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Social advertising uses information about consumers' peers, including peer affiliations with a brand, product, organization, etc., to target ads and contextualize their display. This approach can increase ad efficacy for two main reasons:…
Incrementality, which is used to measure the causal effect of showing an ad to a potential customer (e.g. a user in an internet platform) versus not, is a central object for advertisers in online advertising platforms. This paper…
With the continuous development of machine learning technology, major e-commerce platforms have launched recommendation systems based on it to serve a large number of customers with different needs more efficiently. Compared with…
The causal effect of showing an ad to a potential customer versus not, commonly referred to as "incrementality", is the fundamental question of advertising effectiveness. In digital advertising three major puzzle pieces are central to…
In this paper we investigate the ability of modern machine learning algorithms in inferring basic offline activities,~e.g., shopping and dining, from location data. Using anonymized data of thousands of users of a prominent location-based…
A/B tests are randomized experiments frequently used by companies that offer services on the Web for assessing the impact of new features. During an experiment, each user is randomly redirected to one of two versions of the website, called…
On today's Web, users trade access to their private data for content and services. Advertising sustains the business model of many websites and applications. Efficient and successful advertising relies on predicting users' actions and…
In online randomized experiments or A/B tests, accurate predictions of participant inclusion rates are of paramount importance. These predictions not only guide experimenters in optimizing the experiment's duration but also enhance the…
This representative study of German search engine users (N=1,000) focuses on the ability of users to distinguish between organic results and advertisements on Google results pages. We combine questions about Google's business with…
Ad-load balancing is a critical challenge in online advertising systems, particularly in the context of social media platforms, where the goal is to maximize user engagement and revenue while maintaining a satisfactory user experience. This…
Developing shopping experiences that delight the customer requires businesses to understand customer taste. This work reports a method to learn the shopping preferences of frequent shoppers to an online gift store by combining ideas from…
Mobile-phone advertising enables marketers to reach customers at a personal level and it enables the measure of costumers reaction by novel approaches, in real time, and at scale. By keeping a device anonymous, we can deliver custom adverts…
As "Big Data" has become pervasive, an increasing amount of research has connected the dots between human behaviour in the offline and online worlds. Consequently, researchers have exploited these new findings to create models that better…
Data sharing between online trackers and advertisers is a key component in online behavioral advertising. This sharing can be facilitated through a variety of processes, including those not observable to the user's browser. The…
In this paper, we deal with the uncertainty of bidding for display advertising. Similar to the financial market trading, real-time bidding (RTB) based display advertising employs an auction mechanism to automate the impression level media…
Online controlled experiments, now commonly known as A/B testing, are crucial to causal inference and data driven decision making in many internet based businesses. While a simple comparison between a treatment (the feature under test) and…
As the number of online shopping websites increases day by day, so are the online advertisement strategies and promotional techniques. The number of people who uses internet keeps on increasing daily and it has become a vast marketplace to…
It is standard practice in online retail to run pricing experiments by randomizing at the article-level, i.e. by changing prices of different products to identify treatment effects. Due to customers' cross-price substitution behavior, such…
Online labor markets have great potential as platforms for conducting experiments, as they provide immediate access to a large and diverse subject pool and allow researchers to conduct randomized controlled trials. We argue that online…
Marketers often use A/B testing as a tool to compare marketing treatments in a test stage and then deploy the better-performing treatment to the remainder of the consumer population. While these tests have traditionally been analyzed using…