Advance techniques and tools for Marketing analytics and data insights #255005

Upon successful completion of this course, participants will be able to:

• Architect a holistic marketing data infrastructure, integrating data from CRM, web analytics, paid media, and social platforms into a single source of truth.

• Apply statistical analysis and predictive modeling techniques (e.g., regression, clustering, forecasting) to uncover deep insights and predict future outcomes.

• Design and implement advanced Multi-Touch Attribution (MTA) and Marketing Mix Modeling (MMM) frameworks to accurately quantify channel contribution and optimize budget allocation.

• Master advanced analytics tools, including Google Analytics 4 (GA4), data visualization platforms (Tableau/Power BI), and introductory SQL/R/Python for analysis.

• Develop a robust testing and experimentation program (A/B, multivariate) grounded in statistical rigor.

• Synthesize complex data findings into compelling, actionable narratives for executive stakeholders.

This advanced course is designed for marketing professionals and data specialists who are responsible for analysis, strategy, and performance optimization:

• Marketing Analysts, Data Analysts, and BI Specialists

• Performance Marketing Managers (SEM, Social, Programmatic)

• Marketing Directors, Heads of Growth, and VPs of Marketing

• CRM and Lifecycle Marketing Leaders

• Marketing Operations Managers

• Digital Strategists and Consultants

• Product Marketers using data to drive GTM strategy

Prerequisite: A strong foundational understanding of digital marketing channels and basic analytics (e.g., familiarity with a previous version of Google Analytics) is essential.

• Pre-assessment
• Live group instruction
• Use of real-world examples, case studies and exercises
• Interactive participation and discussion
• Power point presentation, LCD and flip chart
• Group activities and tests
• Each participant receives a binder containing a copy of the presentation
• slides and handouts
• Post-assessment

Day 1: Architecting the Marketing Data Ecosystem

• Morning Session: The Data-Driven Marketing Framework

  • From Silos to Strategy: Building an integrated data infrastructure.

  • Introduction to Customer Data Platforms (CDPs), Data Warehouses (BigQuery, Snowflake), and the Modern Data Stack.

  • The Role of APIs and ETL/ELT Processes.

• Afternoon Session: Deep Dive into Google Analytics 4 (GA4)

  • Advanced Implementation: Custom events, parameters, and user properties.

  • BigQuery Integration: Unlocking raw, unsampled data for analysis.

  • Workshop: Design and implement a custom tracking plan for a complex user journey.

Day 2: Statistical Analysis & Predictive Modeling for Marketers

• Morning Session: Statistical Foundations

  • Moving Beyond Averages: Correlation, Regression Analysis, and Statistical Significance.

  • Cohort Analysis: Measuring customer behavior and lifetime value (LTV) over time.

• Afternoon Session: Introduction to Predictive Analytics

  • Using Python/R for Marketing Analysis (Pandas, ggplot/Matplotlib).

  • Segmentation 2.0: RFM Analysis and K-Means Clustering for advanced customer segmentation.

  • Hands-On Lab: Perform cluster analysis on a customer dataset to identify high-value segments.

Day 3: Attribution, Budget Optimization & Experimentation

• Morning Session: Multi-Touch Attribution (MTA)

  • Beyond Last-Click: Data-Driven Attribution in GA4 and paid media platforms.

  • Building a Custom MTA Model: Understanding the customer journey.

• Afternoon Session: Marketing Mix Modeling (MMM) & Testing

  • Introduction to MMM: Measuring offline and long-term marketing impact.

  • Designing Statistically Sound A/B and Multivariate Tests.

  • Case Study: Analyze MMM output to reallocate a annual marketing budget across channels for maximum ROI.

Day 4: Advanced Tools & Data Visualization

• Morning Session: SQL for Marketers

  • Writing queries to extract, join, and analyze marketing data from databases.

  • Answering complex business questions with data.

• Afternoon Session: Data Storytelling with Visualization Tools

  • Tool Mastery: Building interactive, executive-level dashboards in Tableau or Power BI.

  • The Art of Data Storytelling: Crafting a narrative around insights.

  • Workshop: Connect a data source and build a comprehensive marketing performance dashboard.

Day 5: Synthesis, AI & Capstone Project

• Morning Session: The Future: AI and Machine Learning in Marketing

  • Leveraging AI for Predictive Analytics, Personalization, and Content Optimization.

  • Introduction to churn prediction and propensity modeling.

• Afternoon Session: Capstone Project & Presentation

  • Final Challenge: Participants are given a complex, multi-source dataset and a business problem (e.g., “Why are we seeing rising CAC?”). They must clean the data, perform analysis, build a visualization, and present their data-driven strategy.

  • Presentation & Critique: Present findings to the “C-Suite” (instructors and peers).

  • Course Recap: Building a Data-Driven Culture within Your Organization.

  • Certification.