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Businesses rely on solid marketing strategies to boost
sales yet the tools used to evaluate these strategies often provide
misleading results, leaving managers with the inability to accurately
measure how they can get the best bang for their marketing buck."Companies really need to pay attention to the effectiveness of their marketing instruments"
Thomas J. Steenburgh, an associate professor in the Marketing Unit at
Harvard Business School, has developed a new analytical tool that more
accurately measures the effectiveness of various marketing efforts. He
created the model with Qiang Liu, an assistant professor of marketing at
Purdue University, and Sachin Gupta, the Henrietta Johnson Louis
Professor of Management and professor of marketing at Cornell
University.
Steenburgh believes that the model could help brand managers determine which marketing strategies work best to invest in.
"Companies really need to pay attention to the effectiveness of their
marketing instruments," Steenburgh says. "They need to look at whether
they're creating new customers or whether they're just drawing customers
away from competitors. It's a fundamental question in the field, and
this model helps measure that."
The ideal mix
When planning marketing campaigns, brand managers have a wide
portfolio of weapons to draw on, including in-store merchandising,
advertising, coupons and sweepstakes, trade promotions, prices, and
deployment of a direct sales force. The key is crafting the right mix
between them—the ideal brew needed to achieve sales and market share
goals.
The trick is that each marketing effort affects consumer behavior in
different ways, and also prompts different types of responses from
competitors. Some activities result in expanding demand across an entire
category of products. Take for example the "Got Milk" advertising
campaign, which is intended to increase demand for a category of
products, milk. In contrast, an advertisement that points out how one
brand is better than a competitor's brand has the goal of encouraging
consumers to switch products within a particular category.
If a business seeks to grow demand for a category of products, the
effort may not elicit much of a reaction from its competitors; after
all, if the entire category grows the rising tide lifts all boats. But a
competitor's reaction is typically quite different when a company
attempts to move in on its market share, perhaps by offering price
discounts. Since this strategy is viewed as more threatening, the
competitor can be expected to retaliate with prejudice—often by firing
off a campaign to win back many more customers than it lost.
"We know that retaliation happens and that companies worry about
that," Steenburgh says. "But nobody benefits when both companies are
retaliating. One effort just offsets the other."
Measuring the different effects of these marketing strategies can
help brand managers make the right decisions about which strategies to
use in their marketing mix. Steenburgh, Liu, and Gupta argue that the
tools that have been used in the past to analyze the effectiveness of
different marketing activities—called discrete choice models—can skew
the results and misguide brand managers.
Traditional discrete choice models—logit, nested logit, and probit,
for example—are flawed because they make it appear as if all marketing
activities produce the same results, the researchers contend. In
reality, differences between various marketing instruments are often
significant. The cause of these flawed results comes from what is called
the Invariant Proportion of Substitution (IPS) property, which implies
that the proportion of demand generated by taking business away from a
competitor is the same, no matter which marketing activity is used.
"These models get run all the time in academics," Steenburgh says.
"There has been some talk at conferences where there seems to be an
understanding that these models are too restrictive."