DE

Modul

Data Science: Evidence-based Marketing [M-WIWI-101647]

Credits
9
Recurrence
Jedes Semester
Duration
2 Semester
Language
German
Level
4
Version
5

Responsible

Organisation

  • KIT-Fakultät für Wirtschaftswissenschaften

Part of

Bricks

Identifier Name LP
T-WIWI-107720 Market Research 4.5
T-WIWI-103139 Marketing Analytics 4.5

Competence Certificate

The assessment is carried out as partial exams (according to Section 4 (2), 1-3 SPO) of the courses of this module, whose sum of credits must meet the minimum requirement of credits of this module. The assessment procedures are described for each course of the module separately.

The overall grade of the module is the average of the grades for each course weighted by the credits and truncated after the first decimal.

Competence Goal

Students

  • possess advanced knowledge of relevant market research contents
  • know many different qualitative and quantitative methods for measuring customer behavior, preparation of strategic decisions, making causal deductions, usage of social media data and sales forecasting
  • possess the statistical skills required for working in marketing research

Prerequisites

Keine.

Content

This module provides in-depth knowledge of relevant quantitative and qualitative methods used in market research.Students can attend the following courses:

  • The course “Market Research” provides contents of practical relevance for measuring customer attitudes and customer behavior. The participants learn using statistical methods for strategic decision-making in marketing. Students who are interested in writing their master thesis at the Marketing & Sales Research Group are required to take this course.
  • The course "Marketing Analytics“ is based on "Market Research“ and teaches advanced statistical methods for analyzing relevant marketing and market research questions. Please note that a successful completion of "Market Research" is a prerequisite for the completion of "Marketing Analytics".

Recommendation

None

Workload

The total workload for this module is approximately 270 hours.