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Regular version of the site
Master 2019/2020

Big Data Based Marketing Analytics

Category 'Best Course for Career Development'
Category 'Best Course for Broadening Horizons and Diversity of Knowledge and Skills'
Type: Elective course (Big Data Systems)
Area of studies: Business Informatics
Delivered by: Department of Innovation and Business in Information Technologies
When: 2 year, 1, 2 module
Mode of studies: offline
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
  • non-blocking Final test
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