Personalization in Social Retargeting – A Field Experiment

This study compares the effectiveness of product- and category-specific advertising personalization in Social Retargeting. Social Retargeting combines the features of social advertising, targeting consumers based on social connections, and retargeting, using consumers’ browsing behavior to personalize ad content. We conducted a large-scale randomized field experiment in collaboration with a major e-retailer. Contradicting prior empirical findings, our results indicate that product-specific ads outperform less personalized category-specific ads. While theory suggests a positive effect, we find that social targeting decreases the performance of personalized ads. Surprisingly, socially targeted consumers are not more responsive to product-specific ads. We show that our results remain robust and are driven by ad personalization when controlling for temporal targeting and how deep consumers browse the e-retailer’s website. Our study contributes to the IS and marketing literature related to personalization in digital advertising and provides valuable suggestions for firms’ personalization strategies

Personalization in social retargeting - A field experiment

This study compares the effectiveness of product- and category-specific advertising personalization in Social Retargeting. Social Retargeting combines the features of social advertising, targeting consumers based on social connections, and retargeting, using consumers' browsing behavior to personalize ad content. We conducted a large-scale randomized field experiment in collaboration with a major e-retailer. Contradicting prior empirical findings, our results indicate that product-specific ads outperform less personalized category-specific ads. While theory suggests a positive effect, we find that social targeting decreases the performance of personalized ads. Surprisingly, socially targeted consumers are not more responsive to product-specific ads. We show that our results remain robust and are driven by ad personalization when controlling for temporal targeting and how deep consumers browse the e-retailer's website. Our study contributes to the IS and marketing literature related to personalization in digital advertising and provides valuable suggestions for firms' personalization strategies

How Digital Nudges Influence Consumers – Experimental Investigation in the Context of Retargeting

Retargeting is an innovative online marketing technique in the modern age. Although this advertising form offers great opportunities of bringing back customers who have left an online store without a complete purchase, retargeting is risky because the necessary data collection leads to strong privacy concerns which, in turn, trigger consumer reactance and decreasing trust. Digital nudges – small design modifications in digital choice environments which guide peoples’ behaviour – present a promising concept to bypass these negative consequences of retargeting. In order to prove the positive effects of digital nudges, we aim to conduct an online experiment with a subsequent survey by testing the impacts of social nudges and information nudges in retargeting banners. Our expected contribution to theory includes an extension of existing research of nudging in context of retargeting by investigating the effects of different nudges in retargeting banners on consumers’ behaviour. In addition, we aim to provide practical contributions by the provision of design guidelines for practitioners to build more trustworthy IT artefacts and enhance retargeting strategy of marketing practitioners

When Does Retargeting Work? Information Specificity in Online Advertising

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 ads no longer underperform. One explanation for this finding is that when consumers begin a product search, their preferences are initially construed at a high level. As a result, they respond best to higher-level product information. Only when they have narrowly construed preferences do they respond positively to ads that display detailed product information. This finding suggests that in evaluating how best to reach consumers through ads, managers should be aware of the multistage nature of consumers' decision processes and vary advertising content along these stages.London Business School. Centre for MarketingNational Science Foundation (U.S.) (CAREER Award 1053398

The Implications of Advertising Personalization for Firms, Consumers, and Ad Platforms

The personalization of advertising offers firms tremendous potential. If done right, firms can address consumers with more relevant ads, leading to more positive consumer responses. Nevertheless, firms are struggling with how to design personalization strategies and face the challenge to correctly assess advertising effectiveness. With this research, we advance the understanding of advertising personalization and its implications for firms, consumers, and ad platforms. With the help of a large-scale field experiment, we present evidence for how firms should design their personalization strategies. We find that high levels of personalization specificity pay off for firms. At the same time, socially targeting personalized ads, where names of consumers' friends are included in the ad text, leads to less positive consumer responses. To advance the understanding of privacy concerns in advertising personalization, we conduct a lab experiment using eye tracking technology. Our findings reveal that firms cannot use intrusive ads that cause privacy concerns to attract consumers' attention. Such a strategy is harmful as it decreases consumers' overall attention towards ads, eventually leading to less positive consumer responses. An examination of contracts between firms and ad platforms exposes that these contracts might not be in the economic interest of firms. We conduct a large field experiment and our analysis reveals that currently implemented contracts between ad platforms and firms lead to an incentive misalignment that is harmful for firms. While ads generally increase consumers' likelihood to purchase, firms pay more for ads that are not providing higher value to them

Responsive and Personalized Web Layouts with Integer Programming

Over the past decade, responsive web design (RWD) has become the de facto standard for adapting web pages to a wide range of devices used for browsing. While RWD has improved the usability of web pages, it is not without drawbacks and limitations: designers and developers must manually design the web layouts for multiple screen sizes and implement associated adaptation rules, and its "one responsive design fits all"approach lacks support for personalization. This paper presents a novel approach for automated generation of responsive and personalized web layouts. Given an existing web page design and preferences related to design objectives, our integer programming -based optimizer generates a consistent set of web designs. Where relevant data is available, these can be further automatically personalized for the user and browsing device. The paper includes presentation of techniques for runtime adaptation of the designs generated into a fully responsive grid layout for web browsing. Results from our ratings-based online studies with end users (N = 86) and designers (N = 64) show that the proposed approach can automatically create high-quality responsive web layouts for a variety of real-world websites.Peer reviewe

How Social Media Advertising and Repetitive Marketing Messages Affect the Online Purhasing Behavior?

