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When Does Retargeting Work? Information Specificity in Online Advertising

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TLDR
In this article, the authors use data from a field experiment conducted by an online travel firm to examine whether dynamic retargeted ads are more effective than simply showing generic brand ads.
Abstract
Firms can now offer personalized recommendations to consumers who return to their website, using consumers' previous browsing history on that website. In addition, online advertising has greatly improved in its use of external browsing data to target Internet ads. Dynamic retargeting integrates these two advances by using information from the browsing history on the firm's website to improve advertising content on external websites. When surfing the Internet, consumers who previously viewed products on the firm's website are shown ads with images of those same products. To examine whether this is more effective than simply showing generic brand ads, the authors use data from a field experiment conducted by an online travel firm. Surprisingly, the data suggest that dynamic retargeted ads are, on average, less effective than their generic equivalents. However, when consumers exhibit browsing behavior that suggests their product preferences have evolved (e.g., visiting review websites), dynamic retargeted ad...

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Citations
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Dissertation

Behavioural profiles of potential students as basis for more effective university recruiting

F.J. Kuiper
TL;DR: A framework of Unsupervised Machine Learning algorithms for User Profiling with respect to important data properties is developed to discover high converting behavioural profiles among Dutch website visitors of the University of Twente interested in Master studies.

Airbnb and social environment in big cities

Yunquan Liu
TL;DR: In this paper, the authors aim to increase the sensitivity of foreign tourists who want to rent a flat on Airbnb and let tourists and households take their responsibility of Airbnb through explaining the relatio...
Journal ArticleDOI

Electronic Trace Data and Legal Outcomes: The Effect of Electronic Medical Records on Malpractice Claim Resolution Time

TL;DR: The finding that EMRs speed resolution of malpractice claim resolution time has important welfare implications because unresolved malpractice claims impose substantial costs on providers and patients.
Book ChapterDOI

Interaktionseffizienz im Beziehungslebenszyklus (INTER|CYCLE)

TL;DR: In this paper, a vorliegende Beitrag liefert einen Uberblick der Ergebnisse des Forschungsprojekts INTER|CYCLE, in dem Optimierungspotenziale in der Interaktion mit Kunden entlang des Kundenlebenszyklus untersucht wurden.
Journal Article

Identifying Effective Online Service Strategies: The Impact of Network Externalities and Organizational Lifecycle Stage

TL;DR: In this paper, the authors present a framework for identifying effective online transaction-based service strategies that incorporate network externalities and organizational life cycle theories, considering changes in marginal costs, marginal revenues and service value as the company moves through its initial three life cycle stages (start-up, growth, and maturity).
References
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Book ChapterDOI

Regression Models and Life-Tables

TL;DR: The analysis of censored failure times is considered in this paper, where the hazard function is taken to be a function of the explanatory variables and unknown regression coefficients multiplied by an arbitrary and unknown function of time.
Journal ArticleDOI

Amazon's Mechanical Turk A New Source of Inexpensive, Yet High-Quality, Data?

TL;DR: Findings indicate that MTurk can be used to obtain high-quality data inexpensively and rapidly and the data obtained are at least as reliable as those obtained via traditional methods.
Journal ArticleDOI

Interaction terms in logit and probit models

TL;DR: In this article, the authors present the correct way to estimate the magnitude and standard errors of the interaction effect in nonlinear models, which is the same way as in this paper.
Journal Article

Industry Report: Amazon.com Recommendations: Item-to-Item Collaborative Filtering.

TL;DR: This work compares three common approaches to solving the recommendation problem: traditional collaborative filtering, cluster models, and search-based methods, and their algorithm, which is called item-to-item collaborative filtering.
Journal ArticleDOI

Marketing in Hypermedia Computer-Mediated Environments: Conceptual Foundations

TL;DR: The authors address the role of marketing in hypermedia computer-mediated environments by considering hypermedia CMEs to be large-scale (i.e., national or global) networked enviro...
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