Animation Effects in Online Banner Ads

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1 Animation Effects in Online Banner Ads Suzanne C. Beckmann & Torben Hansen, Copenhagen Business School Lene Matthiesen, Vizeum & Jakob Thorbech, TNS Gallup Abstract This study examines how consumers attitude towards a fictitious brand is formed after exposure to an online banner ad with varying degrees of animation effects. Using the Elaboration Likelihood Advertising Model as frame of reference an online experiment was designed in which 599 students participated. The results show a relationship between respondent s emotional responses and ad liking, with attitude towards the ad being a mediator variable. Ad liking also influenced brand image, with an impact on buying intention where brand preference works as mediator. The results also suggest an inverted U-shape relation between the level of animation and recall and recognition rates, thus cautioning against using too heavy animation in banner ads. Introduction Banner ads are one of the most common forms of marketing communication on the Internet, and usually aim at enticing consumers to click through for making a purchase. But can banner ads be used for other purposes as well? We were interested in investigating (1) whether online banner ads can influence consumers attitude formation towards a new product and (2) whether various degrees of animation effects make a difference in this process of attitude formation. This interest is grounded in divergent findings of previous research. Heo and Sundar (2001) found that animated banner ads were not better recalled than static ones, and that high involvement products were better recalled than low involvement products. Bayles (2002) also found that animation does not have a significant effect on unaided and aided advertising recall. Yoo and Kim (2005) found an inverted U-shape relation between the degree of animation and aided recall with a negative effect of too much animation. And finally the study by Shrestha (2006) showed that pop-up and floating had a positive effect on aided and unaided recall, while animation did not have an effect. Hansen s (1997) Elaboration Likelihood Advertising Model ELAM was chosen as the frame of reference for our study. This model posits that central information processing is product and brand related, thus leading to brand awareness influencing product/brand image, product/brand preference and ultimately buying intention. The peripheral route is suggested to be execution related, leading to emotional responses and attitudes towards the ad that together influence ad liking, which in turn determines buying intention (see Figure 1). This model thus takes into account critical voices concerning Petty and Cacioppo s (1983) Elaboration Likelihood Model, which disregards emotions (Morris, Chongmoo & Singh, 2005) and situational variables (Cook & Steel, 2004). Cho (1999) also argues that the ELM is unsuited for assessing online advertising effects where consumers are exposed to a message and can take action right away contrary to traditional effect hierarchy models that assume long-term effects. 1400

2 The Study An experimental design was chosen to test a set of hypotheses derived from the ELAM and based on previous studies in this area: H1: The central information-processing route has a positive effect on brand awareness. H2a: The peripheral information-processing route has a positive effect on attitude towards the ad. H2b: The peripheral information-processing route has a positive effect on emotional responses. H3: Emotional responses have a positive effect on ad liking. H4: Attitude towards the ad has a positive effect on ad liking. H5: Brand awareness has a positive effect on brand image. H6: Brand image has a positive effect on brand preference. H7a: Ad liking has a positive effect on brand preference. H7b: Ad liking has a positive effect on buying intention. H8: Brand preference has a positive effect on buying intention. Figure 1: ELAM model and hypotheses Additionally, the following hypotheses were formulated to assess the effect of animation: H9: There is an inverted U-shaped relation between animation and awareness of the banner ad. H10a: There is a negative relationship between degree of animation and central informationprocessing. H10b: There is a positive relationship between degree of animation and peripheral informationprocessing. Finally the following hypotheses refer to potential effects of animation: H11: There is a negative relationship between degree of animation and brand awareness. 1401

