The internet has dramatically expanded the modern marketer’s tool kit, in large part because of one simple but transformative development: digital data. With users regularly sharing personal data online and web cookies tracking every click, marketers have been able to gain unprecedented insight into consumers and serve up solutions tailored to their individual needs. The results have been impressive. Research has shown that digital targeting meaningfully improves the response to advertisements and that ad performance declines when marketers’ access to consumer data is reduced. But there is also evidence that using online “surveillance” to sell products can lead to a consumer backlash. The research supporting ad personalization has tended to study consumers who were largely unaware that their data dictated which ads they saw. Today such naïveté is increasingly rare. Public outcry over company data breaches and the use of targeting to spread fake news and inflame political partisanship have, understandably, put consumers on alert. And personal experiences with highly specific ads (such as one for pet food that begins, “As a dog owner, you might like…”) or ads that follow users across websites have made it clear that marketers often know exactly who is on the receiving end of their digital messages. Now regulators in some countries are starting to mandate that firms disclose how they gather and use consumers’ personal information.
The latter outcome seems more likely if marketers continue with
a business-as-usual approach. One study revealed
that when a law that required websites to inform visitors of covert tracking
started to be enforced in the Netherlands, in 2013, advertisement click-through
rates dropped. Controlled experiments have found similar results.
Some firms have done better than others in anticipating how
customers will react to personalization. Amazon features shopping ads
throughout its site, making product recommendations based explicitly—and often
conspicuously—on individual users’ search data, without seeming to draw any
consumer ire whatsoever. However, in a now-infamous example, when Target
followed a similar practice by creating promotions that were based on
individual shoppers’ consumption data, the response was not so benign. The
retailer sent coupons for maternity-related products to women it inferred were
pregnant. They included a teenager whose father was incensed—and then abashed
to discover that his daughter was, in fact, expecting. When the New York Times reported the incident, many
consumers were outraged, and the chain had a PR problem on its hands.
Similarly, Urban Outfitters walked back the gender-based personalization of its
home page after customers complained. “We saw customer frustration at being
targeted outweigh any benefit,” Dmitri Siegel, the marketing executive in
charge of the initiative, concluded in an interview with the Times.
For the consumer who prefers relevant ads over irrelevant ones
(an ad-free experience is not realistic in today’s ad-supported web landscape),
it’s important that marketers get the balance right. Digital marketers need to
understand when the use of consumer data to personalize ads will be met with
acceptance or annoyance so that they can honor consumers’ expectations about
how their information should be used. The good news is that social scientists
already know a lot about what triggers privacy concerns off-line, and new
research that we and others have performed demonstrates that these norms can
inform marketers’ actions in the digital sphere. Through a series of
experiments, we have begun to understand what causes consumers to object to
targeting and how marketers can use personalization while respecting people’s
privacy.
The Privacy Paradox
People don’t always behave logically when it comes to privacy.
For example, we often share intimate details with total strangers while we keep
secrets from loved ones. Nevertheless, social scientists have identified
several factors that predict whether people will be comfortable with the use of
their personal information. One of these factors is fairly straightforward—the
nature of the information. Common sense holds that the more intimate it is (data
on sex, health, and finances is especially sensitive), the less comfortable
people are with others knowing it.
A second, more nuanced factor involves the manner in which
consumers’ personal information changes hands—what social scientists call
“information flows.” One such norm is, to put it colloquially, “Don’t talk
about people behind their backs.” While people may be comfortable disclosing
personal information directly (what scientists call “first-person sharing”),
they may become uneasy when that information is passed along without their
knowledge (what we term “third-party sharing”). If you learned that a friend
had revealed something personal about you to another, mutual friend, you’d
probably be upset—even though you might have no problem with both parties
knowing the information. It can also be taboo to openly infer information about
someone, even if those inferences are accurate. For example, a woman may inform
a close colleague of her early-term pregnancy, but she’d likely find it
unacceptable if that coworker told her he thought she was pregnant before she’d
disclosed anything.
In our recent studies we learned that those norms about
information also apply in the digital space. In our first study, we collected a
list of common ways in which Google and Facebook use consumers’ personal data
to generate ads. We then asked consumers to rate how acceptable they found each
method to be, and—employing a statistical technique called factor
analysis—identified clusters of practices that consumers tended to dislike,
which mirrored practices that made people uncomfortable off-line:
- obtaining information outside the website on which an ad appears, which is akin to talking behind someone’s back
- deducing information about someone from analytics, which is akin to inferring information.
Next, we wanted to see what effect adherence to—or violation
of—privacy norms would have on ad performance. So we divided participants in
our study into three groups. In a simulation of acceptable, first-person
sharing, one group first browsed a website; on that same site we later
displayed an ad accompanied by the disclosure “You are seeing this ad based on
the products you clicked on while browsing our website.” In a simulation of
unacceptable, third-party sharing, another group browsed a website and then
visited a second site, where we displayed an ad accompanied by the disclosure
“You are seeing this ad based on the products you clicked on while browsing a
third-party website.” The final group served as a control; like the other groups,
these participants engaged in a browsing task and were then shown a targeted
ad, but without a message. In all groups, we measured interest in purchasing
the advertised product as well as the likelihood that participants would visit
the advertiser’s website. Additionally, to understand how these three ad
scenarios affected consumers’ attitudes, we asked all participants which they
valued more: the personalization of ads or the privacy of their data.
If people dislike the way their
information is shared, purchase interest drops.
We found that when unacceptable, third-party sharing had
occurred, concerns about privacy outweighed people’s appreciation for ad
personalization. Those attitudes in turn predicted interest in purchasing,
which was approximately 24% lower in the group exposed to unacceptable sharing
than in both the first-party sharing and the control groups—a clear indication
of backlash.Source: Harvard Business Review
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