Marketing Analyst Course

Lesson 1 • Analytical Thinking for Marketers

Trains structured problem decomposition and hypothesis-driven thinking. Grounds all future analyses in a repeatable reasoning framework.

Lesson 2 • Marketing Data Ecosystem Overview

Maps the landscape of data sources marketers rely on, from CRM to ad platforms. Connects data origins to analytical decisions made throughout the course.

Lesson 3 • Core Marketing Metrics Defined

Introduces essential KPIs such as CAC, LTV, ROAS, and conversion rate. Provides a shared vocabulary used in every subsequent chapter.

Lesson 1 • Building and Managing a Data Pipeline

Introduces ETL concepts and basic pipeline architecture for marketing data flows. Prepares students to work with data engineers and maintain data freshness.

Lesson 2 • Data Cleaning and Preparation

Teaches deduplication, outlier handling, and missing-value treatment for marketing datasets. Ensures data integrity before any metric calculation or modeling.

Lesson 3 • Data Privacy and Compliance Principles

Reviews consent frameworks, data minimization, and user rights relevant to marketing data. Ensures analysts operate within ethical and regulatory boundaries.

Lesson 4 • Tracking and Tagging Fundamentals

Explains how pixels, tags, and event tracking capture user behavior across channels. Directly enables accurate data collection for all downstream analyses.

Lesson 1 • Building Marketing Dashboards

Guides the design of live dashboards that track KPIs across channels. Connects metric definitions from Chapter 1 to actionable visual displays.

Lesson 2 • Data Visualization Principles

Teaches chart selection, color theory, and layout for marketing audiences. Ensures visuals communicate insights rather than obscure them.

Lesson 3 • Exploratory Data Analysis Techniques

Applies summary statistics and distribution analysis to marketing datasets. Builds the habit of understanding data shape before drawing conclusions.

Lesson 1 • Paid Search and Display Analytics

Covers Quality Score, impression share, CPC, and ROAS for paid media campaigns. Enables data-driven budget allocation and bid strategy recommendations.

Lesson 2 • Web Analytics Deep Dive

Examines sessions, bounce rate, funnel drop-off, and on-site behavior metrics. Provides the analytical foundation for website optimization decisions.

Lesson 3 • Email and CRM Analytics

Analyzes open rate, click-to-open rate, deliverability, and list health for email programs. Connects email performance to revenue and customer lifecycle stages.

Lesson 4 • Social Media Analytics

Measures reach, engagement rate, share of voice, and paid social efficiency. Links social metrics to brand and conversion outcomes.

Lesson 1 • Hypothesis Testing Essentials

Teaches t-tests, chi-square tests, and z-tests for comparing marketing groups. Enables statistically sound conclusions from campaign and segment comparisons.

Lesson 2 • Segmentation with Clustering Methods

Uses k-means and hierarchical clustering to identify distinct customer segments. Translates statistical groupings into actionable marketing personas.

Lesson 3 • Regression Analysis in Marketing

Applies simple and multiple linear regression to forecast metrics and identify drivers. Connects statistical modeling to actionable marketing recommendations.

Lesson 4 • A/B and Multivariate Testing

Designs and analyzes controlled experiments for ads, landing pages, and emails. Applies hypothesis testing skills to real marketing optimization scenarios.

Lesson 1 • Unified Measurement Strategy

Combines attribution, incrementality, and MMM into a coherent measurement framework. Prepares students to advise on measurement architecture for complex organizations.

Lesson 2 • Marketing Mix Modeling Basics

Introduces regression-based MMM to quantify channel contribution at aggregate level. Complements digital attribution with an offline and long-term view.

Lesson 3 • Attribution Model Fundamentals

Compares last-click, first-click, linear, time-decay, and position-based models. Establishes the trade-offs each model introduces for budget decisions.

Lesson 4 • Incrementality and Lift Testing

Teaches holdout tests and geo-lift experiments to measure true incremental impact. Separates organic conversions from marketing-driven ones.

Lesson 1 • RFM Analysis and Customer Scoring

Applies recency, frequency, and monetary scoring to prioritize customer segments. Provides a practical, low-complexity framework for CRM-driven marketing.

Lesson 2 • Churn Prediction and Prevention

Identifies at-risk customers using behavioral signals and predictive scoring models. Connects churn reduction to LTV improvement and retention ROI.

Lesson 3 • Cohort Analysis Techniques

Groups customers by acquisition period to track retention and revenue over time. Reveals product-market fit signals and campaign quality differences.

Lesson 4 • Customer Lifetime Value Modeling

Builds historical and predictive LTV models using purchase frequency and margin data. Enables ROI-based decisions on acquisition spend and retention investment.

Lesson 1 • Building the Analytics Business Case

Structures ROI arguments for analytics investments, tools, and team expansion. Equips analysts to advocate for data-driven culture within organizations.

Lesson 2 • Competitive and Market Analysis

Synthesizes share-of-voice, benchmarking, and market sizing data for strategic context. Positions the brand's performance relative to market dynamics.

Lesson 3 • Forecasting Marketing Performance

Applies time-series methods and regression forecasting to project future KPIs. Enables proactive planning and early identification of performance risks.

Lesson 4 • Capstone: End-to-End Analytics Project

Integrates all prior skills into a full analytics engagement from data to recommendation. Simulates real-world analyst deliverables for portfolio and interview readiness.