When Predicting Other People's Preferences, You're Probably Wrong

Marketers, job hunters and people looking for mates are all called upon to predict behavior—and many are probably wrong. The reason: We erroneously make assumptions about what others will like and dislike based on their previous choices, according to new research by Kate Barasz, Tami Kim, and Leslie John.
by Carmen Nobel

The Bachelor is a wildly popular reality dating game show on which 28 women compete for the hand of a single man. Along with flirting and fighting and engaging in feats of derring-do, many of the competitors spend ample time confessing insecurities to the camera.

Leslie K. John admits that she has been watching the show long enough to notice a pattern in the self-doubt: The women tend to fret when they see the supposed man of their dreams bonding with women who are dissimilar to themselves. “One thing that’s commonly said is, ‘Well, if he’s into her, there’s no way he could be into me,’” says John, an assistant professor in the Negotiation, Organizations, and Markets unit at Harvard Business School. “They assume the Bachelor can only like one type of woman.”

“When you like one lake, people infer that you hate cities”

It turns out those fretful competitors support new scientific findings about presuming preferences. When predicting other people’s tastes, we tend to erroneously assume that liking one thing precludes enjoying another, dissimilar option, according to a recent set of studies by researchers at Harvard Business School, which were led by HBS doctoral candidate Kate Barasz and conducted in collaboration with John and doctoral candidate Tami Kim. Their research is detailed in their paper The Role of (Dis)similarity in (Mis)predicting Others’ Preferences, which will appear in a forthcoming issue of the Journal of Marketing Research.

The findings have important implications for anyone looking to impress others, for those who are tasked with forecasting consumer behavior, or for salespeople who consult with customers on prospective purchases. In short, it’s dangerous to predict what others will like, and faulty assumptions can lose you a new job, a sale, or, yes, even a potential mate.

“When you’re observing another person’s choice, the choice itself becomes very diagnostic,” says Barasz, who graduated in May and will soon join the faculty of the IESE Business School in Barcelona. “It becomes the only piece of information that you have to go on, and you kind of anchor to that choice,” Barasz explains. “So once I see that you wearing a gray sweater, maybe I assume you don’t like bright floral prints.”

When this man sees this woman buying a casual yellow shirt, does he assume she doesn't like wearing fancy red dresses, too? Research shows that when predicting other people’s tastes, we tend to assume that liking one thing precludes enjoying another, dissimilar option. (Photo: iStockphoto)

For example, a real estate agent might forego the opportunity to show a mid-century modern home to a client who previously showed interest in a Tudor cottage. Or a bookseller might only recommend books that are similar to previous purchases. Or if someone “likes” a fancy Manhattan hotel on Facebook, her Facebook friends might not invite her on an overnight hike in the woods. Or, more seriously, a physician might decide on an aggressive treatment plan for a terminally ill patient, based on the patient’s previous choices—neglecting to discuss more palliative options.

And if you knew nothing of Leslie John other than her guilty pleasure of watching The Bachelor, you’d probably predict that she likes watching its counterpart, The Bachelorette, too. But you’d be less likely to predict that John also enjoys conducting social science research at Harvard.


The researchers conducted five studies to determine when and why people assume that others are incapable of liking dissimilar things.

In the first study, 205 participants considered Facebook status updates of a hypothetical friend, Joe Smith. Half the participants saw the status, “Just booked a vacation! Headed to a lake.” The other half saw the less descriptive post, “Just booked a vacation!” Those who knew where Joe was headed were much more likely to decide that he didn’t like city vacations.

“When you like one lake, people infer that you hate cities,” Barasz says. “And when you hate one lake, people infer that you love cities.”

In the second study, 297 participants read a scenario about a consumer named Jane, who was choosing between two products, Widget A and Widget B. Both widgets could be described by five attributes: price, size, shape, function, and quality. (Participants received no information about what the widgets actually were.)

