Introduction to Decision Science for Marketing

This course is part of Machine Learning for Marketing Specialization

Instructor: Prof. Lalit Pankaj

What you'll learn

  •   Demonstrate a solid understanding of the decision-making process through data analytics.
  •    Visualize and imagine the application of data analytics techniques to real-world marketing problems.
  •   Explain how marketing analytics and decision science approaches for marketing can enhance the quality of marketing decision-making.

    • Skills you'll gain

  •   Customer Acquisition Management
  •   Data-Driven Decision-Making
  •   Business Analytics
  •   Marketing Analytics
  •   Predictive Analytics
  •   Consumer Behaviour
  •   Marketing Strategies
  •   Customer experience improvement
  •   Customer Retention
  •   Loyalty Programs
  •   Customer Insights
  •   Personalized Service
  •   Customer Analysis

    • There are 15 modules in this course

    This beginner-level course provides awareness about the present practice of data-driven decision-making in the marketing discipline. This will help you familiarize yourself with practical tips about when and where to use various techniques and tools. You will learn about critical theories and concepts with the help of relevant examples. To succeed in this course, you should have basic clarity of concepts of the marketing discipline. As a prerequisite for the course, you should know key marketing terms, such as segmentation, targeting, and positioning. After the successful completion of this course, you will have basic understanding of how to use data for making marketing predictions. You will have sufficient knowledge of foundational elements, the relationship between data and marketing constructs/concepts, and how decision science and marketing work in tandem to produce relevant insights for today’s market. Finally, the course provides concrete strategies to start with decision science in marketing.

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    Weekly Summative Assessment: Introduction to Decision Science for Marketing and Building Customer Profiles to Optimize Enterprise Value

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    Predict Customer Value and Their Likelihood to Buy/Engage

    Recommend Products to Each Customer Individually

    Weekly Summative Assessment: Life Cycle Marketing: Predicting the Customer Journey, Customer Value, and Their Likelihood to Buy/Engage

    Predict Customer Personas and Convert More Customers

    Grow Customer Value

    Retention of Customers

    Weekly Summative Assessment: Predict Customer Personas and Convert More Customers, Grow Customer Value, and Retention of Customers

    How to Use Predictive Analytics in Marketing

    Useful Tools

    What It Needs to Be a Successful Predictive Marketer

    Weekly Summative Assessment: How to Use Predictive Analytics in Marketing, Useful Tools, and What It Needs to Be a Successful Predictive Marketer

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