• A
  • A
  • A
  • АБB
  • АБB
  • АБB
  • А
  • А
  • А
  • А
  • А
Обычная версия сайта
Магистратура 2019/2020

Маркетинговая аналитика. Продвинутый курс

Лучший по критерию «Полезность курса для расширения кругозора и разностороннего развития»
Лучший по критерию «Новизна полученных знаний»
Статус: Курс обязательный (Маркетинг)
Направление: 38.04.02. Менеджмент
Когда читается: 2-й курс, 1 модуль
Формат изучения: без онлайн-курса
Прогр. обучения: Маркетинг
Язык: английский
Кредиты: 6

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

Learning Objectives

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

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

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

Assessment Elements

  • non-blocking In-class assignment
  • non-blocking Homework
  • non-blocking In-class assignment
  • non-blocking Homework
Interim Assessment

Interim Assessment

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

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.