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| Semester | spring semester 2024 |
| Course frequency | Every spring sem. |
| Lecturers | Andreas Lanz (andreas.lanz@unibas.ch, Assessor) |
| Content | In today’s connected world, CMOs and marketing professionals can increasingly capitalize on rich, granular data about consumers, from geolocation through to online reviews. Merging and analyzing this (big) data allows them to inform and/or take business actions that are backed up by insights rather than intuition alone. The goal of this course is to transform you into a marketing professional that can engage in such data- driven decision-making. Focusing on secondary (already-collected) data, it offers to demystify data science and make it available to you. Using the statistical computing software R, one of the standard tools among data scientists, you will be able to listen to what consumers are telling you through their behavior, which is nowadays captured in the form of data. By mining this data using R and generating decision-relevant insights, you will be able to complement your intuition and insights from other available sources such as primary data. This will bolster your confidence as a future marketing professional in informing and/or taking business actions. Note that this is a hands-on marketing course including several practitioners: Philipp Martin, Reachbird; Christoph Bräunlich, BSI; Steffen Schmidt, LINK; Simon Stolz, Deutsche Telekom. Also note that for establishing a complete marketing mindset, combining both tactics and strategy, Marketing Analytics (which focuses more on the tactical level) is best combined with Marketing Strategy. |
| Learning objectives | At the end of the course, you will be able to generate decision-relevant insights for informing and/or taking business actions. Using the various functionalities of the statistical computing software R, you will be able to • Collect (secondary) data. • Manipulate and visualize data. • Apply statistical models. • Make data-fairness considerations. • Report insights. Overview of Lectures 1-14: 1. Getting StaRted 2. Data Manipulation, Summary Statistics, and Testing for Differences 3. Creator Economy: Research 4. Creator Economy: Practice (Guest: Philipp Martin, Reachbird) 5. Reporting 6. Basic Data Visualization 7. Advanced Data Visualization 8. Data Fairness (Guest: Christoph Bräunlich, BSI) 9. Presentations 10. (In-Sample) Fitting and (Out-of-Sample) Predictions 11. Case Study I (Guest: Steffen Schmidt, LINK) 12. Case Study II (Guest: Simon Stolz, Deutsche Telekom) 13. Case Study III 14. Presentations (and Submission of Report) |
| Bibliography | • Chapman, C. and E. McDonnell Feit (2015). R for Marketing Research and Analytics, Springer. • Wickham, H., M. Çetinkaya-Rundel, and G. Grolemund (2023). R for Data Science: Import, Tidy, Transform, Visualize, and Model Data, O’Reilly. (Link: https://r4ds.hadley.nz) • Wilke, C. O. (2019). Fundamentals of Data Visualization. (Link: https://clauswilke.com/dataviz/) • Yildirim, G. and R. Kuebler (2023). Applied Marketing Analytics Using R, Sage. |
| Comments | None |
| Admission requirements | None |
| Course application | Registration: Please enroll in the Online Services (services.unibas.ch). Eucor-Students and mobility students of other Swiss Universities or the FHNW first have to register at the University of Basel BEFORE the start of the course and receive their login data by post (e-mail address of the University of Basel). Processing time up to a week! Detailed information can be found here: https://www.unibas.ch/de/Studium/Mobilitaet.html After successful registration you can enroll for the course in the Online Services (services.unibas.ch). Applies to everyone: enrollment = registration for the assessment! |
| Language of instruction | English |
| Use of digital media | No specific media used |
| Interval | Weekday | Time | Room |
|---|---|---|---|
| wöchentlich | Tuesday | 08.15-12.00 | Wirtschaftswissenschaftliche Fakultät, Auditorium |
| Modules |
Module: Business Field: Marketing (Master's Studies: Business and Technology) Module: Business Field: Strategy and Organization (Master's Studies: Business and Technology) Module: Core Courses in Marketing and Strategic Management (Master's Studies: Business and Economics) Module: Specific Electives in Business and Economics (Master's Studies: Business and Economics) Module: Specific Electives in Labor Economics, Human Resources and Organization (Master's Studies: Business and Economics) Module: Specific Electives in Marketing and Strategic Management (Master's Studies: Business and Economics) |
| Assessment format | record of achievement |
| Assessment details | Group-project report including two presentations (attendance and participation is a must!) |
| Assessment registration/deregistration | Reg.: course registration, dereg: cancel course registration |
| Repeat examination | no repeat examination |
| Scale | 1-6 0,1 |
| Repeated registration | as often as necessary |
| Responsible faculty | Faculty of Business and Economics , studiendekanat-wwz@unibas.ch |
| Offered by | Faculty of Business and Economics |