Applying Data Analytics in Marketing
Master marketing analytics through causal analysis, survey analysis, text analysis, and network analysis using R for data-driven decisions.
Master marketing analytics through causal analysis, survey analysis, text analysis, and network analysis using R for data-driven decisions.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Business Analytics Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
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English
پښتو, বাংলা, اردو, 3 more
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What you'll learn
Apply causal analysis to marketing data
Analyze survey data using regression methods
Perform text and sentiment analysis
Conduct network analysis for social media data
Make data-driven marketing decisions
Skills you'll gain
This course includes:
4.1 Hours PreRecorded video
5 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This comprehensive course introduces students to marketing analytics through various analytical tools and approaches. The curriculum covers causal analysis, survey analysis using regression, textual analysis including sentiment analysis, and network analysis. Students learn to make better marketing decisions by analyzing multiple types of data related to customer satisfaction, utilizing R programming for hands-on analysis.
Course Introduction and Module 1: Causal Analysis
Module 1 · 5 Hours to complete
Module 2: Survey Analysis
Module 2 · 1 Hours to complete
Module 3: Text Analysis
Module 3 · 4 Hours to complete
Module 4: Network Analysis
Module 4 · 2 Hours to complete
Fee Structure
Instructors
Assistant Professor of Business Administration and John M. Jones Fellow of Marketing and Deloitte Scholar
Unnati Narang is an Assistant Professor of Business Administration and the John M. Jones Fellow of Marketing at the Gies College of Business, University of Illinois Urbana-Champaign. With a Ph.D. in Marketing from Mays Business School, Texas A&M University, she has established herself as a prominent figure in the field of marketing, focusing on mobile and location marketing, consumer mobility, and engagement in digital environments. Her research examines how interactions with mobile technologies influence consumer behavior in both online and offline retail contexts, utilizing methods such as causal modeling, econometrics, and machine learning.In addition to her research pursuits, Professor Narang is dedicated to teaching courses that bridge data analytics and marketing, including "Applying Data Analytics in Marketing" and "Introduction to Business Analytics: Communicating with Data." Her commitment to fostering an inclusive and engaging learning environment has earned her recognition as one of the best undergraduate professors. Unnati's innovative approach to education combines real-world applications with academic rigor, preparing her students for success in a rapidly evolving business landscape.
Research Professor
Joseph T. Yun is a Research Professor of Electrical and Computer Engineering at the University of Pittsburgh, where he also serves as the Artificial Intelligence and Innovation Architect. With a focus on developing novel data science algorithms and user-centric analytics systems, his research addresses critical societal considerations related to AI-based advertising and marketing, including privacy and ethics. Dr. Yun is the principal investigator of the Social Media Macroscope, an open research environment dedicated to social media analytics, which facilitates innovative research in this rapidly evolving field.In addition to his research endeavors, Dr. Yun is actively involved in various initiatives aimed at enhancing the understanding of AI's impact on society. He is affiliated with Pitt Cyber and the Collaboratory Against Hate, where he contributes to discussions on the ethical implications of technology. His expertise spans multiple domains, including computational advertising and digital marketing strategies, making him a prominent figure in the intersection of technology and social science. Through his courses, such as "Applying Data Analytics in Marketing," Dr. Yun aims to equip students with the skills necessary to navigate the complexities of modern data-driven environments.
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4.5 course rating
151 ratings
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