87363 - CUSTOMER VALUE MANAGEMENT

Conoscenze e abilità da conseguire

By the end of this course students are able to: - apply relevant concepts of business analysis to marketing problems - familiarize with different types of real world data, and some advanced statistical techniques that can be applied to analyze customer-level data - acquire tools and skills needed to evaluate the appropriateness, performance, and value of different marketing models - stimulate students working in teams to simulate real market research contexts

Contenuti

This course explores key challenges in both business-to-business and business-to-consumer marketing from the perspectives of buyers and sellers, combining methodological and applied approaches. Students will learn how to apply data analysis techniques to marketing decision-making, with a strong focus on customer satisfaction, CRM, and customer profitability. The first module emphasizes the role of customer satisfaction in driving loyalty and profitability, guiding students through methods for measuring and managing customer satisfaction and translating insights into commercial strategies. The second module focuses on customer value, equipping students with tools to segment customers, deliver value through distribution, and optimize pricing and promotion. Through case studies, lab exercises, and teamwork, participants will gain hands-on experience applying analytical tools to real-world marketing problems.

Structure of the course:

Module 1 (Gian Luca Marzocchi)

1. Course introduction. The key role of relationships. Customer relationship management (CRM) as evolution of the marketing concept. From transaction to relationship, from mass marketing to customer marketing, from market share to customer share. (G.L. Marzocchi)
2. CRM and Customer satisfaction. Customer Lifetime Value as key indicator of customer profitability. Measuring Customer Lifetime Value. (G.L. Marzocchi)
3. Measuring Customer Lifetime Value (cont'd). CLV and word of mouth: the value of referrals. Measuring Customer Satisfaction: theory and methods. (G.L. Marzocchi)
4. Overall CS and key satisfaction drivers. Importance/ performance grid. Stated-importance versus derived importance scores. Presentation and discussion of the group project work CLV. (G.L. Marzocchi)
5. Stated-importance versus derived importance scores (cont’d). (G.L. Marzocchi)
6. Analytical models of CS. Designing and implementing a customer satisfaction survey. (G.L. Marzocchi)
7. Measuring Customer Satisfaction thru a (very) popular technique: the Tri*m Grid approach. The Tri*m index. The structure of the Tri*m matrix. The relevant dimensions: stated importance of the attributes, derived importance (impact on retention), relative performance of the attributes. Building and using the matrix. (G.L. Marzocchi)
8. Presentation and discussion of the group project work Alma Hotel. Guest lectures. (G.L. Marzocchi)
9. Trim Grid: The Trim Grid at Work: cases and examples. (G.L. Marzocchi)
10. Guest lecture: CRM and CS: lessons from the field - Presentation and discussion of the CS Tri*m survey project work. (G.L. Marzocchi)

 

Module 2 (Gabriele Pizzi)

1. Customer Satisfaction - Customer Segmentation and Cluster Analysis (G. Pizzi)
2. Analyzing satisfaction and segmentation data (G. Pizzi)
3. Perceptual Maps for Targeting and Positioning (G. Pizzi)
4. Perceptual Maps: data preparation and analysis (G. Pizzi)
5. Conjoint Analysis for pricing/product decisions (G. Pizzi)
6. Conjoint Analysis: collecting and analyzing data (G. Pizzi)
7. Experimental Studies in Consumer Research; Mediation and Moderation (G. Pizzi)
8. Analyzing and Collecting Experimental Data; Mediation and Moderation with PROCESS (G. Pizzi)
9. Course Wrap-up (G. Pizzi)
10. Team-work class presentation (G. Pizzi)

 

Testi/Bibliografia

Module 1 (Gian Luca Marzocchi)

A reading package will be made available by the instructor at the beginning of the course

 

Module 2 (Gabriele Pizzi)

The module is mainly practical in its nature. Therefore, the best way to learn is actively participate in class discussion and laboratory exercises. Lecture slides can be used as a tool to support learning in class. There are not mandatory readings for this course. However, students might make reference to the following two books aimed to deepening either the theoretical concepts or the methodological issues.

1) Winer & Dhar – Pearson Ed. “Marketing Management (4^th Edition)

2) Mazzocchi, M. (2008). Statistics for marketing and consumer research. Sage.

 

Metodi didattici

The course teaching methods includes cases discussions, desk analyses of customer satisfaction data sets and group project work to allow participants to apply to real settings the concepts and techniques that have been analyzed during the course.

 

Modalità di verifica e valutazione dell'apprendimento

There will be different assessments methods for each module. The grades of the two modules will be averaged (simple average) to compute the final grade of the complete Customer Value Management class.

 

Module 1 (Gian Luca Marzocchi)

Final written exam (exam duration: 75 min) plus assessment of three compulsory team-based project works.

