Banner Advertising – Definition

Cite this article as:"Banner Advertising – Definition," in The Business Professor, updated January 24, 2020, last accessed October 25, 2020, https://thebusinessprofessor.com/lesson/banner-advertising-definition/.

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Banner Advertising, in regards to digital marketing, is a form of advertising that allows anyone to place an ad on another site through the use of attractive images. Banner advertising is image-centric, as the images communicate a series of messages for the audience. It can also be referred to as a “web banner”. The primary purpose is to drive the attention of users or visitors on the host site to another site. A web banner or banner ad can be on an official site or on a social media site depending on the content of the banner or the target audience.

A Little More on What is Banner Advertising

Digital banner advertising also requires the basic procedures that have been in use by the ancient traditional banner advertising. These basics includes deciding on the right shape (vertical or skyscraper / horizontal or leaderboard) that fit the nature and purpose of the banner ad, quality design with brand colors, catch large fonts on the banner, strategic placement of the banner. The most effective innovations and changes brought about by information technology in the way banner advertising is done is the payment model, the strategic reach, and the in-expensive set-up structure of digital banner advertising. Call to action buttons  CTA, also allows advert placers to specify the kind of actions expected to be achieved through banner ad placements.

Key Takeaways

  • Banner advertising is one of the foremost forms of digital marketing.
  • It is basically used for product sales and brand awareness.
  • Advertisers can personalize and target specific industries, audiences, and demographics.
  • Through click-through rates (CTR) analytics, advertisers can monitor the effectiveness of their ads and the corresponding behavior of visitors towards the banner ads.
  • Close to six trillion banner ad impressions (views) were achieved in the year 2012.
  • Advertisers rely on ad networks to target banner ads to prospective web visitors.
  • In the history of banner advertising, the biggest size skyscrapers with alength of 336 by 280 has the highest average CTR of 0.33%

Due to the use of technology, banner advertising has advanced so much in its effectiveness.

There are now technological applications and software used in designing different banner types for different platforms on the world wide web. Through ad networks, advertisers can match their ads to interests and keyword search of web visitors and users so as to enable these visitors to find meaning or value in the displayed ad. Through an on-demand biding system, the advertisers can place their ads to the prospective audiences and are billed through cost per click (CPC), cost per impression (CPM), cost per action(CPA). Much return on investment (ROI) can be derived from banner advertisements if the basics well done to appeal to the psychology of online visitors.

Reference for “Banner Advertising”

https://blog.bannersnack.com/beginner-guide-banner-ad/

https://www.investopedia.com/terms/b/banneradvertising.asp

https://developers.google.com/admob/android/banner

https://www.marketingterms.com/dictionary/banner_ad/

https://www.collinsdictionary.com/dictionary/english/banner-ad

Academics research on “Banner Advertising”

The effect of banner advertising on internet purchasing, Manchanda, P., DubĂ©, J. P., Goh, K. Y., & Chintagunta, P. K. (2006). The effect of banner advertising on internet purchasing. Journal of Marketing Research, 43(1), 98-108. This article focuses on whether banner advertising affects purchasing patterns on the Internet. Using a behavioral database that consists of customer purchases at a Web site along with individual advertising exposure, the authors measure the impact of banner advertising on current customers’ probabilities of repurchase, while accounting for duration dependence. The authors model the probability of a current customer making a purchase in any given week (since the last purchase) with a survival model that uses a flexible, piecewise exponential hazard function. The advertising covariates are purely advertising variables and advertising/individual browsing variables. The model is cast in a hierarchical Bayesian framework, which enables the authors to obtain individual advertising response parameters. The results show that the number of exposures, number of Web sites, and number of pages all have a positive effect on repeat purchase probabilities, whereas the number of unique creatives has a negative effect. Returns from targeting are the highest for the number of advertising exposures. The findings also add to the general advertising literature by showing that advertising affects the purchase behavior of current (versus new) customers.

The impact of content and design elements on banner advertising click-through rates, 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. This study investigates the impact of content and design elements on the click-through rates of banner advertisements using data from 8,725 real banner advertisements. It is one of the first empirical studies to examine banner advertising effectiveness (measured by click-through rates) and also one of the first to examine the differences between business-to-business (B2B) and business-to-consumer (B2C) banner advertisements.The authors acknowledge the financial and data support of Michael Moore and Marianna Dizik in the conduct of this study.

Content elements examined include the use of incentives and emotional appeals. Design elements examined include the use of interactivity, color, and animation. Results suggest that content and design elements do not work the same way for B2B and B2C banner advertisements.

Banner advertising: Measuring effectiveness and optimizing placement, Sherman, L., & Deighton, J. (2001). Banner advertising: Measuring effectiveness and optimizing placement. Journal of Interactive Marketing, 15(2), 60-64. The article describes how one company improved banner advertising response rates by taking advantage of the medium’s rich data to optimize placement. The study identified Web surfers who were frequent visitors to the banner advertiser’s site. It then identified 100 Websites that these surfers tended also to visit. These sites were cluster analyzed to yield site genre definitions (affinities). In this manner a model was built to identify a group of affinities whose visitors were disproportionately likely to respond to banner advertising. These predictions were tested by placing banners on sites forecast to perform well. The average cost per response was nine times lower for sites predicted to belong to high affinity groups than low groups. © 2001 John Wiley & Sons, Inc. and Direct Marketing Educational Foundation, Inc.

Assessing the effects of animation in online banner advertising: Hierarchy of effects model, Yoo, C. Y., Kim, K., & Stout, P. A. (2004). Assessing the effects of animation in online banner advertising: Hierarchy of effects model. Journal of interactive advertising, 4(2), 49-60. The present study attempts to examine the effects of animated banner ads, as well as the moderating effects of involvement, on each stage of the hierarchy of effects model, and to explore the applicability of the hierarchy of effects model to the banner advertising environment through an online experiment. The results provide support for the notion that animated banner ads prompt better advertising effects than do static ads. Animated banner advertising has better attention-grabbing capabilities, and generates higher recall, more favorable Aad, and higher click-through intention than static ads. Furthermore, an individual’s product involvement moderates the effects of animated banner advertising on recall, Aad, and click-through intention. However, the study does not provide solid evidence of the feasibility of the traditional hierarchical model (Cognition -> Affect -> Behavior) in the online banner advertising environment. Several implications and limitations of these results are discussed, and future research is suggested.

Processing of animation in online banner advertising: The roles of cognitive and emotional responses, Yoo, C. Y., & Kim, K. (2005). Processing of animation in online banner advertising: The roles of cognitive and emotional responses. Journal of Interactive marketing, 19(4), 18-34. Marketers often compete to incorporate fast-moving images in their online banner ads to break through the ad clutter, in the hope for a positive perception of the ads. However, the findings of this study suggest that this strategy may not work. An experiment was designed to explore the effects of the degree of animation on memory and attitudes toward ads. The results showed inverted U-shaped relationships between the level of animation and both recognition rates and A <INF>ad</INF>, suggesting the existence of unintended negative effects of highly animated online banner ads. Under high-animation conditions, subjects experienced negatively valenced thoughts and unpleasant feelings, which negatively influenced A <INF>ad</INF>. Also, subjects were highly aroused, as indicated by the increased level of emotional intensity; this arousal inhibited subjects’ ad recognition performance. These findings show different processing mechanisms under different animation levels, and suggest that marketers should exercise caution when using animation in their ads.

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