• United States



by No Analyst or Consultant

Banner Ads Click with Consumers

Nov 16, 20049 mins
CSO and CISOData and Information Security

By Pradeep K. Chintagunta,

Jean-Pierre Dubé,

and Puneet Manchanda

Banner advertising helps companies retain customers by bringing them back to a company’s Web site faster and encouraging them to spend more.

Total spending on Internet advertising now exceeds spending on some traditional media, but despite the quick adoption of online marketing by many firms, remarkably little is known about the potential payoffs of such efforts.

Most online advertising exists in the form of banner ads, which combine graphics, text, and a link to an advertiser’s Web site. Consumers access the advertiser’s site by clicking on the banner ad, which is referred to as “clickthrough.” In the early days of e-commerce, the fact that consumer behavior in response to advertising could be measured instantaneously and objectively by calculating the clickthrough rate was seen as an exciting development. However, clickthrough rates typically have been less than one percent of all exposures. In addition, these rates only measure visits to a site, ignoring actual purchasing behavior. Previous research has shown that few visits translate into actual purchases.

University of Chicago Graduate School of Business professors Pradeep K. Chintagunta, Jean-Pierre Dubé, and Puneet Manchanda, together with doctoral student Khim Yong Goh suggest that, as in traditional advertising, exposure to banner ads may result in purchase behavior after a temporal gap.

“Most theories of advertising note that the effects of advertising are not immediate,” says Manchanda. “We therefore wanted to link individual exposure to banner advertising to individual behavior while allowing for a temporal gap. Our approach expands upon the work of previous studies that have only documented attitudinal changes as a function of exposure to Internet advertising.”

The authors report their findings in their recent study, “The Effects of Banner Advertising on Consumer Inter-purchase Times and Expenditures in Digital Environments.”

The authors find that banner ads are effective for bringing existing customers back to a Web site sooner to make additional purchases. Thus, in any given period of time, current customers who were exposed to banner advertising are likely to spend more money than customers who were not. The authors also suggest that the industry-wide practice of judging banner ads by the number of clicks they generate understates the effectiveness of banner ad campaigns.

“If you just measure clicks, you are not capturing the real effect of advertising,” says Dubé. “What you want to see is whether people are purchasing items.”

Even though banner ads are typically regarded as doorways to bring in new customers, the long-term viability of a Web site depends on its ability to retain customers. Many industry studies have shown that retaining current customers, relative to acquiring new customers, is more profitable to a firm over the lifetime of the customer. For online firms, the question then becomes whether banner advertising can modify the behavior of repeat customers as they become more experienced with the firm’s Web site.

“Online advertising budgets have been shrinking since the dot-com bust,” says Dubé. “It’s a known fact that it’s cheaper to market to a current customer than a new customer. Our study shows you can use banner ads to stimulate business in your repeat customer base.”

Following the Cookie Trail

What distinguishes Internet advertising from traditional advertising is the ability to match individual advertising exposure to individual consumer behavior. If a consumer sees a television commercial for a product, it is very difficult to then match up the commercial with whether or not a consumer purchases the advertised product in a store. The Internet allows researchers to put the whole story together, from awareness building through actual purchasing, going beyond what is possible in the traditional world.

The technology that makes this possible is based on small files called “cookies” that are stored on an individual consumer’s computer once they visit a Web site. By keeping track of cookies, firms have detailed data on when, where, and to how many ads each individual cookie was exposed. This advertising data can then be matched up with purchases made via that computer. Advertisers can therefore return to their clients and let them know which cookie actually resulted in a purchase, and how many dollars that cookie generated.

Beyond Clicks

Chintagunta, Dubé, Manchanda, and Goh use data from an Internet-only firm that sold healthcare and beauty products as well as nonprescription drugs. Their data spans a period of three months during the third quarter of 2000. Most data used for studying online environments feature browsing behavior only. Their new dataset is unique because the authors are able to measure individual stimulus (advertising) as well as response (purchase visits and dollars spent).

