Credits: 6
Schedule: 16.04.2019 - 23.05.2019
Teacher in charge (valid 01.08.2018-31.07.2020):
Ashish Kumar
Teaching Period (valid 01.08.2018-31.07.2020):
not lectured 2018–19
not lectured 2019–20
Learning Outcomes (valid 01.08.2018-31.07.2020):
Online marketing landscape is complex than ever. The holy grail of marketing problem, “delivering the right message to the right audience at the right time” promised by digital channels soon turned out to be a distant dream for marketers. Digital environment even though provides unparalleled and unlimited data on various aspects of consumer behavior; it fails to live up to the expectation of marketers due to its increased complexity. The objective of this course is to understand the complexity of this digital environment through the lenses of data analytics and unravel the true underlying consumer and firm behavior.
The course will help students understand four steps of data-driven marketing decision process: data collection, quantitative analysis, experiments, and managerial intuition. The first step will shed light on identification for right data and analytic technique for a given online marketing problem. The second step outlines how to conduct analysis and obtain insights from it. The third step will highlight the steps involved in what-if analysis, counterfactuals, simulations, and optimal solutions. And finally the core idea of the fourth step to connect insights from all these three steps into strategic decision-making.
At the end of the course, students will learn the real value of digital marketing analytics by carefully integrating quantitative analysis with managerially important digital marketing problems. During the process, the students will gain expertise in various tools, techniques, models, and experimental designs.
Content (valid 01.08.2018-31.07.2020):
The contents of this course will consist of two parts. First, the conceptual and foundational concepts of the digital marketing environment that will include capturing value in an online marketing environment by understanding consumer and firm behavior. Second, the course will focus on data science that will cover topics such as from big data to better data, marketing performance measurement, analysis of unstructured marketing data, and tools for data analytics.
Assessment Methods and Criteria (valid 01.08.2018-31.07.2020):
Assessment method for the course will be based on compulsory assignments and course project that will be based on group works.
Workload (valid 01.08.2018-31.07.2020):
6 credits, 160 hours:
Lectures and Group Works.
(Please check the syllabus for details on course workload)
Study Material (valid 01.08.2018-31.07.2020):
Reading materials and teaching tools used in the course.
Substitutes for Courses (valid 01.08.2018-31.07.2020):
Course Digital Marketing Management, 23E01000 replaces the course 23E47050 Online Marketing Engineering in the academic year 2018-19. During academic year 2019-20 course can be replaced by one of the following courses: 23E10000 Service Business Strategy, 21E00052 Data-Driven Business, 37E01600 Data Resources Management, 30E03000 Data Science for Business I.
Course Homepage (valid 01.08.2018-31.07.2020):
https://mycourses.aalto.fi/course/search.php?search=23E47050
Registration for Courses (valid 01.08.2018-31.07.2020):
Registration via WedOodi. Check registration time in WebOodi.
Further Information (valid 01.08.2018-31.07.2020):
The number of students admitted to the course is restricted to 60. Priority is given to (1) Aalto students studying in MSc Program of Marketing, (2) Aalto students studying in MSc Program of Global Management with focus area in Marketing, (3) Aalto students studying a MSc minor study package in Marketing, and (4) other students.