Kate Barasz

Article | Cognition

I Know Why You Voted for Trump: (Over)inferring Motives Based on Choice

Kate Barasz, Tami Kim and Ioannis Evangelidis

People often speculate about why others make the choices they do. This paper investigates how such inferences are formed as a function of what is chosen. Specifically, when observers encounter someone else's choice (e.g., of political candidate), they use the chosen option's attribute values (e.g., a candidate's specific stance on a policy issue) to infer the importance of that attribute (e.g., the policy issue) to the decision-maker. Consequently, when a chosen option has an attribute whose value is extreme (e.g., an extreme policy stance), observers infer-sometimes incorrectly-that this attribute disproportionately motivated the decision-maker's choice. Seven studies demonstrate how observers use an attribute's value to infer its weight-the value-weight heuristic-and identify the role of perceived diagnosticity: more extreme attribute values give observers the subjective sense that they know more about a decision-maker's preferences, and in turn, increase the attribute's perceived importance. The paper explores how this heuristic can produce erroneous inferences and influence broader beliefs about decision-makers.

Keywords: self-other difference; social perception; inference-making; preferences; consumer behavior; prediction; prediction error; Decision Choices and Conditions; Perception; Behavior; Forecasting and Prediction;

Citation:

Barasz, Kate, Tami Kim, and Ioannis Evangelidis. "I Know Why You Voted for Trump: (Over)inferring Motives Based on Choice." Cognition (in press). View Details

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Article | Journal of Consumer Research

Why Am I Seeing this Ad? The Effect of Ad Transparency on Ad Effectiveness

Tami Kim, Kate Barasz and Leslie K. John

Given the increasingly specific ways marketers can target ads, many consumers and regulators are demanding ad transparency: disclosure of how consumers’ personal information was used to generate ads. We investigate how and why ad transparency impacts ad effectiveness. Drawing on literature about offline norms of information-sharing, we posit that ad transparency backfires when it exposes marketing practices that violate norms about “information flows”—consumers’ beliefs about how their information ought to move between parties. Study 1 inductively shows that consumers deem information flows acceptable (or not) based on whether their personal information was: 1) obtained within versus outside of the website on which the ad appears and 2) stated by the consumer versus inferred by the firm (the latter of each pair being less acceptable). Studies 2 and 3 show that revealing unacceptable information flows reduces ad effectiveness, which is driven by increasing consumers’ relative concern for their privacy over desire for the personalization that such targeting affords. Study 4 shows the moderating role of platform trust: when consumers trust a platform, revealing acceptable information flows increases ad effectiveness. Studies 5a and 5b, conducted in the field with a loyalty program website (i.e., a trusted platform), demonstrate this benefit of transparency.

Keywords: Online Advertising; Customization and Personalization; Information; Trust; Performance Effectiveness;

Citation:

Kim, Tami, Kate Barasz, and Leslie K. John. "Why Am I Seeing this Ad? The Effect of Ad Transparency on Ad Effectiveness." Journal of Consumer Research 45, no. 5 (February 2019): 906–932. View Details

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Article | Harvard Business Review

Ads That Don't Overstep: How to Make Sure You Don't Take Personalization Too Far

Leslie John, Tami Kim and Kate Barasz

Data gathered on the web has vastly enhanced the capabilities of marketers. With people regularly sharing personal details online and internet cookies tracking every click, companies can now gain unprecedented insight into individual consumers and target them with tailored ads. But when this practice feels invasive to people, it can prompt a strong backlash. Marketers today need to understand where to the draw the line. The good news is that psychologists already know a lot about what triggers privacy concerns off-line. These norms—and the authors’ research—strongly suggest that firms steer clear of two ad-targeting techniques generally disliked by consumers: using information obtained on a third-party site rather than on the site on which an ad appears, which is akin to talking behind someone’s back; and deducing information about people (such as a pregnancy) from analytics when they haven’t declared it themselves. If marketers avoid those tactics, use data judiciously, focus on increasing trust and transparency, and offer people control over their personal data, their ads are much more likely to be accepted by consumers and help raise interest in engaging with a company and its products.

Keywords: Online Advertising; Customization and Personalization; Information; Customers; Attitudes;

Citation:

John, Leslie, Tami Kim, and Kate Barasz. "Ads That Don't Overstep: How to Make Sure You Don't Take Personalization Too Far." Harvard Business Review 96, no. 1 (January–February 2018): 62–69. View Details

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Article | Behavioural Public Policy

Unhealthy Consumerism: The Challenge of Trading Off Price and Quality in Healthcare

Kate Barasz and Peter A. Ubel

Over the last decade, healthcare in many parts of the world has shifted toward a more patient-centric, consumeristic model, marked by an emphasis on choice and a proliferation of typical consumer-facing information (e.g., price and quality data). However, while the "patients as consumers" perspective is an apt one, there are crucial differences between healthcare and typical consumer domains that warrant special consideration by policymakers and researchers alike. This article discusses some of these differences and explores the challenges that consumers (a.k.a. patients) face when making tradeoffs between price and quality.