3 H12: There is a negative relationship between a high degree of animation and attitude towards the ad. H13: There is a negative relationship between a high degree of animation and emotional responses. Study design In order to avoid any influences of existing knowledge and attitudes, it was decided to develop a fictitious Internet portal with three different start pages that contained both articles and two banner ads each. Since respondents were university students, articles from various print media were selected based on their relevance for this target group. The articles topics and content were the same for all three pages. The product to be advertised for was chosen based on the Rossiter- Percy Grid (Rossiter & Percy, 1997) and belongs to the transformation/low involvement category: A chocolate bar, where traditional sugar is substituted by dextrose for fast energy supply. The chocolate bar, named Boost, is not available on the market and the banner ad was designed specifically for this study. Advertisements on the webpage for other categories were also fictitious and developed to reflect typical web-ads: a job portal, Internet stores offering books, cosmetics and sports clothing, and a web hotel. Data collection The study was designed as a between-subjects visual lab experiment, i.e., respondents were invited to computer labs where they were shown the three web pages, which varied according to animation levels (low, moderate, and high, respectively). It was strived for a true experimental design (Malhotra & Birks, 2003) with one post test. Respondents were informed that they would see 3 homepages of a new portal called Avantgarde with each being shown for 45 seconds. The test ad was placed on the second homepage with three different animation speeds, randomly assigned to each respondent. After this, a questionnaire had to be answered that took 10 to 15 minutes to answer. The questionnaire started by measuring unaided recall of the chocolate bar ad and then asked for emotional responses to the ad using the SAM icons (Self-Assessment Manikin; Lang 1985). Open questions were used to assess whether respondents had used the central or peripheral information-processing route. Five items (6-point scale) measured attitudes, while image was assessed with 11 semantic differential items. Four other well-known chocolate bars were used here for comparison. Finally, ad liking, brand preference and buying intention were assessed. Respondents were recruited at three different universities in the Copenhagen metropolitan area. 599 students participated: 53% female and 47% male, 18 to 38 years old with 75% in the age bracket of 22 to 27 years old. Distribution across the three animation levels was as follows: 37.3% low, 30.1% moderate and 32.6% high animation. 50% of the respondents recalled the fictitious ad for the chocolate bar and thus answered the whole questionnaire (n=299). Results Various methods of analysis were used to test the set of hypotheses. Due to space limitations, results can only be shown summarily in Table 1. Note that rejection versus confirmation of the various hypotheses is based on standard statistical significance values. Moreover, a number of 1402

4 other analyses that reflected the complexity of the data can unfortunately not be presented here. We will, however, in the following briefly describe the main findings. Hypotheses 3 to 8, which cover the core of the ELAM model, were analysed using LISREL. Following Verdù-Jover et al. (2004), an exploratory factor analysis was conducted first because the relationships between the latent variables in the model have so far not been tested empirically to a sufficient extent. The findings showed that the large majority of items measured the intended construct, the exception being brand awareness for the chocolate bar, most certainly because Boost is an unknown product. Hypothesis 5 was therefore not tested nor was hypothesis 11, which also concerned brand awareness. With regard to hypotheses 9 and 10 it should be noted that the expected inverted U-shaped relationship between animation degree and ad recall was found, but failed statistical significance - both for unaided and aided recall. In the case of aided recall the p-value was 0,104. Table 1: Summary of results for the 13 hypotheses Hypotheses Test result Analysis method H1: The central information-processing route has a positive effect on brand awareness rejected cross tabulation, H2a: The peripheral information-processing route has a confirmed MANOVA positive effect on attitude towards the ad H2b: The peripheral information-processing route has a rejected MANOVA positive effect on emotional responses H3: Emotional responses have a positive effect on ad rejected LISREL model liking H4: Attitude towards the ad has a positive effect on ad confirmed LISREL model liking H6: Brand image has a positive effect on brand confirmed LISREL model preference H7a: Ad liking has a positive effect on brand preference confirmed LISREL model H7b: Ad liking has a positive effect on buying intention rejected LISREL model H8: Brand preference has a positive effect on buying confirmed LISREL model intention H9: There is an inverted U-shaped relation between rejected animation and ad awareness H10a: There is a negative relationship between degree rejected of animation and central information-processing H10b: There is a positive relationship between degree of rejected animation and peripheral information-processing H13: There is a negative relationship between a high degree of animation and emotional responses rejected MANOVA Additionally, we conducted a correspondence analysis to assess whether the Boost ad successfully communicated the intended image. The results showed that the product was closely associated with attributes such as sporty, youthful and giving energy as well as 1403