In the past decade social media advertising has disrupted the marketing and advertising totally. As social media advertising platforms such as Facebook offer easy, effective and relatively cheap services, they have enabled and encouraged the rise of new kinds of companies operating solely online by tapping into the potential of easily reaching the audience and attracting them to their webstores. This has made it possible for up and coming companies with less well-known brands to attract customers and build up their brands. Naturally as the marketing field has been disrupted by the social media advertising, the traditional rules and guidelines of marketing need to be re-evaluated requiring academic research to understand how social media marketing and people’s behavior online differs from more traditional channels. Additionally, the ability to effectively personalize the marketing messages for different audience groups for example based on the previous engagement or other online behavior brings up another layer to the phenomenon. For the purpose of this study, the audience visiting the webstore of the case company is divided based on their previous brand engagement to three groups; fresh audience with no previous engagement, retargeted audience with some engagement for example on social media platforms or website visits and returning audience with previous webstore visits. Fresh and retargeted audience groups ended up to the webstore via Facebook advertisements while returning audience returned to the site without the need of extra marketing activities. With t-tests and ANOVA it was possible to establish differences in behavior between these groups and based on that, regression models were created to further understand the drivers affecting conversion rate and revenue per user. What comes to the reactions to the Facebook advertisements, people with previous brand engagement, i.e. retargeted audience was much more likely to enter the webstore by clicking the advertisement than fresh audience. Additionally, retargeted audience has higher conversion rate and higher revenue per user values as well. As previous research has also found, previous engagement with the brand is indeed the strongest indicator for purchase intention. In addition to that, returning audience i.e. the people who return to the website on their own have the highest conversion rates and revenue per user values out of the audience groups studied. It is likely that this can be explained with the stronger firm-consumer relationship, making this group the most loyal and profitable customers. For the fresh and retargeted audience groups, time spent on the website has positive affect on both conversion rate and revenue per user. So, it seems that when previous engagement with the brand is lower, clicking the Facebook advertisement and spending more time on the website builds up the firm-customer relationship and improves purchase intention

Understanding the Value of Online Ad Targeting - Advertiser's Perspective

Online advertising is a huge, growing industry and a key part of the growth is the improving efficiency of online advertising due to ad targeting. Targeting is a process that includes collecting data from various sources to help match advertisements with consumers who are most likely to be interested and to purchase the advertised products. While the consensus is that targeting can be used to provide value for advertisers, and for consumers, the incremental value is difficult to quantify. In this paper, we take a look at some of the problems advertisers face when using targeting and present some existing solutions to mitigate these challenges. Earlier literature is used to exemplify how advertisers can effectively identify desired target audiences, choose the optimal methods for targeting to reach the selected audience and measure the success of their campaigns. One of the key challenges for advertisers however, appears to be difficulties understanding the platforms they use for online advertising. Participant observation, a method often used for ethnographic research is presented here as a way for advertisers to learn about the ad platforms and the success of their campaigns. In business, participant observation has been used to analyze the quality of in-store services, but here its use is developed and demonstrated in an online environment. To exemplify how the method can be used in an online advertising context, this paper presents the findings of a study, where ads were observed on YouTube. The study is a combination of market research and marketing research. First, ads from four different markets are observed to find out whether market size and the level of data privacy regulations affect how advertisements appear to consumers. Then, additional observations are made in two of the markets, to see how disabling personalized advertising affects how adverts are distributed to consumers. The study presented here, is intended as a proof-of-concept and advertisers can use the developed method in a multitude of ways to find out valuable insight about online advertising platforms. Participant observation can be used for example to better understand the setup process of targeted advertising campaigns, to optimize one’s campaigns and to examine how one’s competitors appear to be running their campaigns. In addition to numerous business use cases like these, the method can be used for academic purposes, as presented in this paper

Online Advertising

This chapter explores what makes online advertising different from traditional advertising channels. We argue that online advertising differs from traditional advertising channels in two important ways: measurability and targetability. Measurability is higher because the digital nature of online advertising means that responses to ads can be tracked relatively easily. Targetability is higher because data can be automatically tracked at an individual level, and it is relatively easy to show different people different ads. We discuss recent advances in search advertising, display advertising, and social media advertising and explore the key issues that arise for firms and consumers from measurability and targetability. We then explore possible public policy consequences, with an in depth discussion of the implications for consumer privacy