- Email: [email protected]
The impacts of banner location, banner content and navigation style on banner recognition
Computers in Human Behavior Computers in Human Behavior 24 (2008) 535–543 www.elsevier.com/locate/comphumbeh
The impacts of banner location, banner content and navigation style on banner recognition Fethi Calisir a
a,*
, Demet Karaali
b,1
Industrial Engineering Department, Faculty of Management, Istanbul Technical University, 80680 Macka-Istanbul, Turkey b Mercedes-Benz Turk A.S. Marketing Center, 34500 Bahcesehir-Istanbul, Turkey Available online 5 April 2007
Abstract This study is an attempt to examine factors that might impact banner recognition. These factors include banner location, banner content and navigation style. Via an experimental design conducted on a sample of 90 students, we manipulate these factors over several levels. Our key finding is that banner recognition is affected by the interaction of banner content and navigation style. In particular, as far as aimless browsing participants were concerned, they recognized the banner ad with a URL address significantly better than the one with some service information as well as the URL address. However, for goal-directed search participants, there was no significant difference among the three banner content types. The results also indicated that goal-directed search participants had higher recognition scores than aimless browsing subjects only when the banner ad with some service information and URL address was used. Managerial implications of these results are discussed and future research avenues are proposed. 2007 Elsevier Ltd. All rights reserved. Keywords: Banner recognition; Navigation style; Banner location; Banner content
1. Introduction It is estimated that over 1 billion people were using the Internet worldwide in 2005, up from only 45 million in 1995 and 414 million in 2000. Moreover, this number is expected to *
1
Corresponding author. Tel.: +90 212 240 7260; fax: +90 532 661 53 12. E-mail addresses: [email protected] (F. Calisir), [email protected] (D. Karaali). Tel.: +90 212 858 0990; fax: +90 212 858 0980.
0747-5632/$ - see front matter 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.chb.2007.02.019
536
F. Calisir, D. Karaali / Computers in Human Behavior 24 (2008) 535–543
reach the 2 billion Internet users target in 2011 (Computer Industry Almanac, 2006). With the continuing growth in the number of Internet users, advertising expenditure on the Internet is also going up exponentially. This is obvious in the fact that Internet advertising revenues for 2005 are projected to surpass $12.5 billion, a 30% increase over the prior revenue record of $9.6 billion in 2004. In addition, Internet advertising accounted for nearly 5% of total U.S. advertising revenues in 2005, up from less than 4% reported in 2004. Internet advertising surpassed advertising for business magazines by more than 50% in 2005, and almost matches total consumer magazine advertising. Adjusted for inflation, Internet advertising revenue notably outperformed both cable and broadcast television in comparable early growth periods (Interactive Advertising Bureau, 2006). Even though there is a wide variety of advertising forms on the Internet, banner advertisements have become the most common and standard advertising format on the Internet since the first banner appeared on the Internet in 1994 (Cho, 2003). According to the Interactive Advertising Bureau, search ads accounted for 41% of Internet advertising revenue in 2005, followed by display ads (34%) and classifieds (17%). It should be noted that in the case of display ads advertiser pays an on-line company for space to display a static or hyper-linked banner or logo on one or more of the on-line company’s pages. The goal of most banner ads seems to be twofold: (1) to get direct responses, and (2) to obtain brand recognition through banner exposure. In other words, a banner ad may result in a significant amount of increase in brand enhancement even without being clicked on. As a result, a debate has developed in the advertising industry as to whether web advertising effectiveness should be assessed by the click-through rate that is the proportion of viewers who click on a banner to visit the advertiser’s website (Hanson, 2000) or simple page exposure. Despite the fact that click-through based metrics may be appropriate for particular types of advertising (Gatarski, 1996), there will be instances where online advertising will have a tangible impact just by way of mere exposure without actually being clicked on (Briggs & Hollis, 1997). A review of recent literature indicates that an exposure-based approach to web advertising has become more common in recent years (Olsen, 2001; Sherman & Deighton, 2001; Yoon & Kim, 2001). At the same time, the inclination to ignore or avoid banner ads especially among heavy Internet users has become a focal issue in the web advertising industry (Pagendarm & Schaumburg, 2001). As a result, these trends increase the importance of a banner’s ability to stimulate direct responses and put emphasis on the problem of effective design and media planning (Shamdasani, Stanaland, & Tan, 2001). Therefore, it is the first function of an advertisement to attract attention (Sandage, 1945). Advertisements that fail to gain and hold consumers’ attention cannot be effective. However, the existence of only attention is not enough. Advertisements also need to leave long-lasting traces of brands in memory (Wedel & Pieters, 2000). In this respect, advertisers need to first identify the factors affecting banner ads effectiveness. Despite the importance of the topic, there has been little research conducted to investigate the factors that contribute to the effectiveness of banner ads. Moreover, primary focus of much of the prior research (e.g., Hofacker & Murphy, 2000; Baltas, 2003; Chatterjee, Hoffman, & Novak, 2003; Lohtia, Donthu, & Hershberger, 2003) has been on determining factors affecting click-through rates. In addition, our literature review revealed only a few studies that have produced contradictory results concerning the perception of banners on the Web (Bachofer, 1998; Benway, 1999). Pagendarm and Schaumburg (2001) have explained these performance
