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Digital Marketing Analytics and Big Data

Collecting, processing and analysing large volumes of data from digital platforms for strategic decisions. Students learn to predict consumer behaviour, segment customers and measure campaign ROI.

University
UNEC
Centre
International Centre for Master’s and Doctoral Studies
Status
Mandatory course
Semester
Spring
Language
English
Volume
60 hours, 24 topics
Explaining an offline experiment
24 topics
60 hours · in English

About the course

The course teaches how to turn complex data into business reports with visualisation tools such as Power BI and Tableau, and how to bring machine learning into marketing strategy. At its centre is a data-driven marketing strategy that creates a competitive advantage.

Tools: Power BI · Google Analytics 4

Teacher
Shamistan Isayev

MSc, PhD candidate. UNEC, International Centre for Master’s and Doctoral Studies. A mandatory course in the master’s programme.

What graduates can do

  • Analytical framework

    Understand the role of Big Data technologies in marketing strategy and apply data-driven decision models in the digital ecosystem.

  • Predicting consumer behaviour

    Use predictive analytics for segmentation, churn analysis and Customer Lifetime Value (CLV).

  • Measuring performance

    Assess the effectiveness of social, search and e-mail channels with modern metrics and attribution models.

  • Technical skills

    Process complex data sets with Python, SQL or GA4 and turn the results into professional reports with visualisation tools.

  • Strategic optimisation

    Prepare proposals to optimise the marketing budget and grow ROI based on Big Data insights.

Programme: 24 topics

One topic a week. For easy reading the topics are grouped into six blocks; week numbers follow the syllabus.

  1. Foundations

    Week 1-4 · 4 topics

    The role of analytics, data-driven decisions and the idea of Big Data.

    • Week 1The nature and role of digital marketing analytics
    • Week 2Data-Driven Decision Making in marketing
    • Week 3Concept of Big Data and its core characteristics
    • Week 4Data types used in digital marketing

  2. Data collection and web analytics

    Week 5-7 · 3 topics

    Collection methods, key metrics and GA4.

    • Week 5Customer data collection methods
    • Week 6Web analytics and key metrics
    • Week 7Application of Google Analytics in marketing

  3. Channel analytics

    Week 8-12 · 5 topics

    Social media, content, advertising, SEO/SEM and e-mail.

    • Week 8Social media analytics and performance measurement
    • Week 9Analytics and KPIs in content marketing
    • Week 10Measurement of digital advertising campaigns
    • Week 11SEO and SEM analytics
    • Week 12Email marketing analytics and effectiveness measurement

  4. Customer analytics

    Week 13-16 · 4 topics

    Segmentation, customer journey, insights and forecasting.

    • Week 13Customer behavior analysis and segmentation
    • Week 14Customer Journey Analytics
    • Week 15Big Data and obtaining customer insights
    • Week 16Predictive analytics and marketing planning

  5. Automation and AI

    Week 17-19 · 3 topics

    Real-time data, automation, AI and ML.

    • Week 17Real-time data and agile marketing decisions
    • Week 18Marketing automation and analytics
    • Week 19The role of AI and Machine Learning in marketing analytics

  6. Reporting, ethics and strategy

    Week 20-24 · 5 topics

    Visualisation, data quality, privacy and strategic decisions.

    • Week 20Visualization and preparation of reports
    • Week 21Problems of data quality and interpretation
    • Week 22Ethical issues and data privacy in digital marketing
    • Week 23Big Data-based personalization strategies
    • Week 24The role of Digital Marketing Analytics and Big Data in strategic decision-making

Assessment

  • Semester project20 points
  • Midterm exam30 points
  • Final exam50 points

Attendance is mandatory: at least 75%.

Literature

Core

  1. Yıldırım, A. (2019). Dijital Pazarlama Analitiği. İstanbul: Beta Yayınları.
  2. Kara, A. & Koç, E. (2021). Veri Odaklı Pazarlama. Ankara: Seçkin Yayıncılık.
  3. Bozkurt, İ. (2022). Büyük Veri ve Dijital Pazarlama. İstanbul: Ekin Yayınevi.

Supplementary

  1. Marr, B. (2016). Big Data in Practice. Wiley.
  2. Odabaşı, Y. (2020). Dijital Pazarlama ve Sosyal Medya Yönetimi. İstanbul: MediaCat Yayınları.
  3. Clifton, B. (2012). Advanced Web Metrics with Google Analytics. Wiley.

A guest lecture or programme partnership

I prepare lectures and master classes on these topics for universities and education programmes.

Get in touch