B0384 - BUSINESS INTELLIGENCE E CUSTOMER RELATIONSHIP MANAGEMENT

Learning outcomes

At the end of the course, the student is able to process information about both the internal and external environment of the enterprise from large masses of data, identify relationships between phenomena and link them to the relevant problem. In addition, the student knows how and where the transactional data of the CRM process originates, learns the basics of managing an information system, and uses data with the ETL process to create an enterprise data warehouse. Thus, the course aims to impart the methodological knowledge to carry out predictive analysis (time series analysis, linear and nonlinear regression), to support business decisions (statistical decision theory), while also imparting the skills useful for understanding the ERP business information system, necessary to manage business information (knowledge management).

Course contents

• Analytical CRM.
• Information sources internal to the company: the customer databases
• Data cleaning.
• Customer acquisition.
• Behavioral segmentation and the RFM metric.
• Methods for Customer Retention and Churn Analysis: survival analysis and logistic regression.
• Lookalike processes for prospecting (hints).

Readings/Bibliography

• (Required) Kumar, V. and Petersen, A. (2012) "Statistical Methods in Customer Relationship Management," Wiley, chapters 1,2,3.4, 4.1,4.2,4.3, 6
• (Recommended) Reinartz and Kumar (2018) "Customer Relationship Management Concept, Strategy, and Tools," Springer, chapters 1, 4.1, 5, 6,8
• (Required) Bolasco, S. (1999) "Multidimensional Data Analysis," Carocci, ch.9
• Lecture notes

The textbooks (REQUIRED and RECOMMENDED) can be found in the catalog of the Bologna branch of the National Library Service. You can check their availability at the following link: http://sol.unibo.it/SebinaOpac/Opac

Lecture notes will be made available before each lecture on the e-learning platform https://virtuale.unibo.it/

The dedicated space at https://virtuale.unibo.it/ will also make available

• additional bibliographic and background materials
• sample exams

Teaching methods

Lectures involve the presentation of theoretical and applied issues of the various methods. After each theoretical session a practical tutorial is devoted to applications on real CRM problems. Applications are discussed and replicated during the computer laboratory session using SAS statistical software.

Students are invited to solve and discuss case studies. Home assignments will serve to reinforce class concepts and get familiarity with data analysis and interpretation. Home assignments will be ungraded. However, solutions (or simply a feedback) will be provided for self-assessment.

In view of the type of activities and teaching methods adopted, attendance of this training activity requires prior participation of all students in Modules 1 and 2 on safety training in the workplace [https://elearning-sicurezza.unibo.it/] , in e-learning mode.

Assessment methods

The examination is designed to ascertain theoretical knowledge of the statistical techniques explained during the lectures and the ability to apply these techniques in a CRM context starting from a customer or transaction database through the use of SAS software.
There is no distinction between attending and non-attending students.
The exam is a written test consisting of a section with 2 open-ended theoretical questions (40% of the final grade) and a practical section (60% of the final grade) consisting of 2-3 exercises requiring the interpretion of outputs already produced or to be produced from a data set (customer or transaction database) through the use of SAS software. The section with open-ended questions is aimed at testing theoretical knowledge of the topics covered in the course. The practical section is aimed at testing the ability to produce and interpret results from both a statistical and decision-making perspective with respect to the research objective at the various stages of a CRM process.

The time available to the student for the written test is 75 minutes. No materials (e.g., handout, notes) may be consulted during the conduct of the test. This is a 'closed book' examination.
The maximum score that can be given to each question, if correctly done, is indicated in the text next to each exercise.

The maximum score obtainable by giving all correct and complete answers is 30 with honors. The test is considered passed with a minimum score of 18/30. Access the virtual course page for more details.

Grading Scale

Grading of the final exam will be based on the following grid:

<18 (failed)

18-23 (sufficient): sufficient preparation but related to a limited amount of course content;

24-27 (good): adequate preparation but with some gaps with respect to course content;

28-30 (excellent): very thorough knowledge of all course content;

30 cum laude (excellent): very good knowledge of course content.

Teaching tools

The UNIBO's e-learning platform (VIRTUALE) will be used to share teaching materials and to assign students' periodic homework. Teaching materials include:

• Lecture notes summarizing the theoretical topics explained in class
• Open data and lecture notes for following the practical sessions
• Miscellanea: exercises, homework solutions, sample exams, follow-up materials.
• SAS on Demand software (https://www.sas.com/en_us/software/on-demand-for-academics.html)
  

Office hours

See the website of Ida D'Attoma