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Marketing Analytics

Target Group Bachelor students (B.Sc.)
Course type Lecture, tutorial
Cycle Summer term
Hours per week  2 (lecture), 2 (tutorial)
Grading Written exam (120 minutes)
Credits 6 ECTS in WP 43 (Marketing and Strategy III) - PSTO 2015
Time / Room See LSF for lecture and tutorial

Course Overview

This course provides an introduction to the systematic creation of consumer insights based on large structured and unstructured data that consumers generate in their journey across different channels and touchpoints with companies (e.g., ratings, reviews, web clickstream data, transactions). Students learn about different sources and types of data, about collecting, verifying, and using data for enhanced marketing decision-making. In particular, the course presents a portfolio of tools and techniques that decision makers can use to prepare and transform different data types into adequate information to support marketing decisions. Data visualization tasks offering clear business insights will be specifically emphasized. Students’ work will be application-oriented, as they will analyze business cases and (real) datasets by using software such as SQLITE, IBM Cognos Analytics, Tableau, Rapid Miner, DataRobot, Python, Polinode, and Google Analytics.

Structure

• Sources and types of data
• Modeling types: Supervised and unsupervised learning
• Seven-step marketing analytics process
• Big data in marketing
• Database management systems
• Data quality, preparation, and transformation
• Exploratory data analysis by means of cognitive analytics
• Data visualization
• Regression analysis
• Neural networks
• Automated machine learning
• Cluster analysis
• Market basket analysis
• Natural language processing
• Social network analysis
• Digital marketing analytics

The course language is English.