F. Calisir, D. Karaali / Computers in Human Behavior 24 (2008) 535–543
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differences by different navigation styles employed (aimless browsing versus goal-directed search). They found that aimless browsing subjects achieve better results in banner recognition and recall tests than subjects who search for information in a goal directed way. This finding is consistent with prior research indicating that goal-directed behavior reduces attention to peripheral stimuli, while exploratory behavior means peripheral stimuli can compete for attention, since attention is not singularly focused (Janiszewski, 1998, Danaher & Mullarkey, 2003). A number of advertising research studies have tried to understand the role and effect of web addresses in a general mass media advertisement. One of these studies was that of Maddox, Mehta, and Daubek (1997), who suggest that web addresses in advertising are effective in terms of advertising memory and competitive advantage. In particular, 30% of their respondents indicated that a Web address helps them to remember an advertiser’s brand name. Their results also reveal that web addresses in advertising are noticed by 83%. Since they conducted their study in the middle of the Internet hype, it remains to be shown whether similar effects can be observed for banner ads. On the other hand, Nielsen (2000) gave a bank banner ad with five colored buttons providing a better idea of some of the services the user will find as a good example of an effective banner. It is a fact that consumers are exposed to banner ads in the context of web pages rather than as stand-alone banners. Therefore, the effectiveness of the banner ads may be influenced by the banner location on the page. A research study on the effectiveness of magazine ads supports the idea that exposure varies somewhat with the position of the ad. Specifically, the percent of readers who viewed the tested ad were higher for ads in the first third of a magazine, lower for those in the last third, and highest for those across from the table of contents (Magazine Publishers of America, 1995). Similarly, Nielsen (2000) suggested the placement of objects such as company name, logo, picture, etc., in the upperleft corner of a web page. Some support for this suggestion was provided by Bernard (2001) who found that banner advertisements are generally expected to be at the top of a web page. It should be noted that to our knowledge, there are no studies that directly examine the separate and interactive effects of banner location, banner content, and navigation style on the effectiveness of banner ads. It was therefore felt timely to examine whether these factors influence banner ads effectiveness, in particular, the recognition of banner advertisements. Recognition was selected as a variable because prior research indicates that recognition measures the presence of trace of the commercial in memory and, it is a more robust measure than recall (Ewing, Napoli, & Du Plesses, 1999). 2. Methodology 2.1. Participants A total of 90 students from Istanbul Technical University participated in the study. Of the 90, 60 were male and 30 were female. The sample was obtained in small groups from a wide variety of undergraduate and graduate courses. They were spread over different years of their studies, with an average age of 23. Forty-five percent of our participants use the Internet more than 10 h a week. The use of student samples has been a source of much concern for a long time (e.g., Sackett & Larson, 1990). The most often cited problem has been the fact that a student
538
F. Calisir, D. Karaali / Computers in Human Behavior 24 (2008) 535–543
sample may not fully represent the entire population. As a result, student sample studies lack external validity. However, there might be situations where a student sample is appropriate. For example, college students have been a profitable group for online marketers since they comprise one of the largest Internet user segments (Davis, 1999). A recent study by Biswas and Biswas (2004) also support the use of student samples since they mirror closely the typical internet user. Therefore, the use of a student sample in this study was deemed acceptable given the nature of the study and their literacy and use of the Internet. 2.2. Materials Mitchell (1986) suggests that professionally developed ads are better than mock-ads in getting more natural responses from the subjects. For this reason, the modified versions of a professionally developed web site and a bank’s banner ad were used in this study. The www.yasamenerjisi.com web site is about positive energy and far eastern philosophies (Fig. 1). This site was selected because we believed that the content was neutral and equally important to general consumers. The pages were on a university server and accessed through the university’s local area network.
Fig. 1. A screen-shot of the web site used in this study.
