefits. Instead, the purpose of the advertisement is to create a favorable attitude toward the ad by leaving the viewer/listener/reader in a positive emotional state after processing the ad. The assumption underlying this concept is that consumers are hedonistically motivated by the desire to feel good. This approach is consistent with the low involvement/peripheral route perspective (Petty, Cacioppo and Schumann 1983).

The Attitude Toward the Ad Perspective

The ATT_" perspective described by Shimp (1981) has led to a recent emphasis in the marketing literature on studies involving attitude toward the ad (Holbrook 1978, Lutz, Mackenzie and Belch 1983, Mackenzie and Lutz 1983, Mitchell and Olson 1981). Typically, this construct is treated as an intervening variable that mediates the effects of the advertising message on brand attitudes and preferences (Edell and Burke 1984, Holbrook and O'Shaughnessy 1984). Further, ATT_" is believed to consist of two distinct components, one cognitive and the other emotional (Shimp 1981). The former dimension is determined by consumers' conscious response to the advertising execution. For instance, consumers may prefer certain ads due to a credible source or a convincing product demonstration. The latter dimension is composed of consumers' emotional responses to advertisements. These responses may include feelings of love, joy, patriotism and nostalgia.

Measurement of ATT_"

One of the most common methods used to measure consumers' reactions to advertisements is through verbal protocols. Although interest in ATT_" has increased, the cognitive response categories used to code verbal protocols have remained similar to those developed by Wright (1973). These categories include support arguments, counterarguments and source derogations. In recent years, researchers have added categories such as simple affirmations and disaffirmations (Berber 1975), neutral and irrelevant thoughts (Cacioppo and Petty 1979), and source bolstering and repetition related thoughts (Belch and Lutz 1982). Further, Lutz, Mackenzie and Belch (1983) divided responses according to whether they were evaluatively positive or negative.

Consumer responses also may include emotional reactions to the moots created by the ads. For example, Golden and Johnson (1983) have conducted research suggesting that factual and emotional ads produce differential communication responses. Therefore, the most appropriate coding scheme for cognitive responses should include categories that capture consumers' reactions to product information, ad execution style, and the emotions elicited by the ad.

Besides cognitive responses, bipolar scales have been used to measure ATT_". For example, Mitchell and Olson (1981) measured attitude toward the ad through four scales (good-bad; like-dislike; irritating-not irritating; and interesting-uninteresting). The mean of these four evaluative measures was interPreted as ATT_".

Although this approach provides a good overall measure of ATT_", it may not capture the multidimensional nature of this construct. Which, if any, of these scales measures emotional response? One investigation did attempt to estimate consumers' emotional reactions to ads with the scale "positive-negative" (Moore and Hutchinson 1983). It is doubtful that this one scale is capable of capturing the richness of possible emotional responses (i.e., happiness, sadness, love and joy).

In an attempt to break from this tradition, Gresham and Shimp (;985) used seven affective items to measure their emotional reactions. Although their results were somewhat disappointing, they did attempt to partition potential emotional reactions into soothing, warm-hearted, sorry, sad, affectionate, happy and elated categories. Therefore, consistent with the discussion involving cognitive responses, it is recommended that researchers using bipolar scales to measure ATT_" select scales that capture the emotional responses as well as the "utilitarian" response.

Measurement of ATT_B

Measures of ATT_B are even less likely to contain an emotional component. For example, Mitchell and Olson (1981) measure ATT_B through mean values on four five-point scales (e.R. Rood-bad and dislike very much-like very much).

The use of these procedures is somewhat peculiar given the widely discussed classical conditioning hypothesis. This position conjectures that ATT_" may directly influence ATT_B through classical conditioning (Edell and Burke 1984). Under this hypothesis, ATT_"'s direct effect on ATT_B occurs since emotional reactions elicited by the ad get transferred to the brand. Thus, the emotional element of the ad acts as the unconditioned stimulus and the brand becomes the conditioned stimulus, eventually generating the same affective response as the ad. Given this perspective, it is essential that measures of ATT_B include both cognitive and affective components that capture the full range of meanings of these variables.

