Notes | The course Analytical CRM deals with methods and techniques for analysis concerning the management and improval of customer relationships. Knowledge about customers is aggregated and used for enterprise decision problems like product line planning, customer loyality, etc. A necessary precondition for these analyses is the transformation of data stemming from operative systems into a common data warehouse that assembles all necessary information. This requires transformation of data models and processes for creating and managing a data warehouse, like ETL processes, data quality and monitoring. The generation of customer oriented and flexible reports for different business purposes is covered. The course finally treats several different statistical analysis methods like clustering, regression etc. that are necessary for generating important indicators (like customer lifetime value, customer segmenatation). As external data source, customer surveys are introduced. Learning objectives: The Student
Workload: The total workload for this course is approximately 135 hours (4.5 credits): Time of attendance
Self-study
Sum: 135h 00m Exam: Assessment consists of a written exam of 1 hour length following §4 (2), 1 of the examination regulation. The exam is passed, if at least 50 out of 100 points are acquired in the written exam. In this case, all additional points (up to 5) from excersise work will be added. Grade: Minimum points
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Bibliography | Ponnia, Paulraj. Data Warehousing Fundamentals: A Comprehensive Guide for IT Professionals. Wiley, New York, 2001. Duda, Richard O. und Hart, Peter E. und Stork, David G. Pattern Classification. Wiley-Interscience, New York, 2. Ausgabe, 2001. Maddala, G. S. Introduction to Econometrics. Wiley, Chichester, 3rd Ed., 2001. Theil, H. Principles of Econometrics. Wiley, New York, 1971. |
Analytical CRM
type: | Vorlesung (V) | links: | weitere Informationen |
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semester: | SS 2019 | ||
time: | 2019-04-23 15:45 - 17:15 wöchentlich 05.20 1C-01 05.20 Kaiserstraße 89-93 (Allianz-Gebäude) 2019-04-30 15:45 - 17:15 wöchentlich 05.20 1C-01 05.20 Kaiserstraße 89-93 (Allianz-Gebäude) 2019-05-07 15:45 - 17:15 wöchentlich 05.20 1C-01 05.20 Kaiserstraße 89-93 (Allianz-Gebäude) 2019-05-14 15:45 - 17:15 wöchentlich 05.20 1C-01 05.20 Kaiserstraße 89-93 (Allianz-Gebäude) 2019-05-21 15:45 - 17:15 wöchentlich 05.20 1C-01 05.20 Kaiserstraße 89-93 (Allianz-Gebäude) 2019-05-28 15:45 - 17:15 wöchentlich 05.20 1C-01 05.20 Kaiserstraße 89-93 (Allianz-Gebäude) 2019-06-04 15:45 - 17:15 wöchentlich 05.20 1C-01 05.20 Kaiserstraße 89-93 (Allianz-Gebäude) 2019-06-11 15:45 - 17:15 wöchentlich 05.20 1C-01 05.20 Kaiserstraße 89-93 (Allianz-Gebäude) 2019-06-18 15:45 - 17:15 wöchentlich 05.20 1C-01 05.20 Kaiserstraße 89-93 (Allianz-Gebäude) 2019-06-25 15:45 - 17:15 wöchentlich 05.20 1C-01 05.20 Kaiserstraße 89-93 (Allianz-Gebäude) 2019-07-02 15:45 - 17:15 wöchentlich 05.20 1C-01 05.20 Kaiserstraße 89-93 (Allianz-Gebäude) 2019-07-09 15:45 - 17:15 wöchentlich 05.20 1C-01 05.20 Kaiserstraße 89-93 (Allianz-Gebäude) 2019-07-16 15:45 - 17:15 wöchentlich 05.20 1C-01 05.20 Kaiserstraße 89-93 (Allianz-Gebäude) 2019-07-23 15:45 - 17:15 wöchentlich 05.20 1C-01 05.20 Kaiserstraße 89-93 (Allianz-Gebäude) |
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lecturer: | Prof. Dr. Andreas Geyer-Schulz | ||
sws: | 2 | ||
lv-no.: | <a target="lvn" href="https://campus.studium.kit.edu/events/QxBVHkoYTSGu20U08TXoyQ">2540522</a> | ||