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A commercial bank’s banner advertisement was selected as one of the target banners to be used in this study. In addition to the original banner displaying the name of the bank, two modified versions were designed. One of the modified versions presented the URL address for the bank while the other one provided some service information as well as the URL address (Fig. 2). Our banner ads were of standard half-size (234 · 60 pixels). The same banner appeared at the same location (the top left side, top right side, or top center) on every page viewed by the same participant. 2.3. Experimental design A between-subjects design was used. The between subjects factors were banner location (top left side, top center, top right side), banner content (bank name, URL address, URL address plus some service information), and navigation style (aimless browsing, goal directed). The dependent variable was the participants’ banner recognition test scores. The banner recognition test consisted of eight multiple-choice questions. Taking a banner that also appeared on every page viewed, and seven other banners that did not appear formed each question. Participants were asked to indicate which banner they did see. Participants also indicated their confidence in their answers by selecting ‘‘guessed’’, ‘‘agree’’, or ‘‘absolutely agree’’ after indicating their response to each question. In all analyses the confidence ratings were combined with their correct (C)/incorrect (I) answers to produce a widened scale (I3 assigned a 1, I2 assigned a 2, I3 assigned a 3, C1 assigned a 4, C2 assigned a 5, C6 assigned a 6) ranging from 1 (very sure that the answer was correct, however, the answer turned out to be incorrect) to 6 (very sure that the answer was correct, and the answer turn out to be correct). A participant’s banner recognition test score is equal to the total points divided by 8 (the number of banners used in the test). Young (1990) has noted that this transformation is commonly used in recognition memory research because it is often more sensitive at finding differences between conditions than yes/no responses. 2.4. Procedure After the participants were randomly assigned to one of 20 personal computers located in the college’s computer classroom, the experimenter informed them verbally about the procedure. Depending on the personal computer they were assigned to, they were also automatically allocated to one of eighteen experimental groups. All further instructions
Fig. 2. The target banner ads used in this study.
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F. Calisir, D. Karaali / Computers in Human Behavior 24 (2008) 535–543
for the experiment were displayed on-screen. In the first part of the experiment, goal-directed subjects were asked to find as many answers as possible to a list of 10 multiple-choice questions, whereas aimless browsing subjects were told that they would have a period of time to surf the web site according to their own interest. No further instructions were given to this group because we did not want to impose a goal on them. Both groups had a total time of 15 min in this part. However, this time limit was not mentioned before the process began, since this would have affected exploratory nature of this part of the experiment especially in the case of aimless browsing subjects. Immediately after the total exposure time elapsed, subjects were tested for their recognition of the target banner advertisement that had been present on every page viewed and could not return to the website. The order of banners was randomized for each participant. Following this, subjects were taken to an on-screen questionnaire to get their basic demographic information, as well as information concerning their internet use. The participation for each subject took approximately 30 min. Responses on each experimental item including click-through were automatically recorded into the database file located at the server. 3. Results A 2 (aimless browsing, goal-directed search) · 3 (top left side, top center, top right side) · 3 (bank name, URL address, URL address plus some service information) ANOVA was performed using banner recognition scores as the dependent variable. A significance level of 0.05 was used for interpreting the results. Table 1 shows the summary of the 3-way ANOVA performed on banner recognition scores. Although, neither the main effects nor the 3-way interaction were significant, there was a significant Banner Content · Navigation Style interaction (F-value = 5.38, P-value = 0.007). The two-way interaction is graphed in Fig. 3. As far as aimless browsing participants were concerned, they recognized the banner ad with a URL address significantly better (M = 4.19, SD = 0.71) than the one with some service information as well as the URL address (M = 3.59, SD = 0.37). However, for goaldirected search participants, there was no significant difference among the three banner content types. The results also indicated that goal-directed search participants had higher recognition scores (M = 4.43, SD = 0.79) than aimless browsing subjects (M = 3.59, SD = 0.37) only when the banner ad with some service information and URL address was used. Table 1 Three way ANOVA for banner recognition Source
DF
SS
MS
F
Significance level
Location Content Navigation Location * content Location * navigation style Content * navigation style Location * content * navigation style
2 2 1 4 2 2 4
0.321 0.096 0.851 1.814 0.330 4.963 1.866
0.161 0.048 0.851 0.454 0.165 2.481 0.467
0.348 0.104 1.843 0.983 0.357 5.377 1.011
0.707 0.901 0.179 0.422 0.701 0.007* 0.408
*
p < 0.05.
F. Calisir, D. Karaali / Computers in Human Behavior 24 (2008) 535–543
541
Content URL address
Mean Recognition Score
4.40
Bank name URL address with some service information
4.20
4.00
3.80
3.60
Aimless browsing
Goal directed search
Navigation Fig. 3. Interaction effect between content and navigation style for banner recognition scores.
