Master 2019/2020

Advanced Marketing Analytics

Category 'Best Course for Career Development'

Category 'Best Course for Broadening Horizons and Diversity of Knowledge and Skills'

Category 'Best Course for New Knowledge and Skills'

Type: Elective course (Global Business)

Area of studies: Management

Delivered by: Faculty of Management (Nizhny Novgorod)

Where: Faculty of Management (Nizhny Novgorod)

When: 2 year, 1 module

Mode of studies: offline

Instructors: Sergey Alexandrovskiy, Denis A. Fomenkov

Master’s programme: Global Business

Language: English

ECTS credits: 6

Contact hours: 40

Course Syllabus

Abstract

The course helps students to learn marketing analytics job requirements, set and decompose analytic goals, select and apply data collection and analysis methods and tools, prepare a report and explain (present) results.

Learning Objectives

• Find out how to apply advanced tools of analytics to make data-informed marketing decisions.

Expected Learning Outcomes

• Know job requirements. Set and decompose analytic goals and metrics.
• Select and apply data collection, preparation and analysis methods and tools
• Prepare a report and explain (present) results

Course Contents

• Marketing analytics jobs and goals
  Job requirements. How to set and decompose analytic goals. Metrics.
• Data collection, preparation and analysis
  How to select and apply data collection and analysis methods and tools. Methods: Comparison of means and A/B tests, factor analysis, cluster and RFM analysis, forecasting with regression and classification, ANOVA, chi-square, hypothesis testing, statistical significance and p-value, cohort analysis. Tools: Spreadsheets, SQL in BigQuery, R (Rstudio), Python, CRM and databases.
• Report and presentation of results
  How to prepare a report and explain (present) results. Reports and dashboards. Visualisation. Presentation.

Assessment Elements

• In-class assignment
• In-class assignment
• In-class assignment
• Homework

Interim Assessment

• Interim assessment (1 module)
  0.25 * Homework + 0.25 * In-class assignment + 0.25 * In-class assignment + 0.25 * In-class assignment

Bibliography

Recommended Core Bibliography

• Phillips, Tim. Data-Driven Business: Use Real-Life Numbers to Improve Your Business by 352% [Электронный ресурс] / Tim Phillips; БД books24х7. – Infinite Ideas, 2016. – 160 pages. – ISBN 978-1908984609. –Режим доступа: http://common.books24x7.com/toc.aspx?bookid=130361. – Загл. с экрана.

Recommended Additional Bibliography

• Foreman, John W. Data Smart: Using Data Science to Transform Information into Insight [Электронный ресурс] / John W. Foreman; БД books24х7. – John Wiley & Sons, 2014. – 432 pages. – ISBN 978-1-118-03496-5. – Режим доступа: http://common.books24x7.com/toc.aspx?bookid=58144. – Загл. с экрана.Foreman, John W. Data Smart: Using Data Science to Transform Information into Insight [Электронный ресурс] / John W. Foreman; БД books24х7. – John Wiley & Sons, 2014. – 432 pages. – ISBN 978-1-118-03496-5. – Режим доступа: http://common.books24x7.com/toc.aspx?bookid=58144. – Загл. с экрана.
• Jeffery, M. Data-Driven Marketing: The 15 Metrics Everyone in Marketing Should Know [Электронный ресурс] / Mark Jeffery; БД ebrary. – John Wiley & Sons, Incorporated, 2010. – 323 p. – ISBN 9780470504543. – Режим доступа: https://ebookcentral.proquest.com/lib/hselibrary-ebooks/reader.action?docID=485632&query=Data-Driven+Marketing. – Загл. с экрана.