OBJECTIVES

The current study is designed to determine whether affective measures that assess emotional responses to advertisements are needed to measure the impact of emotional advertising. In the case of advertising that is primarily factual, traditional cognitive response measuresCsupport argument, counterargument, source bolstering and source derogation--should be sufficient to assess consumer responses to advertising. Emotional measures--positive affect and negative affect are unlikely to assist in the measurement of factual ad effects. On the other hand, emotional measures of cognitive response are likely to be important in examining the impact of emotional ads.

In addition, traditional bipolar evaluative adjective scales -- good-bad; like-dislike; irritating-not irritating; interesting-uninteresting -- are unlikely to discriminate between the effects of factual and emotional ads. It is predicted that these ATT_" measures are inadequate to capture the impact of emotional ads. The "sensual" factor (Leavitt 1970) consisting of adjectives that capture the emotional mood of the television commercial (lovely, beautiful, gentle, serene, tender and sensitive) should be more effective in measuring emotional ad effects.

Finally, traditional ATT_B measures (e.g.,good-bad and like-dislike) should be adequate for determining the impact of factual advertising. However, to discriminate between the effects of factual and emotional ads, affective ATT_B measures are needed. Bipolar adjective scales that measure consumer emotion (e.g.> pleasant-unpleasant; sociable-unsociable; nice-awful) regarding individual brands are likely to be more effective than traditional measures when emotional ads are being tested.

METHOD

The study was conducted at a private university in the eastern United States. Student subjects voluntarily participated in the experiment and received additional course credit for their participation. Subjects were randomly assigned to the two experimental treatments--exposure to emotional or factual advertising. Approximately 25 subjects participated in each of four experimental sessions. Overall, 48 and 51 subjects were in the emotional and factual advertising treatments, respectively.

Subjects were led to believe that the study was designed to examine the impact of television programming on their attitudes and beliefs. This guise was successful since all subjects stated that the program was the central focus of this investigation in response to a study-purpose question placed at the end of the study. All subjects watched three separate segments of a movie that had not yet appeared on network television. The movie was interrupted for three commercial breaks to simulate actual exposure to a television program.

All subjects were exposed to one television ad at each commercial break. Subjects viewed commercials for a bank, telephone service and a camera. Commercials were matched so that emotional and factual versions were the same length (either 30- or 60-seconds). The ads for the telephone service and camera were for the same brands while the bank ads contained different organizations. However, the use of different firms in the bank ads was not expected to impact on the results since both banks were unknown to subjects. A panel of judges familiar with advertising campaigns unanimously concluded that the advertisements used were either predominantly factual or emotional in execution.

After viewing the advertisement during the commercial break, subjects were asked to generate verbal response protocols by providing any and all response to the ad they had just seen. They were given four minutes to complete this task. After the television program was concluded (including commercials), respondents were asked to provide written protocols in response to the television program they had just seen (distractor task).

Written protocols were coded independently by two judges who were given operational definitions of the response categories and were trained in the application of the definitions. In cases where there was no agreement between the judges (approximately 10% of all responses), the researchers served to make the coding decisions.

The cognitive response categories were support argument, counterargument and source derogation (Wright 1973). In addition, a source bolstering category was also used to provide the positive counterpart of source derogation (Belch 1981). Two other cognitive response categories positive and negative affect--were used in order to capture respondents' emotional responses to the messages (Batra 1984). One example of a positive affect response is "I felt good when I saw this ad". On the other hand, a negative affect response might be "This ad made me angry". A series of 45 adjectives were taken from Leavitt's (1970) factor analytic study that identified eight factors--amusing, authoritative, dislike, energetic, familiar, novel, personal relevance and sensual--to rate television commercials. Each factor consisted of six adjectives having the highest loadings on that factor with the exception of the "familiar" factor that contained only three adjectives. Respondents were asked to judge on a five point-scale whether each of the adjectives described the commercial "extremely well" (5) to "not very well at all" (1). Scores for adjectives were summed to develop eight ad rating variables (factors).

Following the advertising ratings for a given commercial, respondents were asked to provide their overall evaluation (ATT_") of the advertisements on four bipolar adjective scales (good-bad ; like-dislike; irritating-not irritating; interesting-uninteresting). These are the four attitude scales commonly used to measure ATT_" (Gardner 1983; Mitchell and Olson 1977). Scores on the four attitude scale,were summed to develop a single overall ad evaluation measure.

After the three commercials were shown and were evaluated, respondents were asked to provide their attitudes toward specific brands of cameras, telephone services and banks. ATT_" measures were taken on four sets of bipolar adjective scales--overall evaluation (good-bad; like-dislike; positive-negative); emotional (pleasant-unpleasant; sociable-unsociable; nice-awful); savory (sensitive-insensitive; interesting-boring; tasteful-tasteless); authoritative (useful-useless; important-unimportant; intelligent-unintelligent). These attitude scales were taken from analytic work of Osgood, Tannenbaum & Suci (1957) and Batra (1984).

RESULTS

Cognitive Response Measures

The data in Table l indicate that arguments advanced, message factors and affect measures were important variables in discriminating between the effects of emotional and factual commercials. For the bank advertisements, there were few support or counterarguments for either the emotional or factual advertisements. However, the factual ad generated significantly more source bolstering statements, on the average, than did the emotional ad (2.04 vs. .92). The factual ad used animation and apparently this technique was liked by respondents. The emotional bank at generated more positive affect responses than did the factual ad (.54 vs. .02).

TABLE 1

COGNITIVE RESPONSE MEASURES EMOTIONAL VS. FACTUAL ADVERTISEMENTS

In the case of the two telephone ads, the factual ad produced more support arguments, on the average, than the emotional ad (.63 vs. .29). The mean number of counterarguments generated for the factual ad was also higher than for the emotional ad (.27 vs. .04). On the other hand, the mean number of source bolstering responses was higher for the emotional at (1.23 vs. .67), but the mean number of source derogations was higher for the factual ad (.96 vs. .15). The emotional telephone ad generated significantly more positive affect responses than the factual ad (.90 vs. .00). Neither message produced any significant volume of negative affect statements.

Finally, the factual camera commercial produced significantly more counterarguments, on the average, than did the emotional commercial (.51 vs. .02). The factual ad also generated significantly more source bolstering responses than did the emotional camera ad (1.49 vs. .71). The mean number of positive and negative affect responses generated was greater for the emotional ad than for the factual ad (.40 vs. .00: .33 vs. .02).

These findings suggest that when there are differences in the number of support arguments or counterarguments generated that factual ads will produce a higher number of these responses than will emotional ads. For the telephone ads, the factual ad resulted in significantly more support and counterarguments than the emotional ad. This finding was also observed for the camera ads; the mean number of counterarguments was higher for the factual ad than for the emotional ad. In no case did emotional ads produce a higher level of support or counterarguments than did the factual ads.

As expected, there was no consistent pattern of differences in source bolstering or source derogation responses produced by emotional and factual commercials. In one case (telephone ad), the emotional ad produced more source bolstering responses; in three cases, the factual ads produced more source bolstering or source derogation responses. The particular execution used is likely to be responsible for source related responses. There is no inherent liking or disliking of emotional or factual executions.

When there were differences in the number of affective responses generated, emotional ads always produced higher mean levels than did factual ads. For all three advertising treatments, there were more positive affect statements when the emotional ad was aired in contrast to when the factual ad was aired. In one case (camera at), the emotional ad also resulted in a greater number of negative affect responses.

Table 2 shows the relative contribution of message arguments (support arguments-counterarguments), source statements (source bolsterings-source derogations) and affective responses (positive affect-negative affect) in predicting consumers' overall ad evaluations. For these three cognitive response measures, the number of negative responses was subtracted from the number of positive responses for each individual. The four ad evaluation scales (good--bad; like-dislike; irritating--not irritating; interesting--uninteresting) were s=ed up to produce an overall ad evaluation measure. Stepwise multiple regression analysis was employed by "forcing" the three independent variables in the following order: (l) message arguments (SA-SD); (2) source statements (SB-SD); and (3) affective response (PA-NA).

The stepwise multiple regression analysis indicates that affective responses (PA-NA) did not produce any significant amount of incremental explained variance for the three factual ads. In each case, the message arguments and source statements accounted for all of the variance explained in the overall ad evaluation measure used in the factual ads. For the emotional ads, however, affective responses accounted for a significant amount of incremental explained variation in ad evaluation for both the bank and telephone commercials. In both of these conditions, affective measures (PA-NA) had more explanatory power (highest simple correlation coefficients) than either the message argument or source statement variables.

Advertising Ratings

The data reveal that the overall evaluation measures (good- bad; like-dislike; irritating--not irritating; interesting-uninteresting) used in most ATT_" research did not distinguish between the impact of emotional and factual ads. Statistically significant differences between emotional and factual ads. Statistically significant differences between emotional and factual ads were observed in only one case (telephones).