4. Discussion The present study sought to examine factors that might impact banner recognition. These factors include banner location, banner content and navigation style. The key finding is that banner recognition is affected by the interaction of banner content and navigation style. In particular, our results suggest that banner content does not work the same way for aimless browsing and goal-directed search subjects. For example, aimless browsing participants recognized the banner ad with a URL address significantly better than the one with some service information as well as the URL address for which goal-directed search subjects had the highest recognition score. Moreover, it was also the highest recognition score achieved in this study. These results are not consistent with the findings of Danaher and Mullarkey (2003), that web users in a goal-directed mode are much less likely to recognize banner ads than users who are surfing the site. The most likely reason for superior recognition performance of goal-directed search subjects is that the combination of the service information with the URL address in the banner ad got their attention more than other two content types because their goal was to look for specific information. This hypothesis needs to be further investigated by using an eye tracking device. This result also has implications for media planning. Media planners should not only focus on banner design, but also on understanding the users and their intentions when browsing a Web site if they want to achieve the highest banner recognition levels. Our results suggest that greater banner advertising effectiveness can be gained by choosing web sites for banners giving detailed service information as well as a URL address where more goal-directed searching is likely to take place. On the other hand, greater banner
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advertising effectiveness can be achieved by choosing web sites for banners presenting only a URL address where more surfing is likely to occur. In contrast to our expectations, we did not find a main effect of banner location on banner recognition. We speculate that this may be due to the fact that all target banner ads used in this study were placed at the top of experimental web pages, and it would certainly be beneficial for future research to examine the effect of banner location by placing banner ads in different parts of the experimental web pages such as at the top of the page, on the left side of the page, and on the right side of the page. The results of this study need to be interpreted within the context of its limitations. First, in this study, participants were tested for their recognition of the target banner advertisement immediately after the total exposure time of 15 min elapsed. The present research should be replicated by giving some time before taking the banner recognition test. Second, only standard half-size target banner ads were used in this study. However, previous ad-processing literature had addressed the importance of ad size as having a significant impact on ad recognition. Therefore, further studies should examine the effect of banner size on banner recognition. Third, only three target banner ads and an experimental website were used in this study. It would be valuable to conduct future experiments using banner ads and web sites for diverse product categories. Finally, we have examined banner ad effectiveness as measured by banner recognition for previously stated reasons. However, a single measure can not give an integrated picture of internet advertising (Baltas, 2003). The finding that only 4 subjects out of 90 clicked on the target banner ads seems to be supporting this claim. Hence, the findings should be interpreted with caution since they relate to a specific measure of banner ad effectiveness. References Baltas, G. (2003). Determinants of internet advertising effectiveness: an empirical study. International Journal of Market Research, 45, 505–513. Bachofer, M. (1998). Die Stern Bibliothek: Wie wirkt Werbung im Web? Hamburg: Gruner and Jahr. Benway, J. P. (1999). Banner blindness: what searching users notice and do not notice on the World Wide Web. Dissertation Abstracts International, 60, 1695. Bernard, M. L. (2001). Developing schemas for the location of common web objects. In Proceedings of the Human Factors and Ergonomics Society 45th Annual Meeting (pp. 1161–1165). Santa Monica, CA: Human Factors and Ergonomics Society. Biswas, D., & Biswas, A. (2004). The diagnostic role of signals in the context of perceived risks in online shopping: do signals matter more on the web? Journal of Interactive Marketing, 18(3), 30–45. Briggs, R., & Hollis, N. (1997). Advertising on the Web: is there response before clickthrough? Journal of Advertising Research, 37(2), 33–45. Chatterjee, P., Hoffman, D. L., & Novak, T. P. (2003). Modeling the clickstream: implications for web-based advertising efforts. Marketing Science, 22(4), 520–541. Cho, C. (2003). The effectiveness of banner advertisements: involvement and click-through. Journalism and Mass Communication Quarterly, 80(3), 623–645. Computer Industry Almanac Inc. Press Release (2006). Worldwide Internet Users Top 1 Billion in 2005. http:// www.c-i-a.com/pr0106.htm. Danaher, P. J., & Mullarkey, G. W. (2003). Factors affecting online advertising recall: a study of students. Journal of Advertising Research, 43(3), 252–267. Davis, J. F. (1999). Effectiveness of internet advertising by leading national advertisers. In D. W. Schumann & E. Thorson (Eds.), Advertising and World Wide Web (pp. 81–97). Mahwah, NJ: Lawrence Erlbaum. Ewing, M., Napoli, J., & Du Plesses, E. (1999). Factors affecting in-market recall of food product advertising. Journal of Advertising Research, 39(4), 29–38.
