Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.


You are confident in utilising numerical data to support
marketing decisions and have the basic skills for collecting
and analysing such data.
After completing the course you will be able to:
• Collect and analyse diverse types of market data,
• Produce simple analytical reports,
• Critically evaluate market reports produced by external
• Utilize simple data analysis and market reports effectively to
support marketing decisions.

Credits: 6

Schedule: 23.04.2024 - 03.06.2024

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Antti Abel Vassinen

Contact information for the course (applies in this implementation):

Professor of Practice Antti Vassinen:

Teaching assistant Joonas Määttä: (primary contact)

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English


  • valid for whole curriculum period:

    To address the increasing demand from employers for
    marketing professionals who are at ease with analysing (big)
    market data, this course provides students with basic tools of
    statistical analysis to support marketing decision making. The
    course covers different sources and forms of market data and
    provides practical tools for making simple analyses from such
    data. Practical exercises using SPSS and Microsoft Excel
    provide students with a chance to practice making relevant
    calculations in the context of marketing decisions, and business
    cases solved in class provide experience in solving real life
    business problems using market data. The course consists of
    lectures, practical exercises, cases, and home assignments
    (both individual and group assignments).

  • applies in this implementation

    Marketing professionals are increasingly required to be comfortable working with and analyzing large amounts of data. Companies have access to vast amounts of first party and third party data, and the ability to analyse this data effectively and reliably is increasingly important for marketing decision-making. 

    Driving growth and profitability requires a deep understanding of customer behavior, preferences, and needs, as well as the ability to measure the effectiveness and efficiency of marketing campaigns and make data-driven decisions. This course provides students with the fundamental tools and techniques for analyzing marketing data and using it to make informed marketing decisions.

    In addition to technical skills, this course also emphasizes the importance of practical application and problem-solving in a business context. Students will learn to approach marketing problems with a structured, data-driven approach, and to develop credible recommendations based on sound analysis. The applied parts of the course employ company data from mobile gaming, food, market research, and delivery services industries.

    Microsoft Excel is used for instruction. SPSS is demonstrated, and students are welcome to use it, R, Python or negotiable other tools if they so choose.

Assessment Methods and Criteria
  • valid for whole curriculum period:

    • Written exam • Group presentation • Cases • Individual assignments In order to pass the course, the student must pass at least 50 % of the exam.

  • applies in this implementation

    Individual exercises (30)

    Pair exercise (20)

    Exam (50)

    Feedback (bonus - 2)

    Students must achieve a pass (50%) on all required components.

  • valid for whole curriculum period:

    The course consists of lectures, practical inclass
    assignments, and home assignments.

  • applies in this implementation

    Activity h
    Lectures and work sessions20
    Individual exercises
    Pair exercise25
    Final exam inc. preparation25


Study Material
  • valid for whole curriculum period:

    Materials distributed in class.

    Naresh K. Malhotra: Marketing Research - An
    Applied Orientation, 7th edition, Pearson.

  • applies in this implementation

    No textbook. A list of required and suggested readings will be provided to students at the start of the course.

Substitutes for Courses
SDG: Sustainable Development Goals

    10 Reduced Inequality

    16 Peace and Justice Strong Institutions


Further Information
  • valid for whole curriculum period:

    Teaching Language : English

    Teaching Period : 2022-2023 Spring V
    2023-2024 Spring V


    The number of students admitted to the course is restricted to

    Priority is given to (1) Aalto BSc Marketing students , (2)
    Aalto MSc Marketing students, (3) Aalto MSc students in Business Analytics (4) Aalto BIZ exchange students, (5) other BIZ students.

  • applies in this implementation

    Lecture topics and exercises include:

    • Excel as a tool for data analysis in marketing
    • Summarising key features of market data
    • Visualising marketing data
    • A/B tests and experiments in marketing
    • Calculating ROI on marketing campaigns
    • Customer analytics (e.g. churn, LTV)
    • Creating managerial recommendations based on data analysis

Details on the schedule
  • applies in this implementation

    There are six lectures on Tuesday afternoons, starting April 23rd. They run from 15:15 to 17:00 (EET).

    Lecture recordings will be available the same week for some sessions/parts, but not guaranteed for all content (e.g. company guests). Live attendance is not mandatory, but is strongly recommended. An exception is the sixth session on May 28th, when attendance impacts your score.

    Each Tuesday's lecture content is followed on Thursday by a virtual exercise session in small groups. These are an opportunity for you to work on the exercises in study groups and receive help from the instructor/assistant. These sessions are not recorded for privacy reasons.

    There are no face-to-face sessions. Teaching is exclusively over Microsoft Teams. If you wish to sit with other students, you are welcome to use hall U8 - U270 at Kandidaattikeskus. 

    The individual assignments are given on lectures 2, 3, and 4 and are due for the following week's lecture. The pair assignment is given on lecture 5 and due for the final lecture, when randomly selected pairs will present their solutions.

    Changes to the planned order and content of lectures and exercises are possible.