David A. Schweidel is Professor of Marketing at Emory University’s Goizueta Business School. Schweidel received his B.A. in mathematics, M.A. in statistics, and Ph.D. in marketing from the University of Pennsylvania. He was previously on the faculty of the Wisconsin School of Business at the University of Wisconsin-Madison and Georgetown University’s McDonough School of Business.
Schweidel is an expert in the areas of customer relationship management and social media analytics. His research focuses on the development and application of statistical models to understand customer behavior and inform managerial decisions. His research has appeared in leading business journals including Journal of Marketing, Journal of Marketing Research, Marketing Science and Management Science. His research has garnered numerous awards, including the Gaumnitz Junior Faculty Research Award from the Wisconsin School of Business and the Marketing Science Institute’s Buzzell Award. He has been recognized as a leading scholar by the Marketing Science Institute’s Young Scholar and Scholar programs, and by Poets and Quant’s “Top 40 Under 40.” Based on his research, he has consulted for companies including EBay, HP Labs and General Motors.
Schweidel is the author of Social Media Intelligence (Cambridge University Press) in which he and his co-author discuss how organizations can leverage social media data to inform their marketing strategies. He is also the author of Profiting from the Data Economy (Pearson FT Press), in which he details the value of businesses tapping into consumer data for both individuals and companies.
Ph.D. in MarketingThe Wharton School of the University of Pennsylvania
M.Sc. in StatisticsThe Wharton School of the University of Pennsylvania
B.A. in Mathematics, Economics and Actuarial MathematicsUniversity of Pennsylvania
Frontiers: Supporting Content Marketing with Natural Language Generation
Advances in natural language generation (NLG) have facilitated technologies such as digital voice assistants and chatbots. In this research, we demonstrate how NLG can support content marketing by using it to draft content for the landing page of a website in search engine optimization (SEO). Traditional SEO projects rely on hand-crafted content that is both time consuming and costly to produce...
The role of slant and message consistency in political advertising effectiveness: evidence from the 2016 presidential election
We explore the relationship between the content of political advertising on television and ad effectiveness. Specifically, we investigate how slant – the extremeness of the message –...
How consumer digital signals are reshaping the customer journey
Measuring the Impact of Product Placement with Brand-Related Social Media Conversations and Website Traffic
Incorporating direct marketing activity into latent attrition models
When defection is unobserved, latent attrition models provide useful insights about customer behavior and accurate forecasts of customer value. Yet extant models ignore direct marketing efforts. Response models incorporate the effects of direct marketing, but ...
Online product opinions: Incidence, evaluation, and evolution
Whereas recent research has demonstrated the impact of online product ratings and reviews on product sales, we still have a limited understanding of the individual's decision to contribute these opinions. In this research, we empirically model the individual's decision ...
Portfolio dynamics for customers of a multiservice provider
Multiservice providers, such as telecommunication and financial service companies, can benefit from understanding how customers' service portfolios evolve over the course of their relationships. This can provide guidance for managerial issues such as customer ...
Understanding service retention within and across cohorts using limited information
Service churn and retention rates remain central as constructs in marketing activities, such as valuation of service subscribers and resource allocation. Although extant approaches have been proposed to relate service churn to external factors, such as ...
A bivariate timing model of customer acquisition and retention
Two widely recognized components, central to the calculation of customer value, are acquisition and retention propensities. However, while extant research has incorporated such components into different types of models, limited work has investigated the kinds of ...