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Gatarski, R. (1996). Breed better banners: design automation through online interaction. Journal of Interactive Marketing, 16(1), 2–13. Hanson, W. (2000). Principles of internet marketing. Cincinnati, OH: South-Western College Publishing. Hofacker, C., & Murphy, J. (2000). Clickable World Wide Web banner ads and content sites. Journal of Interactive Marketing, 14(1), 49–59. Interactive Advertising Bureau (2006). IAB Internet Advertising Report-2005 Full-Year Results. Price Waterhouse Coopers. http://www.iab.net/resources/ad_revenue.asp Accessed 04.20.06. Janiszewski, C. (1998). The influence of display characteristics on visual exploratory search behaviour. Journal of Consumer Research, 25(3), 290–301. Lohtia, R., Donthu, N., & Hershberger, E. K. (2003). The impact of content and design elements on banner advertising click-through rates. Journal of Advertising Research, 43(4), 410–418. Magazine Publishers of America (1995). Consumer perception of increased advertising, 29(May), 1–7. Maddox, L. M., Mehta, D., & Daubek, H. G. (1997). The role and effect of web addresses in advertising. Journal of Advertising Research, 37(2), 47–59. Mitchell, A. A. (1986). Theoretical and methodological issues in developing an individual level model of advertising effects. In J. C. Olson & K. Sentis (Eds.), Advertising and consumer psychology (pp. 172–196). NY: Praeger Publishing. Nielsen, J. (2000). Designing web usability: the practice of simplicity. Indianapolis, IN: New Riders Publishing. Olsen, S. (2001). Online ads take a cue from TV. Cj Net news.com, November 19. Pagendarm, M., & Schaumburg, H. (2001). Why are users banner-blind? The impact of navigation style on the perception of web banners. Journal of Digital Information, 2(1), http://journals.tdl.org/jodi/article/view/jodi37/38 Accessed 6.20.06. Sackett, P. R., & Larson, J. R. Jr., (1990). Research strategies and tactics in industrial and organizational psychology. In M. D. Dunnette & L. M. Hough (Eds.), Handbook of industrial and organizational psychology (pp. 419–489). Palo Alto, CA: Consulting Psychologists Press. Sandage, C. H. (1945). Advertising: theory and practice. Chicago, IL: Richard D. Irwin. Shamdasani, P. N., Stanaland, A. J. S., & Tan, J. (2001). Location, location, location: insights for advertising placement on the web. Journal of Advertising Research, 41(4), 7–21. Sherman, L., & Deighton, J. (2001). Banner advertising: effectiveness and optimizing placement. Journal of Interactive Marketing, 15(2), 60–64. Wedel, M., & Pieters, R. (2000). Eye fixations on advertisements and memory for brands: a model and findings. Marketing Science, 19(4), 297–312. Yoon, S. J., & Kim, J. H. (2001). Is the internet more effective than traditional media? Factors affecting the choice of media. Journal of Advertising Research, 41(6), 53–60. Young, S. L. (1990). Comprehension and memory of instruction manual warnings: conspicuous print and pictorial icons. Human Factors, 32(6), 637–649.
The impacts of banner location, banner content and navigation style on banner recognition Fethi Calisir a
a,*
, Demet Karaali
b,1
Industrial Engineering Department, Faculty of Management, Istanbul Technical University, 80680 Macka-Istanbul, Turkey b Mercedes-Benz Turk A.S. Marketing Center, 34500 Bahcesehir-Istanbul, Turkey Available online 5 April 2007
Abstract This study is an attempt to examine factors that might impact banner recognition. These factors include banner location, banner content and navigation style. Via an experimental design conducted on a sample of 90 students, we manipulate these factors over several levels. Our key finding is that banner recognition is affected by the interaction of banner content and navigation style. In particular, as far as aimless browsing participants were concerned, they recognized the banner ad with a URL address significantly better than the one with some service information as well as the URL address. However, for goal-directed search participants, there was no significant difference among the three banner content types. The results also indicated that goal-directed search participants had higher recognition scores than aimless browsing subjects only when the banner ad with some service information and URL address was used. Managerial implications of these results are discussed and future research avenues are proposed. 2007 Elsevier Ltd. All rights reserved. Keywords: Banner recognition; Navigation style; Banner location; Banner content
1. Introduction It is estimated that over 1 billion people were using the Internet worldwide in 2005, up from only 45 million in 1995 and 414 million in 2000. Moreover, this number is expected to *
1
Corresponding author. Tel.: +90 212 240 7260; fax: +90 532 661 53 12. E-mail addresses: [email protected] (F. Calisir), [email protected] (D. Karaali). Tel.: +90 212 858 0990; fax: +90 212 858 0980.
0747-5632/$ - see front matter 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.chb.2007.02.019
536
F. Calisir, D. Karaali / Computers in Human Behavior 24 (2008) 535–543
reach the 2 billion Internet users target in 2011 (Computer Industry Almanac, 2006). With the continuing growth in the number of Internet users, advertising expenditure on the Internet is also going up exponentially. This is obvious in the fact that Internet advertising revenues for 2005 are projected to surpass $12.5 billion, a 30% increase over the prior revenue record of $9.6 billion in 2004. In addition, Internet advertising accounted for nearly 5% of total U.S. advertising revenues in 2005, up from less than 4% reported in 2004. Internet advertising surpassed advertising for business magazines by more than 50% in 2005, and almost matches total consumer magazine advertising. Adjusted for inflation, Internet advertising revenue notably outperformed both cable and broadcast television in comparable early growth periods (Interactive Advertising Bureau, 2006). Even though there is a wide variety of advertising forms on the Internet, banner advertisements have become the most common and standard advertising format on the Internet since the first banner appeared on the Internet in 1994 (Cho, 2003). According to the Interactive Advertising Bureau, search ads accounted for 41% of Internet advertising revenue in 2005, followed by display ads (34%) and classifieds (17%). It should be noted that in the case of display ads advertiser pays an on-line company for space to display a static or hyper-linked banner or logo on one or more of the on-line company’s pages. The goal of most banner ads seems to be twofold: (1) to get direct responses, and (2) to obtain brand recognition through banner exposure. In other words, a banner ad may result in a significant amount of increase in brand enhancement even without being clicked on. As a result, a debate has developed in the advertising industry as to whether web advertising effectiveness should be assessed by the