•   Data-Driven Marketing MAR002AS2AE-3003 23.10.2023-15.12.2023  5   (DBE3PCDBI, ...) +-
    Learning objectives
    After completing this course, the student:
    - can explain the central concepts, practices and systems in data-driven marketing.
    - can describe how visitor data drawn from digital channels (home pages, search engines and social media channels) can be analyzed and used for customer insights and decision making in marketing.
    - can plan personalized marketing based on collected data as well as set objectives and metrics.
    - will complete a certification in data-driven marketing.
    - is able to take into account ethics, sustainability and responsibility in the handling of data.
    Starting level and linkage with other courses
    Starting level: Customer Insights and Marketing as well as Customer Experience and Sales should be completed beforehand. This course is part of the Marketing and Communication specialization learning path for the Bachelor's Degree in Business.
    Contents
    - The importance and use of data in the development of marketing, including marketing research
    - How the use of data drives marketing nowadays
    - Artificial Intelligence, automation and robotics as part of marketing
    - The fundamentals of data-driven marketing
    Assessment criteria
    Assessment criteria - grade 1
    The student can define the basic concepts and tools used in data-driven marketing. With assistance, the student can find the necessary information and analyze data as the starting point in marketing.
    Assessment criteria - grade 3
    The student can define the tools used in data-driven marketing as well as interpret the collected data. The student can find the necessary information and both analyze and make use of data as the starting point in marketing. The student understands the importance of measuring data and tracking for both customer insights and marketing.
    Assessment criteria - grade 5
    The student can define data-driven marketing and its special features with mastery. The student is able to competently find essential information, and s/he can independently analyze and make use of data in marketing. S/he can select the appropriate metrics and make suggestions for improvement. The student can professionally communicate solutions.
    Teaching methods and instruction

    This is a contact implementation. Sessions at Porvoo Campus every Tue and Thu.

    Learning material and recommended literature

    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.

    Working life connections

    Material and assignments from and for real case organizations. Visiting lecturers from companies.

    Campus

    Porvoo Campus

    Exam dates and re-exam possibilities

    No exam, only assignments.

    Teaching language

    English

    Internationality

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

    Timing

    23.10.2023 - 15.12.2023

    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 grades 3-5 (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) Group work: - Designing a data-driven digital campaign (max 20 points) - Data-driven marketing analysis of a case study (max. 20 points)

    Enrollment

    12.06.2023 - 20.10.2023

    Content scheduling

    For everybody (if only individual, grades 1-2)
    Multiple-choice review, open 27.11-10.12.
    Reflection on own learning (and peer feedback), DL 12.12.

    Group assignments (grades 3-5)
    Team agreement, DL 27.10.
    Digital marketing campaign, DL 28.11.
    Case-organization interview, DL 8.12.

    Groups
    • DBE3PCDBI
    • CONTACT
    • EXCH
    Alternative learning methods

    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.

    Teachers

    Maria Vickholm

    Seats

    15 - 50

    Further information

    Grading scale

    85 - 100 points = 5
    71 - 84 points = 4
    61 - 70 points = 3
    51 - 60 points = 2
    40 - 50 points = 1

    Degree Programme

    DIGIBBA Digital Business Innovations

    R&D proportion

    0.00 cr

    Virtual proportion

    0.00 cr

    Evaluation scale

    H-5