Oded Netzer

• Columbia University

We introduce a probabilistic machine learning model that fuses customer click-stream data and purchase data within and across journeys. This approach addresses the critical business need for leveraging first-party data (1PD), particularly in environments with infrequent purchases, which are characterized by minimal or no prior purchase history. Com...

Using publicly available data from 299 preregistered replications from the social sciences, we found that the language used to describe a study can predict its replicability above and beyond a large set of controls related to the article characteristics, study design and results, author information, and replication effort. To understand why, we ana...

Routines shape many aspects of day-to-day consumption. While prior work has established the importance of habits in consumer behavior, little work has been done to understand the implications of routines—which we define as repeated behaviors with recurring, temporal structures—for customer management. One reason for this dearth is the difficulty of...

Firms increasingly aim to present diversity across age, gender, and/or race in their promotional material. Recent social movements such as BlackLivesMatter (BLM) or MeToo have further raised awareness towards social inequality. This paper examines racial diversity in U.S. digital advertising, analyzing both the diversity of ads distributed to consu...

This paper investigates whether the polarization of political ideology extends to consumers’ preferences, intentions, and purchases.

Smartphones have made it nearly effortless to share images of branded experiences. This research classifies social media brand imagery and studies user response. Aside from packshots (standalone product images), two types of brand-related selfie images appear online: consumer selfies (featuring brands and consumers’ faces) and an emerging phenomeno...

An important challenge for many firms is to identify the life transitions of its customers, such as job searching, expecting a child, or purchasing a home. Inferring such transitions, which are generally unobserved to the firm, can offer the firms opportunities to be more relevant to their customers. In this paper, we demonstrate how a social netwo...

Marketing is the functional area primarily responsible for driving the organic growth of a firm. In the age of digital marketing and big data, marketers are inundated with increasingly rich data from an ever-expanding array of sources. Such data may help marketers generate insights about customers and competitors. One fundamental question remains:...

Words are part of almost every marketplace interaction. Online reviews, customer service calls, press releases, marketing communications, and other interactions create a wealth of textual data. But how can marketers best use such data? This article provides an overview of automated textual analysis and details how it can be used to generate marketi...

The authors present empirical evidence that borrowers, consciously or not, leave traces of their intentions, circumstances, and personality traits in the text they write when applying for a loan. This textual information has a substantial and significant ability to predict whether borrowers will pay back the loan above and beyond the financial and...

In today’s turbulent business environment, customer retention presents a significant challenge for many service companies. Academics have generated a large body of research that addresses part of that challenge—with a particular focus on predicting customer churn. However, several other equally important aspects of managing retention have not recei...

We investigate the increasingly common business setting in which companies face the possibility of both observed and unobserved customer attrition (i.e., “overt” and “silent” churn) in the same pool of customers. This is the case for many online-based services where customers have the choice to stop interacting with the firm either by formally term...

The rise of ‘Big Data’ had a big impact on marketing research and practice. In this article, we first highlight sources of useful consumer information that are now available at large scale and very little or no cost. We subsequently discuss how this information – with the help of new analytical techniques – can be translated into valuable insights...

Hidden Markov models (HMMs) have been used to model how a sequence of observations is governed by transitions among a set of latent states. HMMs were first introduced by Baum and co-authors in late 1960s and early 1970 (Baum and Petrie 1966; Baum et al. 1970), but only started gaining momentum a couple decades later. HMMs have been applied in vario...

One of the most significant developments in the domain of marketing in recent years involves the proliferation of user-generated content, particularly online social media. Social media has created a power shift in the relationship between consumers and brands, providing consumers more power by allowing them to easily broadcast their views and op...

This tutorial provides evidence that character misrepresentation in survey screeners by Amazon Mechanical Turk Workers (“Turkers”) can substantially and significantly distort research findings. Using five studies, we demonstrate that a large proportion of respondents in paid MTurk studies claim a false identity, ownership, or activity in order to q...

