About this courseSkip About this course
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 maximize its effectiveness and optimize return on investment (ROI).
In this course, part of the Business Analytics MicroMasters program, 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;
You will learn how to use probabilistic models and optimization 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.
At a glance
- Institution: ColumbiaX
- Subject: Business & Management
- Level: Advanced
Undergraduate probability, statistics and calculus.
Familiarity with R or a similar programming language.
- Language: English
- Video Transcript: English
What you'll learnSkip What you'll learn
Skills acquired after the course:
- 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 analyzing 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
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 Optimization
Week 10: Pricing Analytics and Optimization
Week 11: Advertising
Week 12: Sales Promotions and Course Review