Unnati Narang

Unnati Narang

Assistant Professor of Business Administration and RC Evans Data Analytics Scholar

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Unnati’s research lies at the intersection of mobile marketing, consumer mobility, and engagement in digital environments. Specifically, her research examines how consumers’ use of mobile apps affects their behaviors in online and offline retail stores. She also studies how consumers’ movement patterns predict their future retail visits and the impact of new forms of mobility (e.g., e-scooters) for both consumers and retailers. She uses causal modeling, econometrics, machine learning, and deep learning approaches to examine these research themes. Unnati’s research has been published/accepted at Marketing Science, Journal of Marketing Research, the Journal of the Academy of Marketing Science, and Review of Marketing Research. She was awarded the 2019 Mathew Joseph Emerging Scholar Award, the 2019 PDMA Emerging Scholar Award, the 2019 Mays Business School Outstanding Doctoral Student Award for Research, and the 2018 Shankar-Spiegel Best Dissertation Proposal Award, the AMA Emerging Scholar Award (Retail and Pricing) 2022, and the AMA Doctoral Student Award (Retail and Pricing) 2022, and was the finalist for the EMAC-AiMark Doctoral Dissertation Award 2021.


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., & Rindfleisch, A. (2022). The "Idea Advantage": How Content Sharing Strategies Impact Engagement in Online Learning Platforms. Journal of Marketing Research, 59 (1), 61-78.
  • 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 at Urbana-Champaign, 2021 to present
  • Professional Development Grant, The European Union Center at the University of Illinois, 2021

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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