Journal Article10.1093/JCR/UCW012
An Audience of One: Behaviorally Targeted Ads as Implied Social Labels
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TL;DR: This research explores the unique ways in which consumers respond to ads using this type of targeting, demonstrating that a behaviorally targeted ad can act as a social label even when it contains no explicit labeling information.
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Abstract: “Behavioral targeting” is an Internet-based targeting strategy that delivers digital ads to individuals based on their online behavior (e.g., search, shopping). This research explores the unique ways in which consumers respond to ads using this type of targeting (vs. to ads that use more traditional forms of targeting), demonstrating that a behaviorally targeted ad can act as a social label even when it contains no explicit labeling information. Instead, when consumers recognize that the marketer has made an inference about their identity in order to serve them the ad, the ad itself functions as an implied social label. Across four studies, behaviorally targeted ads lead consumers to make adjustments to their self-perceptions to match the implied label; these self-perceptions then impact behavior including purchase intentions for the advertised product and other behaviors related to the implied label. Importantly, these effects only hold when the label is plausibly connected to consumers’ prior behavior (i.e., when the targeting is at least moderately accurate).
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Citations
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TL;DR: Zhang et al. as mentioned in this paper suggest that location-based mobile marketing efficacy depends on its potential to minimize consumer reactance, which can be achieved by effectively combining location targeting (in-store vs. out-store), behavioral targeting (based on consumers’ product category involvement [PCI]), and the type of promotion offered (price vs. non-price promotion).
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Ben Weinshel,Miranda Wei,Mainack Mondal,Euirim Choi,Shawn Shan,Claire Dolin,Michelle L. Mazurek,Blase Ur +7 more
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TL;DR: Tracking Transparency is presented, a privacy-preserving browser extension that visualizes examples of long-term, longitudinal information that third-party trackers could have inferred from users' browsing.
57
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