Guide de L'Email Marketing

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  • Topic: Online advertising, Advertising network, Website
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  • Published : May 21, 2013
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When Does Retargeting Work? Information Specificity in Online Advertising∗ Anja Lambrecht†and Catherine Tucker‡ May 6, 2013

We thank Havas Digital and particularly Katrin Ribant for access to data from Artemis and Marco Bertini for facilitating the contact to Havas Digital. We gratefully acknowledge financial support from the London Business School Centre for Marketing. We thank Kristin Diehl, Anindya Ghose, Avi Goldfarb, Brett Gordon, Duncan Simester, Catalina Stefanescu, Florian von Wangenheim and Ken Wilbur for their comments, as well as participants at the 2011 SICS conference and seminar participants at Cass Business School, ESMT, ESSEC, London Business School and the National University of Singapore. † London Business School, London, UK; alambrecht@london.edu. ‡ MIT Sloan School of Management, MIT, Cambridge, MA; cetucker@mit.edu. and NBER



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Electronic copy available at: http://ssrn.com/abstract=1795105

When Does Retargeting Work? Information Specificity in Online Advertising

Abstract Firms can now serve personalized recommendations to consumers who return to their website, based on their earlier browsing history on that website. At the same time, online advertising has greatly advanced in its use of external browsing data across the web to target internet ads. ‘Dynamic Retargeting’ integrates these two advances, by using information from earlier browsing on the firm’s website to improve internet advertising content on external websites. Consumers who previously visited the firm’s website when surfing the wider web, are shown ads that contain images of products they have looked at before on the firm’s own website. To examine whether this is more effective than simply showing generic brand ads, we use data from a field experiment conducted by an online travel firm. We find, surprisingly, that dynamic retargeted ads are on average less effective than their generic equivalent. However, when consumers exhibit browsing behavior such as visiting review websites that suggests their product preferences have evolved, dynamic retargeted ads no longer underperform.

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Electronic copy available at: http://ssrn.com/abstract=1795105

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Introduction

Innovations in the parsing and processing of individual-level browsing data enable firms to serve product recommendations in real time to consumers who return to their website. These personalized ‘recommendation systems’ often highlight the specific products that the consumer was browsing before they left the website, and may increase sales (Linden et al., 2003; Dias et al., 2008). However, consumers who browse products online often leave the website without buying and do not return. To reach out to such consumers, dynamic retargeted ads feature pictures of precisely the product consumers previously browsed. At first blush, this makes sense: The marketing literature has emphasized that greater specificity of a firm’s interactions with consumers should increase relevance and consumer response (Hoffman and Novak, 1996; Komiak and Benbasat, 2006; Dias et al., 2008). Firms that offer retargeting services point to strong increases in advertising effectiveness. For example, Criteo (2010) reports that personalized retargeted ads are six times more effective than standard banner ads, and four times more effective than retargeting that uses generic ads. As a result, dynamic retargeting has attracted much enthusiasm among online advertising practitioners (Hunter, 2010; Hunter et al., 2010; Hargrave, 2011). For example, a single firm that sells retargeting solutions, the ‘Next Performance’ ad network, reports that it has served 30 billion retargeted impressions, analyzed 1 billion products for possible inclusion in a dynamic retargeted ad, and served dynamic retargeted ads to 500 million unique visitors.1 However, there is little empirical evidence that a personalized product recommendation is as effective when displayed on external websites, as it is when it is displayed internally on...
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