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Regular version of the site
Master 2020/2021

Big Data Based Marketing Analytics

Type: Elective course (Big Data Systems)
Area of studies: Business Informatics
When: 2 year, 1, 2 module
Mode of studies: offline
Open to: students of one campus
Instructors: Vitaly Silchev
Master’s programme: Big Data Systems
Language: English
ECTS credits: 6

Course Syllabus

Abstract

The course Big Data Based Marketing Analytics provides an overview of modern technologies and approaches to marketing analytics with extensive usage of tools, designed for analysis and processing of extremely large and complex datasets.
Learning Objectives

Learning Objectives

  • to explain how to structure and organize modern marketing analysis workflow
  • to give an overview of existing marketing analytical frameworks and solutions
Expected Learning Outcomes

Expected Learning Outcomes

  • give a definition of marketing process
  • estimate the brand value of a particular company or product
  • calculate CLV (Customer Lifetime Value)
  • perform statistically significant A/B tests
  • choose appropriate design for marketing experiments
  • develop a recommendation system based on collected data
  • select appropriate SMM metrics for different media types
Course Contents

Course Contents

  • Marketing analytics in context of marketing process
    A brief introduction
  • Basic Elements of Marketing
    Topics: Brand Management, Sales Funnel, Customer Lifetime Value
  • Marketing Campaign Analysis
    We discuss how to compare marketing campaigns correctly.
  • Personalized marketing
  • Digital Marketing Analytics
Assessment Elements

Assessment Elements

  • non-blocking Mid-term test
  • non-blocking Programming Assignment: Building a Recommender System
    Students may work on this assignment individually or in small teams (up to 3 people)
  • non-blocking Final test.
    The examination shall be held in a form of a test hosted on StartExam platform (https://app.startexam.com/SignIn) in a syncronous mode without proctoring. Students need to connect to the exam session 10 minutes before the start of the examination. A short-term breakdown in internet connection is defined as a loss of connection lasting for 5 minutes. A long-term breakdown in internet connection during the examination is defined as a loss of the internet connection lasting for more than 5 minutes. Should a student experience a long-term loss of connection, he/she may not continue his/her participation in the examination. The procedure for retakes shall follow the procedure for the initial examination.
Interim Assessment

Interim Assessment

  • Interim assessment (2 module)
    0.4 * Final test. + 0.3 * Mid-term test + 0.3 * Programming Assignment: Building a Recommender System
Bibliography

Bibliography

Recommended Core Bibliography

  • Charan, A. (2015). Marketing Analytics : A Practitioner’s Guide to Marketing Analytics and Research Methods. Singapore: World Scientific Publishing Company. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1001262

Recommended Additional Bibliography

  • Grigsby, M. (2018). Marketing Analytics : A Practical Guide to Improving Consumer Insights Using Data Techniques (Vol. Second edition). London: Kogan Page. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1738744