click-through rate that is the proportion of viewers who click on a banner to visit the advertiser’s website (Hanson, 2000) or simple page exposure. Despite the fact that click-through based metrics may be appropriate for particular types of advertising (Gatarski, 1996), there will be instances where online advertising will have a tangible impact just by way of mere exposure without actually being clicked on (Briggs & Hollis, 1997). A review of recent literature indicates that an exposure-based approach to web advertising has become more common in recent years (Olsen, 2001; Sherman & Deighton, 2001; Yoon & Kim, 2001). At the same time, the inclination to ignore or avoid banner ads especially among heavy Internet users has become a focal issue in the web advertising industry (Pagendarm & Schaumburg, 2001). As a result, these trends increase the importance of a banner’s ability to stimulate direct responses and put emphasis on the problem of effective design and media planning (Shamdasani, Stanaland, & Tan, 2001). Therefore, it is the first function of an advertisement to attract attention (Sandage, 1945). Advertisements that fail to gain and hold consumers’ attention cannot be effective. However, the existence of only attention is not enough. Advertisements also need to leave long-lasting traces of brands in memory (Wedel & Pieters, 2000). In this respect, advertisers need to first identify the factors affecting banner ads effectiveness. Despite the importance of the topic, there has been little research conducted to investigate the factors that contribute to the effectiveness of banner ads. Moreover, primary focus of much of the prior research (e.g., Hofacker & Murphy, 2000; Baltas, 2003; Chatterjee, Hoffman, & Novak, 2003; Lohtia, Donthu, & Hershberger, 2003) has been on determining factors affecting click-through rates. In addition, our literature review revealed only a few studies that have produced contradictory results concerning the perception of banners on the Web (Bachofer, 1998; Benway, 1999). Pagendarm and Schaumburg (2001) have explained these performance
F. Calisir, D. Karaali / Computers in Human Behavior 24 (2008) 535–543
537
differences by different navigation styles employed (aimless browsing versus goal-directed search). They found that aimless browsing subjects achieve better results in banner recognition and recall tests than subjects who search for information in a goal directed way. This finding is consistent with prior research indicating that goal-directed behavior reduces attention to peripheral stimuli, while exploratory behavior means peripheral stimuli can compete for attention, since attention is not singularly focused (Janiszewski, 1998, Danaher & Mullarkey, 2003). A number of advertising research studies have tried to understand the role and effect of web addresses in a general mass media advertisement. One of these studies was that of Maddox, Mehta, and Daubek (1997), who suggest that web addresses in advertising are effective in terms of advertising memory and competitive advantage. In particular, 30% of their respondents indicated that a Web address helps them to remember an advertiser’s brand name. Their results also reveal that web addresses in advertising are noticed by 83%. Since they conducted their study in the middle of the Internet hype, it remains to be shown whether similar effects can be observed for banner ads. On the other hand, Nielsen (2000) gave a bank banner ad with five colored buttons providing a better idea of some of the services the user will find as a good example of an effective banner. It is a fact that consumers are exposed to banner ads in the context of web pages rather than as stand-alone banners. Therefore, the effectiveness of the banner ads may be influenced by the banner location on the page. A research study on the effectiveness of magazine ads supports the idea that exposure varies somewhat with the position of the ad. Specifically, the percent of readers who viewed the tested ad were higher for ads in the first third of a magazine, lower for those in the last third, and highest for those across from the table of contents (Magazine Publishers of America, 1995). Similarly, Nielsen (2000) suggested the placement of objects such as company name, logo, picture, etc., in the upperleft corner of a web page. Some support for this suggestion was provided by Bernard (2001) who found that banner advertisements are generally expected to be at the top of a web page. It should be noted that to our knowledge, there are no studies that directly examine the separate and interactive effects of banner location, banner content, and navigation style on the effectiveness of banner ads. It was therefore felt timely to examine whether these factors influence banner ads effectiveness, in particular, the recognition of banner advertisements. Recognition was selected as a variable because prior research indicates that recognition measures the presence of trace of the commercial in memory and, it is a more robust measure than recall (Ewing, Napoli, & Du Plesses, 1999). 2. Methodology 2.1. Participants A total of 90 students from Istanbul Technical University participated in the study. Of the 90, 60 were male and 30 were female. The sample was obtained in small groups from a wide variety of undergraduate and graduate courses. They were spread over different years of their studies, with an average age of 23. Forty-five percent of our participants use the Internet more than 10 h a week. The use of student samples has been a source of much concern for a long time (e.g., Sackett & Larson, 1990). The most often cited problem has been the fact that a student
538
F. Calisir, D. Karaali / Computers in Human Behavior 24 (2008) 535–543
sample may not fully represent the entire population. As a result, student sample studies lack external validity. However, there might be situations where a student sample is appropriate. For example, college students have been a profitable group for online marketers since they comprise one of the largest Internet user segments (Davis, 1999). A recent study by Biswas and Biswas (2004) also support the use of student samples since they mirror closely the typical internet user. Therefore, the use of a student sample in this study was deemed acceptable given the nature of the study and their literacy and use of the Internet. 2.2. Materials Mitchell (1986) suggests that professionally developed ads are better than mock-ads in getting more natural responses from the subjects. For this reason, the modified versions of a professionally developed web site and a bank’s banner ad were used in this study. The www.yasamenerjisi.com web site is about positive energy and far eastern philosophies (Fig. 1). This site was selected because we believed that the content was neutral and equally important to general consumers. The pages were on a university server and accessed through the university’s local area network.
