Code
MPYF MKT 6442
Niveau
M2
Discipline
Marketing, commercial
Langue
Français/French
Crédits ECTS
2
Heures programmées
28
Charge totale étudiant
40
Coordonnateur(s)
Département
- Management, Marketing et Stratégie
Equipe pédagogique
Introduction au 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.
Finalité d'apprentissage (Bloc de compétences)
- 1. S’approprier les usages avancés et spécialisés des outils de l’intelligence digitale en s’assurant de leur impact durable et responsable
Objectifs d'apprentissage
- 1.1 - Auditer les usages avancés et spécialisés des outils de l'intelligence digitale, afin de les mobiliser avec pertinence, en tenant compte du contexte stratégique des organisations.
Traits de compétences
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
Contenu : structure du module et agenda
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
Apprentissage
synchrone
Méthode pédagogique
Lectures
Case studies
Hands-on applications on datasets
Group project: implementation of a conjoint analysis
Système de notation et modalités de rattrapage
Participation : 10%
Quiz : 10%
Projet de groupe: 30%
Examen final: 50%
L’évaluation repose sur plusieurs critères : la participation, l’implication, les questions de cours, applications, ainsi qu’un pitch final. La répartition est la suivante : 60 % de la note concerne le travail individuel et 40 % le travail collectif.
Le règlement de scolarité en vigueur constitue le document de référence.
En cas de note finale inférieure à 10 sur 20, un rattrapage est organisé et compte pour 100% de la note finale. Le rattrapage consistera en un dossier individuel de recherche, de réflexion et d’application, ou un examen oral, sur une thématique du cours.
Tout devoir remis hors délai sera crédité de la note de 0.
Les notes peuvent être individualisées selon la participation (retard ou absence non excusée en cours, comportement en cours, etc.) sous la forme d'un bonus ou d'un malus de points. La règle de ponctualité et de présence fait partie intégrante du cadre de vie et d’apprentissage porté collectivement, elle traduit le respect du travail des enseignants, du groupe et des exigences de l’école ainsi qu'une posture professionnelle attendue des étudiants. Toute absence non justifiée d'une demi-journée de classe entraînera une pénalité d’un point sur la note finale du module concerné. Cette sanction pourra également s’appliquer à tout retard non justifié. En cas de retards ou d’absences répétés, le nombre de points retirés pourra être augmenté, afin de garantir le bon déroulement des enseignements.
Règlement du module
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.
Références obligatoires et lectures suggérées
Palmatier, Petersen, Germann: Marketing Analytics Based on First Principles (2022)
Mots-clés
Data marketing, Customer analytics, Product analytics, Marketing mix models, Segmentation
Prérequis
Familiarity with Excel