The majority of the company’s banner ads focused on brand-building, and typically consisted of the name of the Web site and a line describing the benefits of purchasing from the site. More than 80 percent of the company’s advertising activity during this period was on portal and alliance Web sites such as Yahoo!, America Online,,,, and E*Trade. A given banner ad typically appeared on these sites over several weeks.

To ensure that they only included repeat customers in their analysis, the authors used data from customers that had made at least two purchases from the site. The final sample consisted of 2,192 cookies.

Industry measures such as clickthrough only account for direct action, rather than measuring the awareness building that takes place over an advertising campaign. The authors therefore allowed for the possibility of customers seeing an ad, mulling it over, and then returning to make a purchase after a period of time.

The behavior of repeat customers was measured using statistical models that captured purchase timing (when to visit) and purchase expenditure (how much to spend on a purchase visit). The authors measured the effect of the following advertising variables: the time between purchases and dollars spent; the amount of advertising exposure; the time since consumers last saw an ad; where they saw the ad; and the ad copy and graphics they saw for each banner (the “creative”).

The authors find that seeing the ads more frequently brought customers back to shop sooner. The more recently consumers saw an ad, the faster they came back to buy. Exposure to banner ads at more Web sites also had a similar effect. However, exposure to a higher number of ads with different creative treatments delayed consumers’ return to the Web site. For purchase expenditure, the effect of advertising is small. Instead, the best predictor of current expenditure tended to be the amount spent on the last shopping occasion.

The authors also find differences among the shopping behavior of repeat customers. Their data and statistical model indicate that the Web site’s customers can be classified into three different segments. Customers in these segments are affected differently by the frequency of banner advertising, how recently they saw the banner ads, and the monetary value of their past purchases. The largest segment consists of loyal but infrequent shoppers, followed by a segment comprised of relatively frequent purchasers. There is also a small segment of impulse shoppers who tend to shop on the same day that they are exposed to a banner ad.

Overall, for most consumers in the sample, the authors find evidence of a temporal lag between exposure and action. They speculate that this gap exists because banner advertising acts as a brand building tool and reminds consumers to visit a site.

Ingredients of a Good Campaign

The study provides insights into the nature of consumer response to banner advertising. First, the authors find evidence of temporal differences between exposure and behavior for a majority of the consumers in the sample. This result implies that managers can correctly evaluate the effectiveness of advertising campaigns only if they account for this temporal gap.

Second, the time since last exposure and the number of creatives has a much larger effect on purchase timing relative to the number of exposures. Regarding advertising copy, exposing the same consumer to several unrelated creatives may be less beneficial than a single creative, assuming that all the creatives are of the same quality.

“More companies are starting to realize that redundancy is a good thing for their online advertising campaigns,” says Dubé. “If you have a single, effective message, it’s easier for consumers to extract pertinent information from your banner ad even as they are inundated with ads from other sites.”

In terms of the timing of advertising, it may be more useful to expose consumers to a series of evenly spaced ads rather than massed exposures. Given the strong same day purchase effect resulting from advertising exposure, advertisers can potentially use banner advertisements to smooth out sales and run special promotions.

Finally, there seem to be strong positive benefits from ensuring that customers are exposed to the same advertisement across many Web sites.

“For the category of frequently purchased, nonseasonal products in our study, steady and consistent advertising on many different Web sites is the right managerial approach,” says Manchanda.

In terms of the dollars spent on a visit, exposure to a variety of creatives increases dollars spent while advertising across many sites decreases dollars spent. However, in contrast, exposure to more creatives delays repeat visits while exposure on more sites brings consumers back sooner. Therefore, managers need to optimize the number of creatives and advertising sites by making the trade-off between quicker visits and lower expenditure per visit, or slower visits and higher expenditure per visit.

** Editor’s Note: This article first appeared in the June 2004 issue of Capital Ideas, a magazine that summarizes research conducted by the faculty of the University of Chicago Graduate School of Business.

Pradeep K. Chintagunta is Robert Law Professor of Marketing at the University of Chicago Graduate School of Business.

Jean-Pierre Dubé is assistant professor of marketing at the University of Chicago Graduate School of Business.

Puneet Manchanda is associate professor of marketing at the University of Chicago Graduate School of Business.