Unnati Narang

Unnati Narang

Assistant Professor of Business Administration and RC Evans Data Analytics Fellow

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Educational Background

  • Ph.D., Marketing, Mays Business School, Texas A&M University at Mays Business School, 2020
  • Masters of Commerce, Commerce, Delhi School of Economics, University of Delhi at Delhi School of Economics, 2012
  • Bachelor of Commerce, Commerce, Shri Ram College of Commerce, University of Delhi at Shri Ram College of Commerce, 2010

Positions Held

  • Assistant Professor of Business Administration, Business Administration, University of Illinois at Urbana-Champaign, 2020 to present

Recent Publications

  • Narang, U., Yadav, M., & Rindfleisch, A. Forthcoming. The ‘Idea Advantage’: The Impact of Sharing on Engagement in Massive Open Online Courses. Journal of Marketing Research.
  • Shankar, V., & Narang, U. (2020). Emerging Market Innovations: Unique and Differential Drivers, Practitioner Implications, and Research Agenda. Journal of the Academy of Marketing Science, Springer, 48 1030–1052.
  • Narang, U., & Shankar, V. (2019). Mobile App Introduction and Online and Offline Purchases and Product Returns. Marketing Science, INFORMS, 38 (5), 733-912.  link >

Other Publications

Working Papers

  • Ahsen, M., Narang, U., & Lin, Y. Competition or Collaboration? The Impact of Open Science on Healthcare Innovation.

Honors and Awards

  • RC Evans Data Analytics Scholar, University of Illinois, Gies College of Business, 2021-2022

Teaching Interests

Marketing analytics

Research Interests

Mobile and Location Marketing, Mobility and Commuting, Retailing, Digital Platforms

Current Courses

  • Marketing Analytics (BADM 361) The recent growth in structured and unstructured data combined with sophisticated techniques for leveraging these data for decision-making, creates huge opportunities for marketers. This course introduces key concepts in marketing analytics and shows how analytics can help solve real-world marketing problems. Covered topics include data scraping, text analysis, data visualization, machine learning, causal and predictive models. Each technique is implemented using "mini cases" in R programming with unique datasets from a variety of marketing contexts.

  • Advanced Marketing Management (BADM 420) Integrative study of methods and models for marketing decision-making; emphasizes the application of analytical tools and behavioral and quantitative models to marketing decision-making. Uses lectures, case studies and simulation exercises.

  • Marketing Analytics (BADM 590) Special topics in the general area of business. Topics are selected by the instructor at the beginning of each term.

  • Applying Data Analytics Mrktg (MBA 564) Develops students' knowledge regarding the role, methods, and implications of business and data analytics in business. Application opportunities span multiple areas of business. Special topics may include marketing, finance, supply chain, and accounting. Topics covered may include forecasting using time series models, modern portfolio theory, measurement and scaling, A/B testing, ANOVA, and conjoint analysis.


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