Marks are intended on a numerical grade scale (0 to 30), being 18 to 30 the passing grade range. 

The final examination will consist of open-ended questions and/or short analytical exercises concerning the topics discussed during the course.

Course evaluation is detailed in the following:

 

All students:

Component Weight (%)

Final Exam 50

Project work 1 10

Project work 2 15

Project work 3 25

 

Module 2 (Gabriele Pizzi)

Though not compulsory, participation in team-work assignments is strongly encouraged. Team-work assignments consist of:

One final team-work project: students will be asked to work in group on a project (i.e. analyzing an industry by segmenting customers and mapping the positioning of the main players in the industry) and to present in class the results and the managerial consequences of their project.

Course evaluation will be different depending on the eventual participation in team-work assignment, as detailed in the following:

Course evaluation will be different depending on the non-compulsory participation in team-work assignment, as detailed in the following:

 

Students participating in team-work assignments:

Component Weight (%)

Final Exam 70

Group Project 30

 

Students who do not participate in team-work assignments:

Component Weight (%)

Final Exam 100

Group Project   0

 

Final exams and group projects structure and evaluation

Module 1 (Gian Luca Marzocchi)

The development of the group project works (maximum 8 members per group, minimum 4) allows students to apply all the knowledge acquired during the course. The objective of the projects—consistent with the course's placement in a Master’s program—is to acquire (and demonstrate) operational skills in designing and conducting professional-level research studies on the topic of Customer Value and Customer Satisfaction evaluation.

The first and second project works are desk analyses based upon case studies and data sets provided by the instructor. The third and most important project involves several stages: defining the research subject, analyzing information needs, conducting a literature review, carrying out the exploratory phase of the research (including in-depth interviews and focus groups), developing an appropriate measurement tool (questionnaire), defining a sampling plan, collecting data, and, of course, analyzing the data using multiple methods. The final deliverable also includes a professionally structured PowerPoint presentation.

Project works are subject to peer evaluation, where each group member evaluates their peers based on both their factual contributions and idea generation throughout the project. If a student's peer evaluation score is more than 10% below the group average, their group individual grade will be reduced by the same percentage, up to a maximum penalty of 25%.

 

 Module 2 (Gabriele Pizzi)

The final written exam will consist of the interpretation of a couple of SPSS outputs by proposing a) the conclusions that can be drawn from the data, and b) the managerial consequences of the findings reported on the outputs, backed by the theory studied in class.

Team-work assignments consist of one final team-work project: students will be asked to work in group on a project (i.e. analyzing an industry by segmenting customers and mapping the positioning of the main players in the industry) and to present in class the results and the managerial consequences of their project.

 

Exam policy

Students will separately sit for the exams of the two modules, at the end of each module. The final grade of the course will be given by the simple average of the grades of the two modules. In order to pass the course, students must pass each of two modules (i.e. grade not lower than 18)

The project works are graded according to the following scale:

28–30 with honors: correct, thorough, and sufficiently complex project demonstrating full mastery of the course topics and consistent execution skills, with at most minimal inaccuracies

24–27: project not entirely correct and/or incomplete, but showing a good level of understanding of the course content and solid execution skills

18–23: project with significant methodological errors or major analytical weaknesses, yet showing just sufficient execution ability

0–17: project inadequate in terms of methodology and data analysis

The purpose of the written exam is to assess the student’s ability to apply their knowledge and make logical and deductive connections. The written examination will consist of open-ended questions and/or short analytical exercises concerning the topics discussed during the course. The grading criteria are as follows:

Comprehensive preparation on all course topics, with the ability to independently conduct critical analysis and make connections, full command of terminology, and strong argumentation and self-reflection skills → 30–30 with honors

Preparation on a wide range of course topics, with the ability to make independent critical assessments and good command of specific terminology → 25–29

Preparation on a limited number of topics, with independent analytical ability limited to procedural issues; correct language use → 20–24

Preparation on a very limited number of course topics, with analytical skills emerging only with the instructor’s assistance; overall correct language use → 18–19

Preparation inadequate in terms of topic knowledge and critical analysis → 0–17

Erasmus: at most 15 Erasmus and Overseas students, selected in chronological order, will be admitted to the course and the exam.

Students with disability or specific learning disabilities (DSA) are required to make their condition known to find the best possibile accommodation to their needs.

 

Strumenti a supporto della didattica

Tools, platforms, or resources used during the course:

• Presentation software: PowerPoint
• Communication tools: Virtuale (virtuale.unibo.it), Dropbox, Email, Teams, Forum on Virtuale
• Other digital tools/software: SPSS, Excel

 

Orario di ricevimento

Consulta il sito web di Gian Luca Marzocchi

Consulta il sito web di Gabriele Pizzi