Smart Data Driven Marketing 

Objectives

In this curricular unit, students acquire the skills to make smart and impactful marketing decisions informed  by  the  right  data.  Marketing  data isbecoming  ubiquitous,  and  big  international

companies are  increasingly  investing  in  data  analytics;  however,  the  irony  of  having  too  much data is that it is often hard to distinguish the insights from the clutter, and managers end up with too much data and too little information.

Thankfully, there are common ingredients of good data analysis and marketing decisions that can enhance decision-making  confidence. Students will  acquire  the  right  mindset  and  analytic approach to transform data into insight; they will learn how to find the right data sources/typesto  inform  marketing  decision-making, and  how  to  interpret  these  data  to  make  effective marketing decisions.

General characterization

Code

14223

Credits

2

Responsible teacher

Irene Consiglio

Hours

Weekly - Available soon

Total - Available soon

Teaching language

English

Prerequisites

Available soon

Bibliography

•Boll, Jack B., Katherine L. Milkman, and John W. Payne (2015). Outsmart Your Own Biases.Harvard Business Review.

•Davenport, Thomas H. (2006). Competing on Analytics. Harvard Business Review. 

•Levitt Steven D. and Stephen J. Dubner (2014). Think Like a Freak: How to Think Smarter about Almost Everything. London, England: Allen Lane.

•MacGarvie,  Megan  and  Kristina  McElheran  (2018). Data  Analytics:  From  Bias  to  Better Decisions.Harvard Business Review.

•Thomke,  Stephan  H.  (2020). Experimentation  Works:  The  Surprising  Power  of  Business Experiments. Boston, Massachusetts: Harvard Business Review Press. 

Teaching method

Through a combination of readings, lectures, exercises and  class discussion, this curricular unit provides the latest tools, techniques and cutting-edge thinking to put Students at the forefront of making intelligent marketing decisions and realising the full potential of marketing data and analytics.

Evaluation method

This curricular unit will be assessed through an examination (50%), group work and presentation (25%) and class participation (25%).

Subject matter

GOOD DATA, BAD DATA

–Asking the right questions

Marketing problem definition

Thinking big vs. thinking small

Changing perspectives

–Finding right data & ignoring useless data

Matching marketing problems with their data

Causality vs. observation

Finding the right data

Ignoring bad data

Workshop 1: Application of theory part 1 and 2

In-class mini-cases, exercises, and class discussion

Good questions & bad questions

Good data & bad data

GOOD DECISIONS, BAD DECISIONS

–Smart data analysis

Developing critical thinking

Identifying Assumptions/Confounds

Establishing the right analysis

Experimentation assignments

–Smart decisions

Actionable insights

Deriving insights from data

Workshop 2: Application of theory part 3 and 4

In-class mini-cases, exercises, and class discussion

Good analysis & bad analysis

Good decisions & bad decisions

Programs

Programs where the course is taught: