Admission requirements
Master Marketing Science course (Business Studies) or Minor Marketing course (SBI Minor) completed
- or an equivalent, in that case please consult your master program contact (see under Contact) before signing up for this course for confirming that you meet the admission requirements.
Description
This course provides an introduction to the application of information technology and data science in the marketing domain, also known as Marketing Analytics (MA).
This multi-disciplinary field has seen a growing interest over the last years. Businesses and organisations are facing both huge opportunities ánd challenges provided by the massive use of powerful digital media by their prospects and customers.
Classic marketing approaches are becoming less effective, a clear need exists for establishing interactive, personalised relationships and relevant dialogues, fueled by a superb user experience and an omni-channel approach.
Here is where marketing analytics comes into play, by building a holistic customer view based on the digital footprint, advanced analytics, machine learning and (Generative) AI techniques, and using that to drive highly targeted customer interactions. The rapid developments of cloud platforms and AI technologies are strong enablers for transforming MA.
Yet, data privacy and AI law and regulations demand that consumers get more insight and control over their personal data and AI-powered applications. This calls for a more balanced exchange of personal data for value to the customer, based on the principles of privacy by design.
The hybrid nature of marketing analytics and the rapid developments in technology call for agile, cross-functional approaches and a blending of marketing and IT skill sets.
We will cover a broad spectrum of topics by linking current business practices to concepts and vice versa. Starting with the fundamentals of customer-centricity, we will explore how data is connected to customer journeys, address customer data management including privacy aspects, (digital) marketing technologies and advanced analytical techniques. We will use a hands-on approach to understand the practical application of marketing analytics in some typical use cases. Finally we will explore the organisational impact for realising the huge potential of marketing analytics.
Students are expected to have a good understanding of the basic concepts, frameworks and instruments of marketing - see under Admission Requirements.
Course objectives
By the end of the course, the student should be able to:
understand and apply the strategies, basic concepts, frameworks and processes of marketing analytics;
identify, understand and apply customer data (incl. privacy regulations);
identify, understand and apply MA technologies to improve marketing performance and customer engagement;
understand, apply, analyse and evaluate how to organise, plan and design for data-driven marketing practice.
Timetable
In MyTimetable, you can find all course and programme schedules, allowing you to create your personal timetable. Activities for which you have enrolled via MyStudyMap will automatically appear in your timetable.
Additionally, you can easily link MyTimetable to a calendar app on your phone, and schedule changes will be automatically updated in your calendar. You can also choose to receive email notifications about schedule changes. You can enable notifications in Settings after logging in.
Questions? Watch the video, read the instructions, or contact the ISSC helpdesk.
Note: Joint Degree students from Leiden/Delft need to combine information from both the Leiden and Delft MyTimetables to see a complete schedule. This video explains how to do it.
Mode of instruction
The programme will consist of 6 lectures that cover the following topics.
1. Introduction to Marketing Analytics (MA): course overview, MA concepts, trends, processes and applications;
2. MA strategy: the strategic context of MA; marketing metrics; overview of MA applications;
3. Data & Privacy: customer data & integration, data quality, data protection and privacy aspects;
4. MA Technology: marketing software platforms, analytical tools, AI/ML/big data platforms and technologies;
5. MA Lab: hands-on cases on customer segmentation, predictive modelling, and web analytics;
6. Organising for MA: marketing and IT organisations, sourcing, agile marketing, marketing science skills
Students are expected to attend in class, on premise, as to stimulate interaction and learning, and have read specific textbook chapters before class.
Assessment method
Assessment will be done by these 3 methods:
Participation (in-class pop quizzes)
Assignments (homework, both individual and in groups)
Exam (2 parts, closed book)
Partial grades will be given for these 3 assessment methods, with these weights:
Participation: 10%
Assignments: 30%
Exam: 60%
See detailed information below (under Remarks) on the minimum requirements to pass this course.
The teacher will inform the students how the inspection of the exams will take place.
Reading list
The presentations and background articles will be available on Brightspace. References to articles and books will be provided during the lectures.
Textbook (mandatory):
Verhoef, P. C., Kooge, E., Walk, N., & Wieringa, J. E. (2022). Creating Value with Data Analytics in Marketing (2nd edition). Taylor & Francis.
ISBN: 978-0-367-81978-1 (hardcover), 978-0-367-81979-8 (paperback), 978-1-003-01116-3 (e-book)
Registration
As a student, you are responsible for enrolling on time through MyStudyMap.
In this short video, you can see step-by-step how to enrol for courses in MyStudyMap.
Extensive information about the operation of MyStudyMap can be found here.
There are two enrolment periods per year:
Enrolment for the fall opens in July
Enrolment for the spring opens in December
See this page for more information about deadlines and enrolling for courses and exams.
Note:
It is mandatory to enrol for all activities of a course that you are going to follow.
Your enrolment is only complete when you submit your course planning in the ‘Ready for enrolment’ tab by clicking ‘Send’.
Not being enrolled for an exam/resit means that you are not allowed to participate in the exam/resit.
Contact
For all your questions you can contact info@sbb.leidenuniv.nl
Note: If you are an ICTiBPS student, you can contact the programme coordinator of ICTiBPS for any questions about your program.
Remarks
There is only limited capacity for external students, please contact the programme co-ordinator to discuss.
Students are responsible for enrolling/unenrolling themselves for (partial) exams/retakes.
Students who do not enroll themselves for an exam/retake by the deadline are not allowed to take the exam/retake.
Students fail the course if any of the partial components (except the exam) that make up the final mark of the course is assessed below 4.0.
Students fail the course if the grade for the (final) exam is assessed below 5.0.
The final grade is expressed as a whole or half number between 1.0 and 10.0, including both limits. The result is not to be expressed as a number between 5.0 and 6.0.
If one of the components of the final mark constitutes a component that assesses attendance or class participation, students cannot take a retake for this component. Therefore, students fail the course if their mark for this component is less than 4.0.
Partial grades, inclusive the exam grade will not be rounded. If partial grades will be communicated, it is possible partial grades are rounded, but unrounded partial grades will be used in the calculation of the final grade. The final grade will be rounded at 0.5 (5.49 will rounded down to a 5 and a 5.5 will be rounded up to a 6.0).
Students pass the course if the final grade is 6.0 or higher (5.49 will rounded down to a 5 and a 5.5 will be rounded up to a 6.0).
It is not possible to do retakes for group assignments. Therefore, if students fail the group assignment component, they fail the course.
As class participation is an assessment component, students must notify the program coordinator about any absence via email (info@sbb.leidenuniv.nl) BEFORE the lecture, describing a legitimate reason for missing the lecture. If the student does not notify the program coordinator before the lecture, the student will be penalised. Students may be required to provide further documentation to substantiate their case, and class attendance requirements are only waived under exceptional circumstances such as illness.
Students who are entitled to more exam/retake time must report to info@sbb.leidenuniv.nl 10 days before the exam/retake takes place.
Software
Starting from the 2024/2025 academic year, the Faculty of Science will use the software distribution platform Academic Software. Through this platform, you can access the software needed for specific courses in your studies. For some software, your laptop must meet certain system requirements, which will be specified with the software. It is important to install the software before the start of the course. More information about the laptop requirements can be found on the student website.