scispace - formally typeset
Open Access

When Does Retargeting Work? Information Specificity in Online Advertising

Reads0
Chats0
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...

read more

Citations
More filters
Proceedings ArticleDOI

Designing an adaptive online advertisement system: A focus group methodology

TL;DR: A revisited design for an adaptive online advertisement system called MyAds.com is discussed, using Amazon as a motivational blueprint for the new design and generated a list of requirements from users, in order for their acceptance level of personalised online advertisements to increase.
Proceedings Article

Estimating Ad Impact on Clicker Conversions for Causal Attribution: A Potential Outcomes Approach.

TL;DR: A larger number of converting users attributed to the overall campaign than those attributed based on the clickto-conversion (C2C) standard business model are found, which challenges the well-accepted belief that C2C attribution model over-estimates the value of the campaign.
Proceedings ArticleDOI

Applying Reinforcement Theory to Implementing a Retargeting Advertising in the Electronic Commerce Website

TL;DR: This study designs the retargeting advertising to persuade potential customers to go back the c-commerce website and to complete the shopping.
Posted Content

Context information increases revenue in ad auctions: Evidence from a policy change

TL;DR: In this paper, the authors explore the effect of ad placement disclosure on ad revenue and find that ad context information is important to ad buyers and that providing more context information will not lead to deconflation.
Book ChapterDOI

Big Data and Business Decision Making

TL;DR: The possibilities of big data to improve the services offered by companies and the customer experience and increase the efficiency of these companies are analyzed.
References
More filters
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...
Related Papers (5)