When skimming through his Facebook feed one day, Jiwoong Shin was taken aback when he saw an advertisement related to heart disease. “It freaked me out,” says the Yale SOM professor of marketing. “I know Facebook knows a lot about me, so I began to wonder—is this something I need to worry about?”
Shin got a clean bill of health from his doctor. As it turned out, the ads were likely a result of searches he’d done for a course he was teaching at the time. But the incident led him to wonder about his own reaction to the ad. He often encountered—and ignored—pharmaceutical ads on primetime television. What was different about the advertisement on his social media feed? “Where I see an ad makes me respond differently to it, because I know that certain channels are targeted,” Shin says. “It’s an implicit recommendation.”
In the pre-personalization world, advertisements largely served to expose consumers to products. Watching a commercial for air fryers, for instance, might tell a consumer about a category of kitchen appliances that they could explore purchasing. But ads that target people based on their personal information change the rules. Firms today have increasingly granular customer data; indeed, they can sometimes know more about customers’ needs and wants than consumers know themselves. In fact, a targeted ad can enhance consumers’ interest in a product category that they didn’t even know existed.
In a new study forthcoming in Marketing Science, Shin and Jungju Yu of the City University of Hong Kong propose a theoretical model to “rationalize this interesting phenomenon,” Shin says, looking at how a consumers’ response to an ad differs depending on whether or not the ad is targeted, and analyzing the implications for how companies should promote a product. They find that consumers’ awareness of targeting has an unexpectedly strong influence on the power of advertising. When a customer knows an ad is targeted, they see and respond to it differently than they do otherwise—and that altered response is important for companies to factor in when choosing how to promote a product, Shin says.
In the model, consumers knew the advertisements they saw were personalized in some way, and two competing firms were placing commercials while knowing of consumers’ awareness. Shin and Yu played out various scenarios of how consumers inferred information about a product or category of products, and their subsequent choices and purchases.
They found that when personalization was highly accurate, it created a conflict: when firms knew the odds of an ad resulting in sale were higher because of personalization, they invested more in targeted ads. But because the mere fact of being targeted enhances consumers’ interests in a product category, the targeted consumers are more willing to seek out a competitor’s product instead of buying the one in the ad also increased.
For instance, an advertisement for a phone app to scan documents and turn them into PDF files piqued Shin’s attention. He didn’t know such an app existed, and downloaded the one advertised to him. He found that particular app to be cumbersome, but learning that such tools existed led him to eventually buy an app produced by a different firm.
When ads are customized based on people’s interests, consumers pay closer attention to the firm—but they’re also more likely to look for alternatives within the product category.
In this instance, the product he eventually purchased wasn’t something advertised to him. But the maker still made a sale—thanks to a competitor having invested in ads targeted to Shin. “People initially might have no idea they need something, and the advertisement is a signal that this category of things is something they need,” he explains. “The ad educates customers, who search around that product category and may buy from a competitor, who is effectively freeriding.”
In targeting Shin, the original advertiser took the risk that another seller could benefit from its ad. But the possibility of this sort of free riding was balanced by the potential payoff of being first, especially if the targeting accuracy was fairly high. “Catching the consumer early is better—if you can preempt their demand before they search for anything else, they have less incentive to search,” Shin explains.
Consumers’ knowledge of targeting plays a key role too. When ads in a particular scenario are customized based on people’s interests, according to the model, consumers tend to draw positive conclusions about the product category as a whole. They pay closer attention both to the firm itself and to the category—just as Shin did, when he tried the scanner app advertised to him. They’re also more likely to look for alternatives within the product category, engaging in time-consuming searches and product comparisons. This increased engagement and research creates a spillover effect, so that targeted ads result in awareness far beyond the exposure created by traditional advertising.
“Just the fact that a person is targeted makes a huge difference,” Shin says. “It has important implications for advertising strategy for both firms and consumers.”
“Just because a company is targeting you, doesn’t mean it’s the best product—or even that the product is necessary.”
The researchers further find that companies advertising niche products with a narrow market might find that very precisely targeted ads are worth the cost. But if a product is likely to appeal to a broad range of consumers, targeting ads to those most likely to make a purchase can be trickier—and more likely to benefit a competitor in the same category. Because such products are tougher to effectively target to potential buyers, a mass market approach may prove more effective, according to Shin.
For consumers, the message is simple: a targeted ad is still an advertisement—not a recommendation—no matter how personalized it is, Shin says. “Just because a company is targeting you, doesn’t mean it’s the best product—or even that the product is necessary.”