Marketing

Our faces are said to be windows into the soul. But can they also reflect who we are as consumers? Can facial images predict brand preferences? To answer these questions, we analyze a unique dataset of over 100,000 single-face Twitter profile pictures linked with brand followership data for 444 brands across categories and brand personality metrics. Using advanced machine learning for automated face analysis, we demonstrate that consumers’ social media profile faces can reveal their preferences between rival brands (study 1).

Comment sections on social media extend social influence beyond offline networks, allowing  a small, vocal minority of users to reach much larger audiences. We provide causal evidence that  the views expressed in comments below social media posts shape both on-platform engagement  and off-platform attitudes and behavior, and that these effects move in opposite directions. In  collaboration with a leading racial justice organization, we conduct a large-scale field experi ment on Facebook reaching a million U.S.

Major life transitions, such as pregnancy and childbirth, reshape lifestyles and purchasing priorities, yet causal evidence on how consumers reallocate spending across product categories remains limited. We quantify the effects of first-time parenthood by linking a large-scale transactional panel to verified birth records. To identify causal effects, we implement a difference-in-differences design augmented with causal forests, enabling flexible comparisons between households entering parenthood and carefully matched controls. We uncover a pronounced and dynamic behavioral trajectory.

Firms increasingly rely on A/B testing to evaluate marketing strategies, yet most experiments are analyzed in isolation, limiting insight into why effectiveness varies and how repeated exposure shapes outcomes. We develop a hierarchical Bayesian framework that jointly analyzes randomized marketing interventions to decompose treatment effect heterogeneity into three components: customer responsiveness, campaign design, and contextual timing.

Organizations emphasize specific production practices to deal with authenticity pressures, but the practices that signal authenticity to audiences must be continually adapted when production environments are unstable. Changes in the environment can make production practices suddenly infeasible, compelling organizations to perform in different ways the highly visible practices that audiences have come to associate with authenticity.

Salespeople frequently face the dynamic screening decision of whether to persist in a conversation or abandon it to pursue the next lead. Yet, little is known about how these decisions are made, whether they are efficient, or how to improve them. We study these decisions in the context of high-volume outbound sales where leads are ample, but time is scarce and failure is common.

The use of synthetic data has generated considerable heat (but not as much light) in the consumer insights world. While we should not be fully replacing human respondents anytime soon, there is enough evidence to make a strong case for certain uses of synthetic data.

By Rajan Sambandam and Oded Netzer

A large portion of life as a consumer is spent mind-wandering from one off-task, spontaneous, and imaginative thought to the next. Psychology research has thoroughly documented the various characteristics of mind-wandering, showing that this default state of mind occupies much of our waking life and shapes outcomes ranging from goal pursuit and decision-making to present-moment experience. However, consumer research has largely overlooked mind-wandering as a phenomenon and mechanism that shapes consumption.

We quantify the impact of Generative Artificial Intelligence (GenAI) on firm productivity through a series of large-scale randomized field experiments involving millions of users and products at a leading cross-border online retail platform. Over six months in 2023-2024, GenAI-based enhancements were integrated into seven consumer-facing business workflows. We find that GenAI adoption significantly increases sales, with treatment effects ranging from 0% to 16.3%, depending on GenAI’s marginal contribution relative to existing firm practices.