Spending money on hedonic luxuries often seems wasteful, irrational, and even immoral. We propose that adding a small utilitarian feature to a luxury product can serve as a functional alibi, justifying the indulgent purchase and reducing indulgence guilt. We demonstrate that consumers tend to inflate the value, and usage frequency, of utilitarian f...

Customer relationship management (CRM) campaigns have traditionally focused on maximizing the profitability of the targeted customers. The authors demonstrate that in business settings characterized by network externalities, a CRM campaign that is aimed at changing the behavior of specific customers propagates through the social network, thereby al...

We explore the use of big data tools to shed new light on the idea generation process, automatically “read” ideas to identify promising ones, and help people be more creative. The literature suggests that creativity results from the optimal balance between novelty and familiarity, which can be measured based on the combinations of words in an idea....

The notion that effort and hard work yield desired outcomes is ingrained in many cultures and affects our thinking and behavior. However, could valuing effort complicate our lives? In the present article, the authors demonstrate that individuals with a stronger tendency to link effort with positive outcomes end up complicating what should be easy d...

The legacy of a pioneer in operations research and marketing science. John D. C. Little of MIT's Sloan School of Management is famous for his contributions to operations research and marketing science. He formulated a fundamental theorem in queuing theory known as Little's Law, which is used widely in a variety of fields. His work on such topics as...

We present an end-to-end text mining methodology for relation extraction of adverse drug reactions (ADRs) from medical forums on the Web. Our methodology is novel in that it combines three major characteristics: (i) an underlying concept of using a head-driven phrase structure grammar (HPSG) based parser; (ii) domain-specific relation patterns, the...

We report the results of a survey conducted in November 2014 in which 29 quantitative marketing scholars from around the world reflected on the present and future of their field. The survey focused on substantive areas, methods and tools, practical and managerial relevance, doctoral training, and promotion and tenure. The results of the survey reve...

We investigate the increasingly common business setting in which companies face the possibility of both observed and unobserved customer attrition (i.e., “overt” and “silent” churn) in the same pool of customers. This is the case of many online-based services where customers have the choice to stop interacting with the firm either by formally termi...

We model the multifaceted impact of pricing decisions in business-to-business (B2B) relationships that are governed by trust. We show how a seller can develop optimal intertemporal targeted pricing strategies to maximize profits over time while taking into consideration the impact of pricing decisions on short-term profit margin, reference price fo...

This is an abridged version of an evaluation report for Marketing Science, which was commissioned by the INFORMS Publications Committee as part of its periodic review of every INFORMS journal. The coauthors listed here comprised the task force that conducted the research project and strategic analysis described below.

The canonical design of customer satisfaction surveys asks for global satisfaction with a product or service and for evaluations of its distinct attributes. Users of these surveys are often interested in the relationship between global satisfaction and ...

Over the course of a repeated game, players often exhibit learning in selecting their best response. Research in economics and marketing has identified two key types of learning rules: belief and reinforcement. It has been shown that players use either one of these learning rules or a combination of them, as in the Experience-Weighted Attraction (E...

In recent years academic research has focused on understanding and modeling the survey response process. This paper examines an understudied systematic response tendency in surveys: the extent to which observed responses are subject to state dependence, i.e., response carryover from one item to another independent of specific item content. We devel...

Web 2.0 provides gathering places for internet users in blogs, forums, and chat rooms. These gathering places leave footprints in the form of colossal amounts of data regarding consumers’ thoughts, beliefs, experiences, and even interactions. In this paper, we propose an approach for firms to explore online user-generated content and “listen” to wh...

We model the multifaceted impact of pricing decisions in B2B contexts and show how a seller can develop optimal inter-temporal targeted pricing strategies to maximize long-term customer value. We empirically model the B2B customer’s purchase decisions in an integrated fashion. In order to facilitate targeting and to capture the short and long-term...

A great deal of research in consumer decision-making and social-cognition has explored consumers’ attempts to simplify choices by bolstering their tentative choice candidate and/or denigrating the other alternatives. The present research investigates a diametrically opposed process, whereby consumers complicate their decisions. The authors demonstr...