5 trendsetter, i.e., exactly reflecting intentions. This result is especially interesting, since it indicates that online banner ads can actually create an image for low involvement products: respondents were only once exposed to the ad. The LISREL analysis then also revealed a significant positive relationship between ad liking and image. Conclusions The findings showed that those respondents who processed information peripherally formed a positive attitude towards the ad in concordance with the ELAM model. No significant relationship was found between the central route and brand awareness, thus questioning this part of the ELAM model. The results also suggest that the ELAM model has to be revised, at least in the context of online banner ads. An indirect relationship was found between emotional response and ad liking, with attitude towards the ad as mediating variable. This finding is in line with newer conceptualizations of the role of emotions (e.g., Bagozzi et al., 1999; LeDoux, 1996). The findings also showed that ad liking influences image, though with a stronger effect on buying intentions with brand preference as mediating variable. Taking these findings together, our study indicates that the distinction between central and peripheral processes probably is artificial and arbitrary. This is also supported by the result that the degree of animation did not have any effect on central and peripheral processes. However, the expected U-shape was found in relation to aided and unaided ad recall (albeit statistically non significant). Finally, and quite importantly, the result that online banner ads can actually create a brand image for low involvement products contradicts the findings of Johansen and Herlin (2001) and Cho (1999, who argues that banner ads should only be used for purchase stimulating messages. However, we acknowledge in this context that the distinction between high and low involvement products is a highly debated issue. Yet the central result that well executed banner ads can create the desired brand image is not contestable. One important implication of this study is therefore a revised model for pre-testing banner ads. The other important implication is that animation effects should be used carefully and executed in a way that supports the story line of the advertisement rather than substituting it. Moreover, since the results suggest that positive emotional responses toward banner ads positively affect attitude, which in turn affect ad liking, the design of the banner ad becomes essential. Last but not least we would like to mention a few limitations. First, respondents were mainly students from a business school who are professionally probably more interested in advertising than other target groups, which might decrease external validity. Secondly, and related to the before mentioned limitation, we have followed precisely the ELAM model, which, inter alia, means that we have not assessed attitude towards advertising in general. We suggest that this variable should be included in further research. Thirdly, the disadvantage of a lab experiment is that respondents are passively confronted with the same stimulus this secures high internal validity but at the same time threatens external validity. 1404

6 References Bagozzi, R.P., Gopinath, M., Nyer, P.U., The role of emotions in marketing. Journal of the Academy of Marketing Science 27 (2), Bayles, M.E., Designing online banner advertisement: Should we animate? Available from Cho, C.H., How advertising works on the WWW: modified elaboration likelihood model. Journal of Current Issues and Research in Advertising 21 (1), Cook, A.J., Steel, G.D., The taking of a position: A reinterpretation of the Elaboration Likelihood Model. Journal for the Theory of Social Behaviour 34 (4), Hansen, F., Quantifying creative contributions: Advertising pre-testing s new generation. ESOMAR Conference Proceedings, Edinburgh/UK. Heo, N., Sundar, S.S., Memory for Web advertisements: Exploring effects of animation, position,and product involvement. Paper presented to the Mass Communication Division at the 51 st Annual conference of the International Communication Association, Washington D.C. Johansen, T., Herlin, K., Online communications - banner advertising - more than clicks. Admap, WARC. Lang, P.J., The Cognitive Psychophysiology of Emotion: Anxiety and the anxiety disorders, Lawrence Erlbaum, Hillsdale, NJ. LeDoux, J., The Emotional Brain, Simon & Schuster, New York. Malhotra, N.K., Birks, D.F., Marketing Research: An applied approach, 3 rd edn., Prentice Hall. Morris, J.D., Chongmoo, W., Singh, A.J., Elaboration Likelihood Model: A missing intrinsic emotional implication. Journal of Targeting, Measurement and Analysis for Marketing 14, Petty, R.E., Cacioppo, J.T., Central and Peripheral routes to persuasion: Application to advertising. In: Percy, L., Woodside, A. (Eds.), Advertising and Consumer Psychology, Lexington Books, Lexington. MA, pp Rossiter, J.R., Percy, L., Advertising communications and promotion management, 2 nd edn., McGraw-Hill, New York. Shrestha, S., Does the intrusiveness of an online advertisement influence user recall and recognition? Available from

7 Verdù-Jover, A.J., Lloréns-Montes, F.J., García-Morales, V.J., The concept of fit in services flexibility research: An empirical approach. International Journal of Service Industry Management 15 (5), Yoo, C.Y., Kim, K., Processing of animation in online banner advertising: The role of cognitive and emotional responses. Journal of Interactive Marketing 19 (4)

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