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Using Text for Marketing Insights

Monday, November 30th, 2020 (5pm-6pm PST)

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Webinar Overview:

The digitalization of marketing and other business functions has generated a wealth of textual data with valuable business insights. The data include user-generated-content (UGC) reviewing product performance, dialogs documenting customer service interaction, financial reports explaining performance and strategy, and so forth. Companies and researchers are scrambling for natural language processing (NLP) to distill insights from the textual data. However, data analysts, especially those who mostly use econometrics and multivariate statistics, may not have NLP in their toolset because many breakthroughs in the NLP technique are very recent. In the webinar, we will survey the general applications of NLP in marketing research and discuss their technical foundations. Besides, we also have assembled learning materials for interested attendees who want to further their NLP knowledge. In sum, the webinar aims to lower the learning curve of NLP for attendees who are new to this area.

Webinar Highlights:

  • Recognize the general applications of natural language processing (NLP) in marketing research

  • Understand the technical foundation and general procedures of NLP applications in marketing research

  • Explain the path of learning NLP for marketing research

  • Obtain curated materials for learning NLP

richard tang

Zhen (Richard) Tang,
Assistant Professor of Marketing, Loyola Marymount University

Richard Tang graduated from East China University of Science and Technology with B.A. and M.S. in Business Administration. He then earned his Ph.D. in Marketing with a minor in economics from the University of Arizona. He is now serving as an assistant professor of marketing at Loyola Marymount University (LMU). At LMU, Richard teaches marketing analytics and natural language processing and mentors students in various data science competitions.


Richard’s training on quantitative research methods consists of econometrics and machine learning (focusing on natural language processing). He is interested in applying those quantitative methods to generate constructive insights for businesses and society. Topics of his current research include quantifying business environments with geographical location information, extracting consumer insights from user-generated-content, assessing the effectiveness of AI-based service robots, and redesigning organizational structure to unleash the power of business analytics.