
An executive overview of how AI is reshaping modern marketing decision-making
How raw marketing data is converted into actionable business insights
A real-world case study diagnosing declining ROAS and its root causes
Strategic levers and data-backed optimizations to improve marketing performance
Translating strategy into execution using a structured analytics approach
A step-by-step framework to solve marketing problems using data and AI
Learn how to quickly summarize, analyze, and explore large datasets using pivot tables
Understand how to add interactive filters to pivot tables for easy and dynamic data exploration
Learn to create custom calculations within pivot tables to derive new insights from existing data
Business impact, results achieved, and key learnings from the implementation
Understanding how marketing actions drive outcomes through causal analysis
Essential analytics concepts required for decision-making
Overview of data analysis toolpak used for marketing analytics and modeling
Applying correlation and regression concepts using a real sales example
Hands-on implementation of regression models for marketing analysis
Interpreting model outputs to drive confident executive decisions
Marketing today is increasingly driven by data, analytics, and AI rather than intuition alone. Professionals across marketing, business, and analytics roles are expected to understand performance metrics, interpret data-driven insights, and make informed decisions that improve outcomes. This course is designed to help learners build that capability in a practical and structured way.
Data-Driven Marketing focuses on how analytics and AI can be used to understand marketing performance, identify problems, and design effective optimization strategies. Instead of teaching tools in isolation, the course emphasizes thinking frameworks, interpretation, and real-world examples that can be applied across industries and roles.
You will learn how marketing data is transformed into insights, how issues such as declining return on ad spend (ROAS) can be analyzed, and how data-backed optimizations are planned and evaluated. The course introduces key concepts such as cause-and-effect thinking, correlation, and regression in a clear, business-friendly manner, helping you understand why performance changes and how to respond.
Through step-by-step explanations and hands-on examples, you will see how analytics supports marketing decisions from insight generation to implementation and outcomes. You will also learn how to interpret model outputs, evaluate results, and communicate findings clearly to stakeholders.
This course is suitable for marketing professionals, business managers, consultants, MBA students, and analytics learners who want to strengthen their understanding of data-driven marketing. No advanced technical or coding background is required.
By the end of the course, you will have a solid foundation in using data, analytics, and AI to make smarter marketing decisions.