We’re predicting the birth of the consumer insights function, which will become a critical corporate function as data will grow dramatically in volume. Researchers will have to learn how to communicate insights to senior leadership. There will be organizational barriers, resistance to the “new” data-driven world, and a need for metrics and skilled...

The U.S. pharmaceutical industry spent upwards of $18 billion on marketing drugs in 2005; detailing and drug sampling activities accounted for the bulk of this spending. To stay competitive, pharmaceutical managers need to maximize the return on these marketing investments by determining which physicians to target as well as when and how to target...

Scientific inquiry often advances in triadic waves of thesis, antithesis, and synthesis. We concur with Simonson [Simonson, I., (2008). Will I Like a "Medium" Pillow: Another Look at Constructed and Inherent Preferences. Journal of Consumer Psychology, this issue.] that BDT's antithesis of preference construction, positioned against the normative u...

Product discussion boards are a rich source of information about consumer sentiment about products, which is being increasingly exploited. Most sentiment analysis has looked at single products in isolation, but users often compare different products, stating which they like better and why. We present a set of techniques for analyzing how consumers...

This research models the dynamics of customer relationships using typical transaction data. Our proposed model permits not only capturing the dynamics of customer relationships, but also incorporating the effect of the sequence of customer-firm encounters on the dynamics of customer relationships and the subsequent buying behavior. Our approach to...

We identify gaps and propose several directions for future research in preference measurement. We structure our argument around a framework that views preference measurement as comprising three interrelated components: (1) the problem that the study is ultimately intended to address; (2) the design of the preference measurement task and the data co...

Scientific inquiry often advances in triadic waves of thesis, antithesis, and synthesis. We concur with Simonson [Simonson, I., (2008). Will I Like a “Medium” Pillow: Another Look at Constructed and Inherent Preferences. Journal of Consumer Psychology, this issue.] that BDT's antithesis of preference construction, positioned against the normative u...

To optimally allocate its marketing mix across customers, a firm needs to consider the evolution of its customers over time. Changes in the marketing environment, as well as intrinsic changes in preferences or needs, may discretely shift customers into different buying-behavior states. The ability to identify the dynamics in customer behavior and i...

The ability to identify customers' dynamics and its drivers present an opportunity for firms to optimize their marketing resource allocation and increase long-run profitability. Accordingly, we address the following managerial questions in this research: (1) how can firms dynamically segment their customer base? (2) what are the short- and long-ter...

In recent years, product discussion forums have become a rich environment in which consumers and potential adopters exchange views and information. Researchers and practitioners are starting to extract user sentiment about products from user product reviews. Users often compare different products, stating which they like better and why. Extracting...

This research models the dynamics of customer relationships using typical transaction data. It permits the evaluation of the effectiveness of customer-brand encounters on the dynamics of customer relationships and the subsequent buying behavior. Our approach to modeling relationship dynamics is structurally different from existing approaches. In th...

The authors propose a Web-based adaptive self-explicated approach for multiattribute preference measurement (conjoint analysis) with a large number (ten or more) of attributes. The proposed approach overcomes some of the limitations of previous self-explicated approaches. The authors develop a computer-based self-explicated approach that breaks dow...

Building on the work of Dhar, Menon, and Maach (2004), this com-mentary describes how the compromise effect models developed in the work of Kivetz, Netzer, and Srinivasan (2004) can be extended to predict complex (business-to-business) purchase decisions and additional behavioral context effects. The authors clarify their general modeling approach...

The compromise effect denotes the finding that brands gain share when they become the intermediate rather than extreme option in a choice set. Despite the robustness and importance of this phenomenon, choice modelers have neglected to incorporate the compromise effect in formal choice models and to test whether such models outperform the standard v...

The compromise effect denotes the finding that brands gain share when they become the intermediate rather than an extreme option in a choice set (Simonson 1989). Despite the robustness and importance of this phenomenon, choice modelers have neglected to incorporate the compromise effect within formal choice models and to test whether such models ou...