TABLE 2

MULTIPLE REGRESSION AD EVALUATIONS WITH COGNITIVE RESPONSE MEASURES

The set of eight factors developed by Leavitt (1970) and Wells, Leavitt and McConville (1971) appear to better discriminate between the effects of emotional and factual ads than do the traditional evaluative measures. Three factors related to ad execution--the "energetic" factor (lively, exhilarated, vigorous, enthusiastic, energetic and excited), the "amusing" factor (merry, jolly, playful, joyful, amusing and humorous), and the "novel" factor (original, unique, imaginative, novel, ingenious, and creative)-vary significantly across emotional and factual ad treatments. In the case of the banks and cameras, the factual commercials received higher scores (more descriptive) OD these three factors; for the telephone ad the emotional ad received a higher score on the three execution factors.

As hypothesized, respondents rated the emotional ads as being higher on the sensual factor (lovely, beautiful, gentle, serene, tender and sensitive). For each of the three commercials, statistically significant differences were observed for the sensual factor (Table 3).

TABLE 3

ADVERTISING RATINGS: EMOTIONAL VS. COGNITIVE ADVERTISEMENTS

Brand Ratings

The data in Table 4 indicate that respondents tended to express a more positive attitude toward the brand under the emotional ad conditions as compared with the factual ad conditions (lower numbers in the table are more positive). These differences were particularly strong in the case of the factors that were hypothesized to distinguish between emotional and factual ads. In the case of the "savory" factor (sensitive-insensitive, interesting-boring, and tasteful-tasteless) and the "emotional" factor (pleasant-unpleasant, sociable-unsociable, and nice-awful), there were significant differences between factual and emotional treatment across all three commercials.

The overall brand evaluation factor (ATT_B) (good-bad, like-dislike, and positive-negative), which has been used in most studies employing an ATT_B measure, was slightly less useful; it discriminated between emotional and factual treatments for only two of three ads. The "utilitarian" factor (useful-useless, important-unimportant, and intelligent-unintelligent) was significant in the case of the telephone ad only.

Therefore, affective brand evaluation measures appear to be slightly more sensitive in discriminating between the effects of emotional and factual ads than are traditional evaluation measures.

TABLE 4

BRAND RATINGS: EMOTIONAL VS COGNITIVE ADVERTISEMENTS

DISCUSSION

This paper takes the position that "traditional" approaches to measuring three key dependent variables in advertising research--cognitive responses, ATT_" and ATT_B--are inadequate for assessing the impact of emotional advertising. Zielske (1982) previously reported that traditional day-after-recall measures "penalize" emotional ads since consumers are unlikely to play back specific ad elements in "feeling" ads. He recommends, therefore, that advertising researchers use recognition techniques, which are better able to detect the impact of emotional ads.

The current research extends Zielske's view to three other dependent variables used in advertising studies. Following the theoretical work of Batra (1984), affective cognitive responses were coded in addition to the traditional cognitive response categories--support arguments, counterarguments, source bolstering and derogations. The affective responses were useful in assessing the impact of emotional advertisements. Future researchers should consider using coding schemes that incorporate affective cognitive responses, as well as the traditional cognitive response measures.

This study also suggests that traditional ATT_" measures are inadequate for measuring the impact of emotional ads. The ad rating factors developed by Leavitt and Wells were more effective than the traditional evaluative measures for measuring the emotional ad effects. The "sensual" factor (lovely, beautiful, gentle, serene, tender and sensitive) appears to offer the most promise in future studies involving emotional advertising. Other ATT_" measures specifically focused on the affective component might be developed in subsequent research studies.

Finally, several previous researchers (Bagozzi 1982; Batra 1984; Burnkrant and Page, 1982) have attempted to isolate cognitive and affective components of brand attitudes. These efforts have met with only limited success. Generally, a positive "halo" effect has been found to operate. Respondents do not discriminate between cognitive and affective measures; their responses are strongly influenced by their overall attitude toward the brand. The current study found some differences between cognitive and affective components. However, even though the "savory" and "emotional" factors distinguished between emotional and factual ad effects, the overall evaluation measures "worked" reasonably well also. Therefore, additional research is needed to develop affective brand attitude measures.

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