Digital data in marketing

Course title
Digital data in marketing
Course tag
10404
Semester
1
Course status
Mandatory
ECTS
5
Lectures
30
Practice
30
Independent work
90
Total
150
Teachers and associates
Assistant Professor PhD Goran Klepac
The course aims
The objective of the course is to develop students' awareness about the approach to analysis, structuring, recording, use and business interpretation of digital data from various sources for business and marketing purposes together with the acceptance of changes occurring in technology and society, especially in communications and communicating. The importance of this approach is based on the evident ongoing shift in market paradigm through globalization, new technologies and positions of all participants in the market. The premises of the course aim to explain students why and how they can manage digital data in marketing, how to monitor customer journey, how the ways of accessing data changed over time (and are still changing) and how to develop marketing message relevance based on data. In addition to practical concepts, students are introduced to modern tools and sources of data and knowledge. Students will be able to develop conceptual models for prospective and retrospective customer value, conceptual BSC model, , conceptual churn model.
Content
The course includes topics/lectures that correspond to two-hour sessions. At least one session is reserved for a guest lecture that will be incorporated within the final section of lectures considering the availability of lecturers.
Literature:
1. Data-Driven Marketing the 15 metrics everyone in Marketing should know - Mark Jeffry, Wiley
Supplementary literature
1. Raskino, Waller (Gartner) „Digital to the core“
2. Seybold „The Customer Revolution“
3. Brown, Tim „Change by Design“
4. Hsieh, Tony „Delivering Happyness“
5. Klepac, Kopal, Mršić „Developing Churn Models Using Data Mining Techniques and Social Network Analysis“
6. Lindstrom „Buyology“
7. Baker, Stephen „Numerati“

Minimum learning outcomes

  1. Understand potentials of internal and external digital sources and their shaping with purpose of creating conceptual solutions for customer lifecycle.
  2. Creating conceptual solution for prospective customer value, retrospective customer value.
  3. Develop a simple structured digital questionnaire and describe ways to store data from questionnaires for selected industry / purpose like churn.
  4. Understand test drive concept

Preferred learning outcomes

  1. Identify internal and external sources of digital data about customers, industry or population in general for specific business purpose, and their conceptual shaping for extraction information about customers.
  2. Thoroughly understand concepts of creating conceptual solution for prospective customer value, retrospective customer value which include design of behavioural variables from disposable data.
  3. Develop detailed questionnaire for specific marketing activity, explain the structure of questionnaire appropriate for online mobile users and prepare analysis by combining internal and external data sources.
  4. Advanced use and structuring of test drive concept.