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Research by Michel Wedel and Jie Zhang
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
mwedel@rhsmith.umd.edu or
jiejie@rhsmith.umd.edu.
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