When a large retailer like Safeway or Walgreens puts a circular in your Sunday paper or mailbox, its goal is to increase overall store traffic and sales and enhance their store’s image. These stand-alone circulars are known as feature advertisements, a form of cooperative advertising between retailers and manufacturers. Manufacturers pay retailers to feature their products, while retailers coordinate ad placement and combine the manufacturer’s products with their own private labels and unbranded products. Feature ads often appear in the U.S. as stand-alone mailings or as supplements in the local Sunday newspaper.
Manufacturers and retailers invest significantly in feature ads— about $3 billion in the U.S. in 2003 —so maximizing their effectiveness is an important goal for marketers.
Michel Wedel, PepsiCo Professor of Consumer Science, and Jie Zhang, assistant professor of marketing, examine the way that different design characteristics affect consumer attention to feature ads in a recent paper, “Optimal Feature Advertising Design under Competitive Clutter.” Wedel and Zhang, with co-author Rik Pieters of the University of Tilburg (the Netherlands), analyzed the effects of five key design elements of feature ads to determine how to optimize consumer attention to the ads.
The study uses a large-scale dataset of attention to over 1,100 feature ads, provided by Verify International, a research company in the Netherlands. Consumer attention to the ads was monitored with eye-tracking technology. Modern eye-tracking devices, such as the Tobii eye-tracker that we have at the Netcentric Behavioral Lab at the Smith School of Business, consist of three cameras hidden in the lower edge of a large desktop monitor which track the head and eye movements of the person sitting at the monitor. As study participants viewed the feature advertisements, the eye-tracker recorded how participant’s eyes moved and how long they gazed at each element of an ad.
Because multiple ads appear in the same space, all competing for viewer attention, feature ads are particularly prone to the negative effects of visual clutter. This paper is the first to quantify—and thus model the effects of—such competitive clutter on feature ads.
The authors drew on attention research literature to create two novel measures of visual clutter. Target Distinctiveness measures the extent to which the element being viewed is different from all other elements on the page, and Distractor Heterogeneity describes how similar all other elements on the page are to one another. Using these two measures, the authors constructed a model to examine the surface size effects of five design elements—brand, text, pictorial, price, and promotion—and calculated how to maximize the effectiveness of the entire ad display.
One of the problems faced by designers of feature ads is the competing demands of retailers and manufacturers. Manufacturers want the ad for their own product to be most prominent on the page, but retailers have to balance attention to the products of each manufacturer as well as their own unbranded or private label products. Maximizing the total attention to the ad display meets the needs of both retailers and manufacturers, because it leads to higher total attention to all individual ads on the page.
“The ad display should be segmented more effectively,” said Wedel. “You want people to find the ad more quickly and look at it longer.”
The pictorial element is almost always too large relative to the other elements of the ad. Because pictorial has a big impact, it does not need to take much space to be effective. Text should also be given less space in an ad, but for the opposite reason. Wedel and Zhang found that text has little effect in attracting consumer attention, so there is no point in wasting valuable ad space on it. Reducing the relative size of the pictorial and text elements frees up space in the ad for the elements that need to be larger, like brand, price and discount information.
Wedel and Zhang’s recommendations can be implemented without requiring manufacturers and retailers to spend additional money. They derived the optimal designs with the ad sizes unchanged, so the placement cost of each ad is the same. “Our recommendations can be implemented at no additional costs, so retailers and manufacturers get the benefits without having to pay a penny more,” Zhang says.
Then there is the multi-billion dollar question: do more eyeballs on the page really translate to higher sales in the store? Wedel and Zhang are exploring this question for a future paper.
“Optimal Feature Advertising Design Under Competitive Clutter” will be published in Management Science. For more information about this research, contact email@example.com or firstname.lastname@example.org.
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