Fig. 1. A screen-shot of the web site used in this study.
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A commercial bank’s banner advertisement was selected as one of the target banners to be used in this study. In addition to the original banner displaying the name of the bank, two modified versions were designed. One of the modified versions presented the URL address for the bank while the other one provided some service information as well as the URL address (Fig. 2). Our banner ads were of standard half-size (234 · 60 pixels). The same banner appeared at the same location (the top left side, top right side, or top center) on every page viewed by the same participant. 2.3. Experimental design A between-subjects design was used. The between subjects factors were banner location (top left side, top center, top right side), banner content (bank name, URL address, URL address plus some service information), and navigation style (aimless browsing, goal directed). The dependent variable was the participants’ banner recognition test scores. The banner recognition test consisted of eight multiple-choice questions. Taking a banner that also appeared on every page viewed, and seven other banners that did not appear formed each question. Participants were asked to indicate which banner they did see. Participants also indicated their confidence in their answers by selecting ‘‘guessed’’, ‘‘agree’’, or ‘‘absolutely agree’’ after indicating their response to each question. In all analyses the confidence ratings were combined with their correct (C)/incorrect (I) answers to produce a widened scale (I3 assigned a 1, I2 assigned a 2, I3 assigned a 3, C1 assigned a 4, C2 assigned a 5, C6 assigned a 6) ranging from 1 (very sure that the answer was correct, however, the answer turned out to be incorrect) to 6 (very sure that the answer was correct, and the answer turn out to be correct). A participant’s banner recognition test score is equal to the total points divided by 8 (the number of banners used in the test). Young (1990) has noted that this transformation is commonly used in recognition memory research because it is often more sensitive at finding differences between conditions than yes/no responses. 2.4. Procedure After the participants were randomly assigned to one of 20 personal computers located in the college’s computer classroom, the experimenter informed them verbally about the procedure. Depending on the personal computer they were assigned to, they were also automatically allocated to one of eighteen experimental groups. All further instructions
Fig. 2. The target banner ads used in this study.
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for the experiment were displayed on-screen. In the first part of the experiment, goal-directed subjects were asked to find as many answers as possible to a list of 10 multiple-choice questions, whereas aimless browsing subjects were told that they would have a period of time to surf the web site according to their own interest. No further instructions were given to this group because we did not want to impose a goal on them. Both groups had a total time of 15 min in this part. However, this time limit was not mentioned before the process began, since this would have affected exploratory nature of this part of the experiment especially in the case of aimless browsing subjects. Immediately after the total exposure time elapsed, subjects were tested for their recognition of the target banner advertisement that had been present on every page viewed and could not return to the website. The order of banners was randomized for each participant. Following this, subjects were taken to an on-screen questionnaire to get their basic demographic information, as well as information concerning their internet use. The participation for each subject took approximately 30 min. Responses on each experimental item including click-through were automatically recorded into the database file located at the server. 3. Results A 2 (aimless browsing, goal-directed search) · 3 (top left side, top center, top right side) · 3 (bank name, URL address, URL address plus some service information) ANOVA was performed using banner recognition scores as the dependent variable. A significance level of 0.05 was used for interpreting the results. Table 1 shows the summary of the 3-way ANOVA performed on banner recognition scores. Although, neither the main effects nor the 3-way interaction were significant, there was a significant Banner Content · Navigation Style interaction (F-value = 5.38, P-value = 0.007). The two-way interaction is graphed in Fig. 3. As far as aimless browsing participants were concerned, they recognized the banner ad with a URL address significantly better (M = 4.19, SD = 0.71) than the one with some service information as well as the URL address (M = 3.59, SD = 0.37). However, for goaldirected search participants, there was no significant difference among the three banner content types. The results also indicated that goal-directed search participants had higher recognition scores (M = 4.43, SD = 0.79) than aimless browsing subjects (M = 3.59, SD = 0.37) only when the banner ad with some service information and URL address was used. Table 1 Three way ANOVA for banner recognition Source
DF
SS
MS
F
Significance level
Location Content Navigation Location * content Location * navigation style Content * navigation style Location * content * navigation style
2 2 1 4 2 2 4
0.321 0.096 0.851 1.814 0.330 4.963 1.866
0.161 0.048 0.851 0.454 0.165 2.481 0.467
0.348 0.104 1.843 0.983 0.357 5.377 1.011
0.707 0.901 0.179 0.422 0.701 0.007* 0.408
*
p < 0.05.
