Online Short-Course | In collaboration with Columbia University

Marketing Analytics

Marketers want to understand and forecast how customers purchase products and services and how they respond to marketing initiatives. Learn how analytics help businesses drive marketing to maximise its effectiveness and omarketptimise return on investment (ROI).

In this course, part of the Business Analytics MicroMasters® programme, discover how to develop quantitative models that leverage business data, statistical computation, and machine learning to forecast sales and marketing impact for:

  • customer relationship management
  • market segmentation
  • value creation
  • communication
  • monetisation.

You will learn how to use probabilistic models and optimisation tools to model customer demand forecasts, pricing sensitivity, Lifetime Value and how to leverage such data to make optimal decisions on designing new products, marketing segmentation and strategy.

Associated Programmes: Business Analytics MicroMasters® Programme

Business Analytics MicroMasters® Programme

Columbia’s MicroMasters® programme in Business Analytics will empower learners with the skills, insights and understanding to improve business performance using data, statistical and quantitative analysis, and explanatory and predictive modelling to help make actionable decisions.

Analytics in Python

Learn the fundamental of programming in Python and develop the ability to analyse data and make data-driven decisions.

Data, Models and Decisions in Business Analytics

Learn fundamental tools and techniques for using data towards making business decisions in the face of uncertainty.

Marketing Analytics

Develop quantitative models that leverage business data to forecast sales and support important marketing decisions.

Demand and Supply Analytics

Learn how to use data to develop insights and predictive capabilities to make better business decisions.

Prerequisites:

  • Undergraduate probability, statistics and calculus.
  • Familiarity with R or a similar programming language.

More

No Need to Travel

28th January 2019

R5 037.00

12 Weeks

8-10 hrs effort per week

Demand forecasting using customer-base models and statistical approaches

Market segmentation methods and best practices for identifying potential customer segments and focused targeting

Computation of Customer Lifetime Value for analysing customer, brand loyalty and forecasting revenue in the short and long run

Factors to consider while designing and introducing new products to the market

Calculating Optimal Pricing for products and services to get the best ROI

Assessing Marketing ROI for making better and data-driven decisions

Course Syllabus:

Week 1: Introduction to Marketing Analytics and Customer Analysis

Week 2: Market Segmentation

Week 3: Preference measurement

Week 4: Consumer Choice Models

Week 5: Customer Lifetime Value

Week 6: New Product Decisions

Week 7: New Product Decisions

Week 8: New Product Decisions

Week 9: Pricing Analytics and Optimisation

Week 10: Pricing Analytics and Optimisation

Week 11: Advertising

Week 12: Sales Promotions and Course Review

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