📊 Data Science & Analytics

Marketing Analytics

Marketing Analytics is a comprehensive, skills-first course that teaches how to collect, process, analyze, and act on ma...

Sections

1. 1. Introduction to Marketing Analytics
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Foundational concepts, role of analytics in marketing, types of marketing decisions, and key metrics.

10 topics (10 versions)

1.1What is Marketing Analytics?

1.2Key Marketing Metrics and KPIs

1.3Analytics vs. Intuition in Marketing

1.4Types of Marketing Analytics: Descriptive to Prescriptive

1.5Common Use Cases and Business Questions

1.6Stakeholders and Cross‑Functional Roles

1.7Data-Driven Marketing Workflow Overview

1.8Tools and Technology Landscape

1.9Measuring ROI and Business Impact

1.10Learning Path and Project Roadmap

2. 2. Data Collection & Tracking
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Designing tracking plans, instrumentation for web, mobile and offline channels, and data quality practices.

10 topics (10 versions)

2.1Defining Events and Properties

2.2Tracking Plan Design and Governance

2.3Web Analytics Tagging (UTM, pixels, GTM)

2.4Mobile and App Event Tracking

2.5Server-Side and Data Layer Strategies

2.6CRM and Offline Integration

2.7Third-Party Data Sources and APIs

2.8Data Quality, Validation and Monitoring

2.9Consent Management and Tagging

2.10Data Logging and Event Sampling Considerations

3. 3. Data Management & Engineering
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Storing, cleaning, and preparing marketing data for analysis, including ETL/ELT processes and schema design.

10 topics (10 versions)

3.1Data Ingestion Strategies

3.2Data Modeling for Marketing (Events, Users, Sessions)

3.3ETL vs ELT Patterns

3.4Building a Marketing Data Warehouse

3.5Data Cleaning and Transformation

3.6Schema Design and Naming Conventions

3.7Handling Identity: Cookies, IDs, and Identity Graphs

3.8Time-Series and Windowing for Marketing Data

3.9Scaling and Partitioning Strategies

3.10Data Catalogs and Lineage

4. 4. Exploratory Data Analysis & Visualization
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Techniques for summarizing, visualizing, and interpreting marketing datasets to generate insights and hypotheses.

10 topics (10 versions)

4.1Exploratory Data Analysis (EDA) Principles

4.2Cleaning and Preparing Data for EDA

4.3Univariate and Bivariate Analysis

4.4Cohort Analysis

4.5RFM Analysis Basics

4.6Time Series Visualization and Decomposition

4.7Funnel and Conversion Analysis

4.8Choosing Visualizations for Marketing Data

4.9Using Python/R and SQL for EDA

4.10Storytelling with Data and Insight Framing

5. 5. Digital Analytics: Web, Social & Mobile
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Measuring digital channel performance, understanding user journeys, and analyzing channel attribution for online marketing.

10 topics (10 versions)

5.1Web Traffic Metrics and Sessionization

5.2Behavioral Analytics (Clicks, Views, Scrolls)

5.3Social Media Metrics and Listening

5.4Mobile Engagement and Retention Metrics

5.5Acquisition Channel Analysis

5.6User Journey and Path Analysis

5.7Event-Based vs Page-Based Analytics

5.8Cross-Device Measurement Challenges

5.9Benchmarking and Channel Mix

5.10Tag Management and Analytics Platforms

6. 6. Customer Analytics & Segmentation
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Understanding customer behavior through segmentation, lifetime value, churn analysis, and lifecycle modeling.

10 topics (10 versions)

6.1Customer Lifetime Value (CLV) Fundamentals

6.2Recency, Frequency, Monetary (RFM) Segmentation

6.3Behavioral and Psychographic Segmentation

6.4Churn Detection and Retention Metrics

6.5Propensity Modeling Basics

6.6Customer Journey Stages and Mapping

6.7Value-Based Segmentation for Targeting

6.8Lookalike and Audience Modeling

6.9Segmentation Maintenance and Automation

6.10Measuring Segment Lift and Performance

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Marketing Analytics

Sections

1. 1. Introduction to Marketing Analytics0 views

2. 2. Data Collection & Tracking0 views

3. 3. Data Management & Engineering0 views

4. 4. Exploratory Data Analysis & Visualization0 views

5. 5. Digital Analytics: Web, Social & Mobile0 views

6. 6. Customer Analytics & Segmentation0 views

Sign in to track your progress

1. 1. Introduction to Marketing Analytics
0 views

2. 2. Data Collection & Tracking
0 views

3. 3. Data Management & Engineering
0 views

4. 4. Exploratory Data Analysis & Visualization
0 views

5. 5. Digital Analytics: Web, Social & Mobile
0 views

6. 6. Customer Analytics & Segmentation
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