Source: The Role of (Dis)similarity in (Mis)predicting Others’ Preferences

As in the first study, participants were assigned to one of two conditions. In the “similar” condition, they learned that the two widgets shared four out of five attributes in common; in the “dissimilar” condition, the widgets shared only one attribute. In both conditions, Jane always chose Widget A.

Armed only with that information, participants had to predict how Jane felt about Widget B.

The majority of participants in the dissimilar condition—61.5 percent—predicted that Jane disliked Widget B, compared with only 14.8 percent of participants in the similar condition. And when asked what Jane would do if Widget A was sold out, participants in the dissimilar condition were much less likely to predict that Jane would settle for Widget B instead.


Having established that people don’t believe others can like dissimilar things, the researchers conducted two studies to investigate the accuracy of that belief.

In one study, some participants indicated a preference for one of two movies, a five-star thriller or a five-star documentary, while an assigned partner observed the preferences.

Next, the choice-making participants were faced with this scenario: “Suppose that your first-choice movie is no longer available. Which movie would you select instead?”

Most of the observers assumed—often incorrectly—that their partners would prefer a lower-quality movie in the first-choice genre to a higher-quality movie in a different genre. While 68.5 percent of participants chose the five-star different-genre option for themselves, only 39.3 percent of the observers predicted their partners would make that choice.

The observers did a better job of predicting their partners’ alternate preferences when the choices were relatively similar.

In the fourth study, when given the choice of two movies in similar genres (e.g., an action-adventure flick and a thriller), 73.3 percent of participants opted for the five-star movie in the alternate genre rather than the three-star option in the preferred genre; 68.7 percent of the observers correctly predicted that choice.

When considering sets of very different genres (e.g., documentary vs. comedy), the majority of participants—64.2 percent—still preferred the higher-quality dissimilar choice over the lower-quality similar choice. However, most observers failed to predict their partners’ preference for quality over similarity: Only 18.1 percent predicted that their partners would select the higher-quality dissimilar movie.


In the fifth and final study, the researchers showed why people mistakenly assume other people dislike dissimilar vacations, widgets, movie options, and so on.

The study began with 196 participants imagining that an average consumer wanted to create a five-song playlist from five specific musical genres. Their task: Predict how many songs the consumer would pick from each genre.

Next, in a callback to the first study, participants had to predict how much an unnamed person would enjoy a mountain vacation and a city vacation, based on the knowledge that the person had enjoyed a previous vacation at a lake. As the researchers expected, participants who designed the most homogeneous playlists were also most likely to assume that the lake vacationer liked mountains but hated cities.

“As our account suggests, people default to the belief that others have relatively narrow and homogeneous preferences, and thus predict that dissimilar items are disliked,” the researchers write in “The Role of (Dis)similarity in (Mis)predicting Others’ Preferences.”


So what should we do to correct this widespread prediction error? For starters, we can be mindful of the researchers’ findings.

“From a firm’s perspective, you should never fill in the blank about an option you don’t necessarily know about,” Barasz says. “Maybe you can empirically show that people who drive Toyota Priuses don’t like Hummers. But in more nuanced cases it might behoove you to just ask consumers, ‘Do you like this thing?’ That way you don’t jump to any conclusions about it.”

It’s also important to keep in mind that people are likely to jump to conclusions about you—in job interviews, for instance. “Imagine that if in small talk at the beginning, which is seemingly innocuous, you divulge something like ‘I like watching The Bachelor,’” John says. “You could seriously undermine your prospects. Even though your enjoyment of The Bachelor does not preclude your liking of high-quality content, Kate’s finding suggests that the interviewer might infer that you’re shallow … that you do not like intellectual programming, for example.”

Finally, the research findings provide a weapon against self-doubt.

John recalls a recent conversation with HBS colleague Mike Norton, who told her that she and another colleague had notably different approaches to their work. “I was panicking because I thought, ‘Oh no, he can only like one of us! He can only like one of our styles!’” she laughs. “But then I remembered this research and thought, ‘Whew, so maybe he doesn’t hate me after all.”

Related Reading

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About the Author

Carmen Nobel is the senior editor of Harvard Business School Working Knowledge.

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