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
At the end of this learning unit, the student is able to :
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:
The contribution of this Teaching Unit to the development and command of the skills and learning outcomes of the programme(s) can be accessed at the end of this sheet, in the section entitled “Programmes/courses offering this Teaching Unit”.
- 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.
Due to the COVID-19 crisis, the information in this section is particularly likely to change.Conferences, lectures, group project, exercises, articles, in-class/at-home activities, readings, self-study, discussions, case studies
Due to the COVID-19 crisis, the information in this section is particularly likely to change.Evaluation methods will be detailed later on.
This year (2019-2020) the course is divided into two parts: 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 will be specified on Moodle.
The weight of the total mark will be split as followed:
- 60% for the individual exam.
- 40% for the group assignment.
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.)