363-1043-00L  Marketing Analytics

SemesterFrühjahrssemester 2020
DozierendeS. Tillmanns
Periodizitätjährlich wiederkehrende Veranstaltung


363-1043-00 SMarketing Analytics
Irregular lecture:

19.02.2020 13:00-17:00 WEV F 109-111
04.03.2020 13:00-17:00 WEV F 109-111
11.03.2020 13:00-16:00 tba
18.03.2020 13:00-14:30 tba
01.04.2020 13:00-14:30 tba
22.04.2020 13:00-14:30 tba
06.05.2020 13:00-14:30 tba
13.05.2020 13:00-14:30 tba
20.05.2020 13:00-14:30 tba
27.05.2020 13:00-17:00 tba
24s Std.
19.02.13-17WEV F 109 »
04.03.13-17WEV F 109 »
S. Tillmanns


KurzbeschreibungStudents will use extensive customer data from an insurance company in order to develop prediction models for e.g. customer revenue and churn in a prediction challenge. They will work in groups and give a final presentation.
The class will be held by Andrea Ferrario (Mobiliar Lab for Analytics/Chair of Technology Marketing) and Sebastian Tillmanns (Chair of Technology Marketing).
Lernziel- Participants of this class will gain an understanding, how value can be generated out of customer data.
- Participants will learn how to prepare real customer data.
- Participants will be able to develop prediction models autonomously.
InhaltStudents of this class will gain an understanding how to extract value from customer data autonomously by participating in a prediction competition. Therefore, they receive real customer data from an insurance company. Students are free to prepare the provided data and develop prediction models in the way they consider the best. Their freedom of choice covers all statistical methods, software packages and data that are available to them. At the end of the class, their predictions will be compared with the real development of the customers in the provided sample. Furthermore, students will give final presentations at the end of the class, which will be joined by representatives of the insurance company. Students will have to write a short paper, in which they describe how they proceeded. We expect that students test different prediction models against each other to justify their proceeding.
At the beginning of the class, students will be able to visit several lectures, which will help to work on the given prediction task. These lectures involve fundamentals of marketing analytics and data analytics with common software packages. Throughout the lecture, several time slots are provided, where students can discuss their prediction models with the lecturers Andrea Ferrario (Mobiliar Lab for Analytics/Chair of Technology Marketing) and Sebastian Tillmanns (Chair of Technology Marketing).
The data handling and prediction skills students achieve in this class are not limited to marketing applications, but can be easily extended to other fields where predications of continuous or binary metrics are useful.


Information zur Leistungskontrolle (gültig bis die Lerneinheit neu gelesen wird)
Leistungskontrolle als Semesterkurs
ECTS Kreditpunkte3 KP
PrüfendeS. Tillmanns
Formbenotete Semesterleistung
RepetitionRepetition nur nach erneuter Belegung der Lerneinheit möglich.
Zusatzinformation zum PrüfungsmodusStudents have to form groups and turn in prediction models and a paper about these models.


Keine öffentlichen Lernmaterialien verfügbar.
Es werden nur die öffentlichen Lernmaterialien aufgeführt.


Keine Informationen zu Gruppen vorhanden.


Keine zusätzlichen Belegungseinschränkungen vorhanden.

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