Code
MPYF MKT 6442
Level
M2
Field
Marketing, commercial
Language
Français/French
ECTS Credits
2
Class hours
28
Total student load
40
Program Manager(s)
Department
- Management, Marketing et Stratégie
Educational team
Introduction to the module
This course introduces students to different methods that are commonly used to make marketing decisions based on the collection and analysis of data. It will cover methods to segment consumers, conjoint analysis to design and price products, marketing mix models and controlled experiments to optimize the marketing mix. Tools from statistics and machine learning will be introduced in a practical way; the focus will be on their applications in business settings to make better decisions.
Learning goals
- 1. S’approprier les usages avancés et spécialisés des outils de l’intelligence digitale en s’assurant de leur impact durable et responsable
Learning objectives
- 1.1 - Audit advanced and specialised uses of digital intelligence tools in order to deploy them appropriately, taking into account the strategic context of organisations.
Course Learning objectives
At the end of this specialization course, students should be able to :
• Conduct all the steps of a conjoint analysis to generate insights on consumer preferences and recommendations on the design and price of a product
Content : structure and schedule
Session 1: Review of statistics concepts
Session 2: Cluster analysis for segmentation
Session 3: Perceptual and preference mapping
Session 4: Diffusion of innovations
Session 5: Introduction to conjoint analysis
Session 6: Steps of a conjoint analysis
Session 7: Project: implementation of a conjoint analysis
Session 8: Conjoint analysis project - group presentations
Session 9: Basics of pricing and marketing mix models
Session 10: Product line pricing
Sessions 11-12: Advertising Experiments
Day 1: Customer segmentation, preference mapping, sales forecasting
Day 2: Product Analytics using Conjoint Designs
Day 3: Pricing and Measurement of Advertising Effectiveness
Day 4: Customer Analytics
Learning delivery
synchrone
Pedagogical methods
Lectures
Case studies
Hands-on applications on datasets
Group project: implementation of a conjoint analysis
Evaluation and grading system and catch up exams
Participation: 10%
Quizzes: 10%
Group project: 30%
Final exam: 50%
The evaluation is based on several criteria: participation, engagement, course-related questions, practical applications, and a final pitch. The breakdown is as follows: 60% of the grade corresponds to individual work and 40% to collective work.
The current academic regulations serve as the reference document.
If the final grade for a module is below 10 out of 20, a resit will be organized and will count for 100% of the final grade. The resit exam will consist of an individual research, reflection, and application paper, or an oral exam, on a topic covered in the course.
Any assignment submitted after the deadline will receive a grade of 0.
Grades may be adjusted individually based on participation, including unexcused lateness or absences, classroom behavior, etc., in the form of bonus or penalty points.
Punctuality and attendance are integral to the shared learning environment. They reflect respect for the instructors’ work, the group dynamic, the school’s standards, and the professional attitude expected of students.
Any unexcused absence for a half-day of class will result in a one-point deduction from the final grade of the relevant module. This penalty may also apply to any unexcused lateness. In cases of repeated lateness or absences, the number of points deducted may be increased to ensure the smooth running of the course.
Module Policies
The current academic regulations serve as the reference document.
Professor-Student Communication
● The professor will contact the students through their school email address (IMT-BS/TSP) and the Moodle portal. No communication via personal email addresses will take place. It is the student responsibility to regularly check their IMT-BS/TSP mailbox.
● Students can communicate with the professor by emailing him/her to his institutional address. If necessary, it is possible to meet the professor in his office during office-hours or by appointment.
Students with accommodation needs
If a student has a disability that will prevent from completing the described work or require any kind of accommodation, he may inform the program director (with supporting documents) as soon as possible. Also, students are encouraged to discuss it with the professor.
Class behavior
● Out of courtesy for the professor and classmates, all mobile phones, electronic games or other devices that generate sound should be turned off during class.
● Students should avoid disruptive and disrespectful behavior such as: arriving late, leaving early, careless behavior (e.g. sleeping, reading a non-course material, using vulgar language, over-speaking, eating, drinking, etc.). A warning may be given on the first infraction of these rules. Repeated violators will be penalized and may face expulsion from the class and/or other disciplinary proceedings.
● The tolerated delay is 5 minutes. Attendance will be declared on Moodle during these 5 minutes via a QR code provided by the teacher at each course start.
● Student should arrive on time for exams and other assessments. No one will be allowed to enter the classroom once the first person has finished the exam and left the room. There is absolutely no exception to this rule. No student can continue to take an exam once the time is up. No student may leave the room during an examination unless he / she has finished and handed over all the documents.
● In the case of remote learning, the student must keep his camera on unless instructed otherwise by the professor.
Honor code
IMT-BS is committed to a policy of honesty in the academic community. Conduct that compromises this policy may result in academic and / or disciplinary sanctions. Students must refrain from cheating, lying, plagiarizing and stealing. This includes completing your own original work and giving credit to any other person whose ideas and printed materials (including those from the Internet) are paraphrased or quoted directly. Any student who violates or helps another student violate academic behavior standards will be penalized according to IMT-BS rules.
Students are expected to arrive on time. If a student arrives more than 15 minutes late, he or she will not be allowed to sign on EduSign.
Some sessions will start with a 5-minute quiz. Students arriving late will receive a zero on quizzes.
The use of a calculator will be allowed (and encouraged) for the final exam.
Students will present their group project in English: they will not be allowed to look at their phones during the presentation.
Textbook Required and Suggested Readings
Palmatier, Petersen, Germann: Marketing Analytics Based on First Principles (2022)
Keywords
Data marketing, Customer analytics, Product analytics, Marketing mix models, Segmentation
Prerequisites
Familiarity with Excel