Keywords: quality; consumer behavior; medical decision-making; choice; Health Care and Treatment; Quality; Price; Consumer Behavior; Decision Making;

Citation:

Barasz, Kate, and Peter A. Ubel. "Unhealthy Consumerism: The Challenge of Trading Off Price and Quality in Healthcare." Behavioural Public Policy 2, no. 1 (May 2018): 41–55. View Details

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Article | Journal of Experimental Psychology: General

Pseudo-Set Framing

Kate Barasz, Leslie John, Elizabeth A. Keenan and Michael I. Norton

Pseudo-set framing—arbitrarily grouping items or tasks together as part of an apparent “set”—motivates people to reach perceived completion points. Pseudo-set framing changes gambling choices (Study 1), effort (Studies 2 and 3), giving behavior (Field Data and Study 4), and purchase decisions (Study 5). These effects persist in the absence of any reward, when a cost must be incurred, and after participants are explicitly informed of the arbitrariness of the set. Drawing on Gestalt psychology, we develop a conceptual account that predicts what will—and will not—act as a pseudo-set and defines the psychological process through which these pseudo-sets affect behavior, concluding that over and above typical reference points, pseudo-set framing alters perceptions of (in)completeness, making intermediate progress seem less complete. In turn, these feelings of incompleteness motivate people to persist until the pseudo-set has been fulfilled.

Keywords: framing effects; Gestalt psychology; judgment; decision making; perception; Judgments; Decision Making; Perception; Behavior;

Citation:

Barasz, Kate, Leslie John, Elizabeth A. Keenan, and Michael I. Norton. "Pseudo-Set Framing." Journal of Experimental Psychology: General 146, no. 10 (October 2017): 1460–1477. View Details

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Article | Journal of Marketing Research (JMR)

The Role of (Dis)similarity in (Mis)predicting Others' Preferences

Kate Barasz, Tami Kim and Leslie K. John

Consumers readily indicate liking options that appear dissimilar—for example, enjoying both rustic lake vacations and chic city vacations or liking both scholarly documentary films and action-packed thrillers. However, when predicting other consumers’ tastes for the same items, people believe that a preference for one precludes enjoyment of the dissimilar other. Five studies show that people sensibly expect others to like similar products but erroneously expect others to dislike dissimilar ones (Studies 1 and 2). While people readily select dissimilar items for themselves (particularly if the dissimilar item is of higher quality than a similar one), they fail to predict this choice for others (Studies 3 and 4)—even when monetary rewards are at stake (Study 3). The tendency to infer dislike from dissimilarity is driven by a belief that others have a narrow and homogeneous range of preferences (Study 5).

Keywords: perceived similarity; prediction error; preference prediction; self-other difference; social inference; Cognition and Thinking; Perception; Forecasting and Prediction;

Citation:

Barasz, Kate, Tami Kim, and Leslie K. John. "The Role of (Dis)similarity in (Mis)predicting Others' Preferences." Journal of Marketing Research (JMR) 53, no. 4 (August 2016): 597–607. View Details

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Article | Proceedings of the National Academy of Sciences of the United States of America

Hiding Personal Information Reveals the Worst

Leslie K. John, Kate Barasz and Michael I. Norton

Seven experiments explore people's decisions to share or withhold personal information and the wisdom of such decisions. When people choose not to reveal information—to be "hiders"—they are judged negatively by others (experiment 1). These negative judgments emerge when hiding is volitional (experiments 2A and 2B) and are driven by decreases in trustworthiness engendered by decisions to hide (experiments 3A and 3B). Moreover, hiders do not intuit these negative consequences: given the choice to withhold or reveal unsavory information, people often choose to withhold, but observers rate those who reveal even questionable behavior more positively (experiments 4A and 4B). The negative impact of hiding holds whether opting not to disclose unflattering (drug use, poor grades, and sexually transmitted diseases) or flattering (blood donations) information including across decisions ranging from whom to date to whom to hire. When faced with decisions about disclosure, decision makers should be aware not just of the risk of revealing but of what hiding reveals.

Keywords: disclosure; transparency; trust; policy-making; privacy; Information; Corporate Disclosure; Decision Choices and Conditions; Trust;

Citation:

John, Leslie K., Kate Barasz, and Michael I. Norton. "Hiding Personal Information Reveals the Worst." Proceedings of the National Academy of Sciences of the United States of America 113, no. 4 (January 26, 2016): 954–959. View Details

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