Advanced Tools for Digital Marketing Analytics Course

Lesson 1 • Data Collection Methods and Sources

Covers how digital data is captured across channels and devices. Connects collection methods to downstream analysis accuracy.

Lesson 2 • Core KPIs and Metrics Frameworks

Defines essential marketing KPIs and connects them to business objectives. Provides a structured approach to metric selection.

Lesson 3 • The Digital Analytics Ecosystem

Maps the full landscape of data sources, platforms, and measurement layers. Establishes vocabulary used throughout the course.

Lesson 1 • Custom Dimensions, Metrics, and Segments

Extends default platform data with custom attributes tied to business context. Enables audience and behavior segmentation beyond defaults.

Lesson 2 • Data Quality Auditing and Governance

Establishes processes to detect and correct tracking errors. Maintains data integrity as a prerequisite for trustworthy analysis.

Lesson 3 • Platform Architecture and Data Models

Explains how modern analytics platforms structure hits, sessions, and users. Grounds configuration decisions in platform logic.

Lesson 4 • Conversion and Event Tracking Setup

Configures micro- and macro-conversions across web properties. Ensures accurate attribution and funnel reporting.

Lesson 1 • Data-Driven Attribution Methods

Introduces algorithmic attribution using machine learning on conversion path data. Contrasts with rule-based models for accuracy and scalability.

Lesson 2 • Cross-Channel Attribution Challenges

Addresses gaps caused by walled gardens, device fragmentation, and offline touchpoints. Builds strategies to reduce blind spots.

Lesson 3 • Attribution Reporting and Decision Making

Translates attribution outputs into actionable budget and channel decisions. Connects model insights to marketing mix optimization.

Lesson 1 • Search Campaign Performance Analysis

Analyzes keyword, ad, and quality score data to improve search efficiency. Connects search metrics to downstream conversion outcomes.

Lesson 2 • Social and Display Campaign Analytics

Evaluates reach, frequency, engagement, and conversion data across social and display channels. Identifies creative fatigue and audience saturation signals.

Lesson 3 • A/B and Multivariate Ad Testing

Designs statistically valid experiments to test ad copy, creatives, and landing pages. Applies test results to scale winning variants.

Lesson 4 • Bid Strategy and Budget Optimization

Uses performance data to select and adjust automated and manual bid strategies. Maximizes conversion volume within cost constraints.

Lesson 1 • Behavioral Analytics and Heatmapping

Uses on-page behavioral data to understand user intent and friction. Complements quantitative funnel data with qualitative signals.

Lesson 2 • Customer Journey Mapping with Data

Constructs data-backed journey maps using behavioral and transactional data. Reveals gaps between assumed and actual customer paths.

Lesson 3 • Retention and Lifecycle Analytics

Measures repeat purchase, churn, and engagement patterns across the customer lifecycle. Informs retention marketing strategy with behavioral data.

Lesson 4 • Funnel Analysis and Conversion Rate Optimization

Quantifies conversion rates at each funnel stage and diagnoses underperformance. Prioritizes optimization efforts by revenue impact.

Lesson 1 • Building Reports in BI Tools

Applies BI platform features to connect marketing data sources and build interactive reports. Covers calculated fields, blending, and parameterization.

Lesson 2 • Storytelling with Marketing Data

Structures data narratives to move audiences from insight to action. Adapts communication style to technical and non-technical stakeholders.

Lesson 3 • Dashboard Design and Architecture

Structures dashboards by audience, decision type, and update frequency. Ensures dashboards answer specific business questions efficiently.

Lesson 1 • Predictive Audience Modeling

Builds propensity models to predict purchase, churn, and upsell likelihood. Activates model outputs in ad platforms and CRM systems.

Lesson 2 • Customer Lifetime Value Modeling

Calculates and forecasts CLV using historical transaction and engagement data. Prioritizes acquisition and retention spend by predicted value.

Lesson 3 • Audience Data Sources and Identity Resolution

Consolidates audience data from CRM, web, and ad platforms into unified profiles. Addresses identity fragmentation across devices and channels.

Lesson 4 • Clustering and Unsupervised Segmentation

Uses clustering algorithms to discover natural audience groupings from behavioral data. Validates and labels clusters for marketing activation.

Lesson 1 • Budget Optimization with MMM Outputs

Translates MMM coefficients and response curves into budget allocation recommendations. Simulates scenarios to identify optimal spend levels.

Lesson 2 • Model Building and Validation

Walks through model specification, fitting, and diagnostic testing. Ensures models are statistically sound before informing budget decisions.

Lesson 3 • Marketing Mix Modeling Fundamentals

Explains the statistical basis of MMM and its role in measuring offline and online channels. Contrasts MMM with digital attribution approaches.

Lesson 4 • Unified Measurement Strategy

Integrates MMM, multi-touch attribution, and incrementality testing into a coherent framework. Resolves conflicts between measurement approaches for consistent decisions.