Data-Driven Marketing (5 cr)

Code: MAR002AS2AE-3008

Basic information of implementation


Enrollment
02.01.2025 - 10.01.2025
Enrolment for the implementation has ended.
Timing
13.01.2025 - 14.03.2025
Implementation has ended.
ECTS Credits
5 cr
Campus
Pasila Campus
Teaching languages
English
Seats
30 - 100
Degree programmes
INTBBA International Business
Teachers
Maria Vickholm
Groups
IBE5PAMAR
INTBBA, 5. semester, Pasila, Marketing and Sales
CAMPUSONLINE
CAMPUSONLINE
VIRTUAL
Virtual implementation
INSTRUCTED
Instructed virtual implementation
EXCH
EXCH Exchange students
Course
MAR002AS2AE

Evaluation scale

H-5

Schedule

Will be defined later

Implementation methods, demonstration and Work&Study

Contact, blended, online

Demonstration (RPL): If you already have command of the course contents, you can demonstrate your competence. Ask the course teacher for more information. For more information on Recognition of Prior Learning: https://www.haaga-helia.fi/en/recognition-learning
Some of the self-directed learning that is part of the course takes place in third-party services according to the student’s own choice. The student is responsible for registering as a user of these services.

Intro

In this course, you will learn the fundamentals of modern and effective marketing through the study of the central concepts, practices and systems. You will gain an understanding of the possibilities of data-driven marketing in different channels and you will be able to plan targeted marketing that supports business objectives. You will learn how to make use of various metrics and their importance in agile marketing.

Materials

Chaffey, Dave & Ellis-Chadwick, Fiona, 2022. Digital Marketing 8th Edition.
Available as e-book in Haaga-Helia library.

Driscoll Miller, J, Lim, J. & Meerman Scott, D. 2020. Data-First Marketing : How to Compete and Win in the Age of Analytics. John Wiley & Sons, Incorporated.
Available as e-book in Haaga-Helia library.

Haimowitz, I.J., Verhoef, P.C., Kooge, E., Walk, N. & Wiering, N. 2022. Data analytics for business : lessons for sales, marketing, and strategy. Routledge. Second edition.

Järvinen, J. & Karjaluoto, H. (2015). The use of web analytics for digital marketing performance measurement. Industrial Marketing Management, Vol. 50, pp. 117-127.

Teaching methods and instruction

This is a virtual implementation. Students go through the course material and complete the assignments at their own pace and no lectures are offered with mandatory attendance.

Working life connections

Material and assignments from and for real case organizations.

Exam dates and re-exam possibilities

No exam, only assignments.

Internationality

All material, examples and assignments are created for international students and from a global perspective.

Completion alternatives

Work & Study or RPL

If you feel that you have already attained the competence level required for this course, such as through previous work experience, you can get the credits through Recognition of Prior Learning (RPL). For more information on either Work & Study or RPL, contact the responsible teacher.

Learning assignments

Aiming for grades 1-2 (individual work)

- Review of the material and related multiple-choice review (max. 50 points, to be taken at the end of the course)
- Self-reflection exercise (max. 10 points, to be completed at the end of the course)

Aiming for grade 3 (to be done individually)

- Review of the material and related multiple-choice review (max. 50 points, to be taken at the end of the course)
- Self-reflection exercise (max. 10 points, to be completed at the end of the course)
- Google Fundamentals of Digital Marketing certification (max. 10 points)

Aiming for grades 4-5 (to be done individually and in groups)

Individual work:
- Review of online material and related multiple-choice review (max. 50 points, to be completed at the end of the course)
- Self-reflection exercise (max 10 points, to be completed at the end of the course)
- Google Fundamentals of Digital Marketing certification (max. 10 points)

Group work:

- Data-driven marketing analysis of a case study (max. 30 points)

Assessment methods

Grading scale

90 - 100 points = 5
71 - 89 points = 4
61 - 70 points = 3
51 - 60 points = 2
40 - 50 points = 1

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