Artesis Plantijn Hogeschool Antwerpen
Management en Communicatie
campus Meistraat
Meistraat 5 - 2000 Antwerpen
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mc@ap.be
ICBM: Data-driven Marketing31123/1894/2021/1/75
Study guide

ICBM: Data-driven Marketing

31123/1894/2021/1/75
Academic year 2020-21
Is found in:
  • International programmes Management and Communication, programme stage 2
This is a single course unit.
Study load: 3 credits
It is not possible to enrol in this course unit under
  • exam contract (to obtain a credit).
  • exam contract (to obtain a degree).
Teaching staff: Heirman Wannes
Languages: English
Scheduled for: Semester 2
This course unit is marked out of 20 (rounded to an integer).
Possible deadlines for learning account: 15.03.2021 ()
Re-sit exam: is possible.
Possibility of deliberation: This course unit is eligible for deliberation according to the criteria as determined by the degree programme you are enrolled in.
Total study time: 75,00 hours

Short description

Until the late 1980s, marketing was a profession in which marketers - in addition to sales figures - were mainly guided by their ‘gut feeling’ to support their decisions. However, since the early 1990s, rapid technological advances have changed the way marketing departments support their marketing decisions. Today we have entered the era of "Big Data". In addition, data from all commercial transaction systems are these days combined with data traces that customers leave, when visiting websites and their behavior on social media.

For marketers, data about their current and future customers is increasingly the “new gold”. The best way to retain an existing customer in your company or to seduce a new customer into your company, is to collect data and let these data inspire your approach towards the respective customer. In this course you will learn how to make better decisions as a marketer by working in an evidence-based way and by using your customer data in every marketing activity you undertake. Also, by following this course you will learn everything you need to know to survive in a data-driven marketing landscape.

Prerequisites

There are no prerequisites for this course.

Learning outcomes (list)

The student differentiates clients in terms of importance on the basis of a R(ecency)F(requency)M(onetary value) and/or other formula.
The student is aware of the international and supra-national legal aspects governing the commercial processing of client data
The student has insight in the structure of commercial datasets.
The student is able to integrate several data silos into one data warehouse
The student can predict on the basis of variables within the data set which clients/prospects will accept a commercial offer via a direct marketing channel
The student knows how to use insights gained from a commercial data set in the planning of a marketing campaign
The student is able to make marketing related decisions on the basis of an A/B-test and of an experimental design in a commercial dataset
The student is able to segment a commercial data set in order to enable personalised nano-marketing
The student understands the different direct marketing mix tools
The student is familiar with the pro's and con's of e-mail and social media marketing

Course content

Chapters offered in this course are:
-basic insights to become a data-driven marketer
-needed skills to become a data-driven marketer
-predicting consumer reactions
-carrying out data-driven experiments
-using data to improve traditional marketing and sales
-using data as a guidance in direct marketing
-using data in tele-marketing
-using data to optimize email marketing
-using data to optimize social media marketing
-the hardware and software for data-driven marketing

Study material (text): Mandatory

The study material for this course includes:

-Powerpoint slides

-Notes taken during the lesson



Recommended Literature:

Jeffery, M. (2010). Data-driven Marketing. Oxford: John Wiley & Sons

Graydon. (2016). Data-driven Marketing: Handbook: Graydon. 

Educational organisation (list)

Learning Activities
Lectures and / or tutorials24,00 hours
Work time outside of contact hours51,00 hours

Evaluation (list)

Evaluation(s) for first exam chance
MomentForm%Remark
Semester 2Knowledge test100,00Written exam
Evaluation(s) for re-sit exam
MomentForm%Remark
2nd examination periodKnowledge test100,00Written exam