5 crédits
30.0 h
Q2
Enseignants
Chevalier Ludovic;
Langue
d'enseignement
d'enseignement
Anglais
Préalables
1 basic marketing course
Thèmes abordés
Introduction
Humanity has generated and stored more data in the last 24 months than in the millions of years before that. World's data production, analysis, and consumption are growing exponentially and this trend is not slowing down anytime soon.
In such environment understanding and working with data has become crucial for companies to survive, innovate and grow. For this reason, companies are more and more demanding of data literate workforce - and marketing is no exception.
The fundamental pillars of marketing ' acquire and retain customers - will not change, but the means available to marketers to achieve their objectives are changing fundamentally. This course will introduce and delve into one of the most promising new mean available to marketers to achieve their objectives: Big Data.
Themes that will be addressed are:
Digital marketing (campaign/strategy), Big data, Data mining, Artificial Intelligence, AdWords, Analytics, SEA/SEO/SEM, Technologies, Multi-channel communication
Humanity has generated and stored more data in the last 24 months than in the millions of years before that. World's data production, analysis, and consumption are growing exponentially and this trend is not slowing down anytime soon.
In such environment understanding and working with data has become crucial for companies to survive, innovate and grow. For this reason, companies are more and more demanding of data literate workforce - and marketing is no exception.
The fundamental pillars of marketing ' acquire and retain customers - will not change, but the means available to marketers to achieve their objectives are changing fundamentally. This course will introduce and delve into one of the most promising new mean available to marketers to achieve their objectives: Big Data.
Themes that will be addressed are:
Digital marketing (campaign/strategy), Big data, Data mining, Artificial Intelligence, AdWords, Analytics, SEA/SEO/SEM, Technologies, Multi-channel communication
Acquis
d'apprentissage
d'apprentissage
A la fin de cette unité d’enseignement, l’étudiant est capable de : | |
| 1 | On successful completion of this program, each student will acquire the following skills :
At the end of this course, you should be able to understand and use big data in order to:
|
La contribution de cette UE au développement et à la maîtrise des compétences et acquis du (des) programme(s) est accessible à la fin de cette fiche, dans la partie « Programmes/formations proposant cette unité d’enseignement (UE) ».
Contenu
The content of the lectures (first part) will be divided into 6 Modules:
- Understanding big data and data mining.
- Structure and language of a database.
- Collecting data and working with data.
- Data mining applied to marketing.
- Focus on successful big data marketing.
- Impact of Artificial Intelligence in marketing.
Méthodes d'enseignement
Conferences, lectures, group project, exercises, articles, in-class/at-home activities, readings, self-study, discussions, case studies
Modes d'évaluation
des acquis des étudiants
des acquis des étudiants
Evaluation methods will be detailed later on.
This year (2017-2018) the course is divided into two parts that are equally weighed: weekly lectures and, in parallel, a group project. The evaluation of the first part consists of an individual written exam based on the lectures given throughout the quarter. The methods of evaluation for the second part (i.e. this year the Digital Masters challengeorganised by bloovi.me and Google: For more information click here) will be specified on Moodle.
This year (2017-2018) the course is divided into two parts that are equally weighed: weekly lectures and, in parallel, a group project. The evaluation of the first part consists of an individual written exam based on the lectures given throughout the quarter. The methods of evaluation for the second part (i.e. this year the Digital Masters challengeorganised by bloovi.me and Google: For more information click here) will be specified on Moodle.
Autres infos
Pré-requis Marketing de base Evaluation : Préparation des études de cas par groupe et/ou en individuel Support : Textbook référencé (Malaval, Mktg B2B) et transparents/cas fournis via iCampus Références : Fournies durant le cours Encadrement : Réception hebdomadaire du professeur Autres : - Eléments d'internationalisation X contenu international X études de cas internationales Interventions d'entreprises X conférence X étude de cas X intervenant du monde de l'entreprise X visite d'entreprise
Bibliographie
Slides provided through Moodle.
Additional references on the topic will be communicated later to the students.
Reference books (recommended but not compulsory):
The Big Data-Driven Business: How to Use Big Data to Win Customers, Beat Competitors, and Boost Profits by Russel Glass.
Big Data Marketing: Engage Your Customers More Effectively and Drive Value by Lisa Arthur.
(For even more:
Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die by E. Siegel
Big Data: A Revolution That Will Transform How We Live, Work, and Think by V. Mayer-Schönberger and K. Cukier
Data-driven Marketing: The 15 Metrics Everyone in Marketing Should Know by Mark Jefferey.)
Faculté ou entité
en charge
en charge
CLSM