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Content URL address
Mean Recognition Score
4.40
Bank name URL address with some service information
4.20
4.00
3.80
3.60
Aimless browsing
Goal directed search
Navigation Fig. 3. Interaction effect between content and navigation style for banner recognition scores.
4. Discussion The present study sought to examine factors that might impact banner recognition. These factors include banner location, banner content and navigation style. The key finding is that banner recognition is affected by the interaction of banner content and navigation style. In particular, our results suggest that banner content does not work the same way for aimless browsing and goal-directed search subjects. For example, aimless browsing participants recognized the banner ad with a URL address significantly better than the one with some service information as well as the URL address for which goal-directed search subjects had the highest recognition score. Moreover, it was also the highest recognition score achieved in this study. These results are not consistent with the findings of Danaher and Mullarkey (2003), that web users in a goal-directed mode are much less likely to recognize banner ads than users who are surfing the site. The most likely reason for superior recognition performance of goal-directed search subjects is that the combination of the service information with the URL address in the banner ad got their attention more than other two content types because their goal was to look for specific information. This hypothesis needs to be further investigated by using an eye tracking device. This result also has implications for media planning. Media planners should not only focus on banner design, but also on understanding the users and their intentions when browsing a Web site if they want to achieve the highest banner recognition levels. Our results suggest that greater banner advertising effectiveness can be gained by choosing web sites for banners giving detailed service information as well as a URL address where more goal-directed searching is likely to take place. On the other hand, greater banner
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advertising effectiveness can be achieved by choosing web sites for banners presenting only a URL address where more surfing is likely to occur. In contrast to our expectations, we did not find a main effect of banner location on banner recognition. We speculate that this may be due to the fact that all target banner ads used in this study were placed at the top of experimental web pages, and it would certainly be beneficial for future research to examine the effect of banner location by placing banner ads in different parts of the experimental web pages such as at the top of the page, on the left side of the page, and on the right side of the page. The results of this study need to be interpreted within the context of its limitations. First, in this study, participants were tested for their recognition of the target banner advertisement immediately after the total exposure time of 15 min elapsed. The present research should be replicated by giving some time before taking the banner recognition test. Second, only standard half-size target banner ads were used in this study. However, previous ad-processing literature had addressed the importance of ad size as having a significant impact on ad recognition. Therefore, further studies should examine the effect of banner size on banner recognition. Third, only three target banner ads and an experimental website were used in this study. It would be valuable to conduct future experiments using banner ads and web sites for diverse product categories. Finally, we have examined banner ad effectiveness as measured by banner recognition for previously stated reasons. However, a single measure can not give an integrated picture of internet advertising (Baltas, 2003). The finding that only 4 subjects out of 90 clicked on the target banner ads seems to be supporting this claim. Hence, the findings should be interpreted with caution since they relate to a specific measure of banner ad effectiveness. References Baltas, G. (2003). Determinants of internet advertising effectiveness: an empirical study. International Journal of Market Research, 45, 505–513. Bachofer, M. (1998). Die Stern Bibliothek: Wie wirkt Werbung im Web? Hamburg: Gruner and Jahr. Benway, J. P. (1999). Banner blindness: what searching users notice and do not notice on the World Wide Web. Dissertation Abstracts International, 60, 1695. Bernard, M. L. (2001). Developing schemas for the location of common web objects. In Proceedings of the Human Factors and Ergonomics Society 45th Annual Meeting (pp. 1161–1165). Santa Monica, CA: Human Factors and Ergonomics Society. Biswas, D., & Biswas, A. (2004). The diagnostic role of signals in the context of perceived risks in online shopping: do signals matter more on the web? Journal of Interactive Marketing, 18(3), 30–45. Briggs, R., & Hollis, N. (1997). Advertising on the Web: is there response before clickthrough? Journal of Advertising Research, 37(2), 33–45. Chatterjee, P., Hoffman, D. L., & Novak, T. P. (2003). Modeling the clickstream: implications for web-based advertising efforts. Marketing Science, 22(4), 520–541. Cho, C. (2003). The effectiveness of banner advertisements: involvement and click-through. Journalism and Mass Communication Quarterly, 80(3), 623–645. Computer Industry Almanac Inc. Press Release (2006). Worldwide Internet Users Top 1 Billion in 2005. http:// www.c-i-a.com/pr0106.htm. Danaher, P. J., & Mullarkey, G. W. (2003). Factors affecting online advertising recall: a study of students. Journal of Advertising Research, 43(3), 252–267. Davis, J. F. (1999). Effectiveness of internet advertising by leading national advertisers. In D. W. Schumann & E. Thorson (Eds.), Advertising and World Wide Web (pp. 81–97). Mahwah, NJ: Lawrence Erlbaum. Ewing, M., Napoli, J., & Du Plesses, E. (1999). Factors affecting in-market recall of food product advertising. Journal of Advertising Research, 39(4), 29–38.
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