Introduction to Decision Science for Marketing
Learn data-driven marketing decisions using analytics, from customer profiling to predictive marketing strategies.
Learn data-driven marketing decisions using analytics, from customer profiling to predictive marketing strategies.
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 Machine Learning for Marketing 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.
Instructors:
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What you'll learn
Understand data-driven marketing decision processes
Apply analytics techniques to marketing problems
Develop customer profiling and segmentation strategies
Implement value-based marketing approaches
Create predictive marketing campaigns
Skills you'll gain
This course includes:
2.8 Hours PreRecorded video
36 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 15 modules in this course
This comprehensive course introduces data analytics and decision science principles for marketing applications. Students learn to leverage data for marketing decisions, covering topics from customer profiling and lifetime value analysis to predictive marketing strategies. The curriculum emphasizes practical applications of analytics in marketing contexts, teaching students how to use data-driven insights for customer segmentation, lifecycle marketing, and value optimization.
Introduction to Decision Science for Marketing
Module 1 · 1 Hours to complete
Building Customer Profiles to Optimize Enterprise Value
Module 2 · 2 Hours to complete
Weekly Summative Assessment: Introduction to Decision Science for Marketing and Building Customer Profiles
Module 3 · 1 Hours to complete
Life Cycle Marketing: Predicting the Customer Journey
Module 4 · 1 Hours to complete
Predict Customer Value and Their Likelihood to Buy/Engage
Module 5 · 1 Hours to complete
Recommend Products to Each Customer Individually
Module 6 · 1 Hours to complete
Weekly Summative Assessment: Life Cycle Marketing
Module 7 · 1 Hours to complete
Predict Customer Personas and Convert More Customers
Module 8 · 1 Hours to complete
Grow Customer Value
Module 9 · 59 Minutes to complete
Retention of Customers
Module 10 · 1 Hours to complete
Weekly Summative Assessment: Predict Customer Personas
Module 11 · 1 Hours to complete
How to Use Predictive Analytics in Marketing
Module 12 · 52 Minutes to complete
Useful Tools
Module 13 · 50 Minutes to complete
What It Needs to Be a Successful Predictive Marketer
Module 14 · 3 Hours to complete
Weekly Summative Assessment: Final Assessment
Module 15 · 1 Hours to complete
Fee Structure
Instructor
Assistant Professor in Information Technology and Systems at Jindal Global Business School.
Lalit Pankaj is an Assistant Professor in the Information Technology and Systems area at Jindal Global Business School, O.P. Jindal Global University, India. He teaches courses on Management Information Systems, Digital Transformation, Data Analytics, and Socio-Technical Systems. Lalit completed his PhD in Management Information Systems from the Indian Institute of Management Calcutta and holds a Master’s degree in Development Studies from the Tata Institute of Social Sciences, along with a B.Tech in Computer Science and Engineering from the Indian Institute of Technology Guwahati. With five years of diverse work experience, he initially worked in software development before serving as a Prime Minister’s Rural Development Fellow (PMRDF) for three years, focusing on innovative ICT for development projects in underdeveloped districts in India. His research interests include the dialectic relationship between humans and ICT, specifically in areas such as Sociomateriality, ICT and Development, ICT and Organizations, Social Media, Affordances, and IT Emergence.
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