We quantify the prevalence of undisclosed influencer posts on Twitter across a large set of brands based on a unique data set of over 100 million posts. We develop a novel method to detect undisclosed influencer posts and find that 96% of influencer posts are not disclosed as such. Despite...

We estimate the distribution of television advertising elasticities and the distribution of the advertising return on investment (ROI) for a large number of products in many categories. Our results reveal substantially smaller advertising elasticities compared to the results documented in the...

We estimate the causal effects of different targeted email promotions on the opening and purchase decisions of the consumers who receive them. To do so, we synthesize and extend recent advances in causal machine learning techniques to capture heterogeneity in the content of the email subject...

In this document, we detail how to construct the Nielsen Ad Intel Database from the raw source filesprovided by the Kilts Center for Marketing at the University of Chicago Booth School of Business.Further, we detail our procedure for matching the Ad Intel data with the retail scanner data...

While most managers today acknowledge the importance of featuring diverse racial identities in their marketing communications, empirical research that shows how improving such representation may affect consumer behavior is lacking. To fill this gap, we use face recognition and race...

We quantify the prevalence of undisclosed influencer posts on Twitter across a large set of brands based on a unique data set of over 100 million posts. We develop a novel method to detect undisclosed influencer posts and find that 96% of influencer posts are not disclosed as such. Despite...

In a rapidly changing world, older data is not as informative as the most recent data. This is known as a concept drift problem in statistics and machine learning. How does a firm adapt in such an environment? To address this research question, we propose a generalized revealed preference...

This study examines how social identity affects the generation of electronic word-of-mouth (eWOM). We develop a structural equation model (SEM) comprising self-enhancement, social capital, and social presence as explanatory variables of social identity. We propose that, through these variables,...

The increasing importance of online distribution channels is paralleled by a rising interest in gaining insights into the customer journey and browsing behavior. We evaluate several machine learning methods (latent Dirichlet allocation, correlated topic model, structural topic model, replicated...

Starting from the idea that nowadays the companies use the promotion and communication by event more and more because of the advantages it entails, this paper uses the marketing quantitative research as a tool and it's scope is to present the opinions and the attitudes of the people that...