Data Marketing Course

Lesson 1 • Data Quality and Governance Basics

Introduces accuracy, completeness, and consistency as quality dimensions. Connects poor data quality to wasted spend and missed targeting.

Lesson 2 • What Data Marketing Actually Is

Defines data marketing by contrasting it with intuition-based approaches and maps its core components. Establishes shared vocabulary used throughout the course.

Lesson 3 • Ethical and Regulatory Foundations

Covers consumer privacy rights, consent frameworks, and data minimisation principles. Grounds ethical practice in business risk and consumer trust.

Lesson 4 • The Data Marketing Ecosystem

Maps the tools, teams, and data sources that form a modern marketing stack. Shows how each element connects to campaign execution.

Lesson 1 • Tag Management and Pixel Implementation

Explains how tags and pixels fire data to analytics and ad platforms. Teaches implementation logic without requiring deep coding skills.

Lesson 2 • Customer Data Platforms and CRMs

Distinguishes CDPs from CRMs and explains when each is appropriate. Shows how unified profiles are built from multiple data sources.

Lesson 3 • Data Storage and Access Architecture

Introduces data warehouses, data lakes, and marts as storage options for marketing data. Connects storage choice to query speed and team accessibility.

Lesson 4 • Data Cleaning and Preparation

Teaches deduplication, normalisation, and handling of missing values in marketing datasets. Prepares students to deliver analysis-ready data.

Lesson 1 • Audience Activation Across Channels

Covers how segments are pushed to ad platforms, email tools, and personalisation engines. Addresses match rates and identity resolution in activation.

Lesson 2 • Lookalike and Predictive Audiences

Explains how seed audiences are used to model and expand reach to similar prospects. Introduces predictive scoring as a targeting enhancement.

Lesson 3 • Segmentation Strategy Fundamentals

Defines segmentation criteria and explains why granularity must match campaign objectives. Introduces the trade-off between segment size and specificity.

Lesson 4 • Segment Performance Measurement

Defines KPIs for evaluating segment quality and campaign fit. Teaches iterative refinement based on performance feedback.

Lesson 1 • Dashboard Design and Reporting

Teaches principles of effective marketing dashboards for different stakeholder audiences. Covers layout, chart selection, and automated reporting workflows.

Lesson 2 • Experimentation and A/B Testing

Introduces hypothesis-driven testing, sample size calculation, and statistical significance for marketing experiments. Connects test results to iterative campaign improvement.

Lesson 3 • Web and Campaign Analytics

Covers traffic analysis, session behaviour, and campaign performance reporting using analytics platforms. Teaches UTM parameter strategy for accurate source attribution.

Lesson 4 • Core Marketing Metrics Framework

Establishes a hierarchy of metrics from awareness to revenue and maps each to funnel stages. Prevents vanity metric traps by linking metrics to business outcomes.

Lesson 1 • Email and CRM Personalisation

Covers dynamic content, behavioural triggers, and lifecycle-based messaging in email and CRM systems. Ties personalisation depth to open, click, and conversion rates.

Lesson 2 • Personalisation Strategy and Maturity

Maps personalisation from rule-based to AI-driven and helps students assess their organisation's current maturity. Frames personalisation as a business capability, not just a tactic.

Lesson 3 • Omnichannel Personalisation Orchestration

Explains how to coordinate personalised messages across email, paid, web, and in-store channels. Addresses data synchronisation and message sequencing.

Lesson 4 • Privacy-Safe Personalisation Techniques

Covers contextual targeting, cohort-based personalisation, and on-device processing as privacy-preserving alternatives. Balances relevance with consumer trust.

Lesson 1 • Search and Social Campaign Targeting

Covers keyword intent data, audience layering, and custom audience uploads for search and social platforms. Teaches targeting refinement using performance data.

Lesson 2 • Paid Media Data Fundamentals

Introduces the data signals that power paid media targeting and bidding decisions. Connects first-party data quality to ad platform performance.

Lesson 3 • Budget Allocation and Bid Optimisation

Teaches data-driven budget allocation across channels using performance signals and marginal return analysis. Covers automated bidding strategy selection.

Lesson 4 • Programmatic Advertising and DSPs

Explains real-time bidding, deal types, and data management in programmatic buying. Covers brand safety and inventory quality controls.

Lesson 1 • Customer Lifetime Value Modelling

Teaches CLV calculation methods and their use in acquisition budget setting and retention prioritisation. Connects CLV to long-term revenue strategy.

Lesson 2 • Model Deployment and Monitoring

Covers the steps from model training to production deployment and ongoing performance monitoring. Addresses model drift and retraining triggers.

Lesson 3 • Recommendation Systems in Marketing

Explains collaborative filtering, content-based, and hybrid recommendation approaches. Covers implementation considerations for e-commerce and content platforms.

Lesson 4 • Predictive Analytics Foundations

Introduces regression, classification, and clustering as the core model types used in marketing. Frames each model type by the marketing question it answers.

Lesson 1 • Aligning Data Strategy to Business Goals

Translates business objectives into data marketing priorities and measurable success criteria. Prevents strategy-execution misalignment.

Lesson 2 • Measuring and Evolving the Strategy

Establishes review cadences, performance benchmarks, and feedback loops to keep the strategy current. Connects ongoing measurement to strategic iteration.

Lesson 3 • Technology and Vendor Selection

Teaches a structured evaluation process for selecting marketing technology based on data needs and integration requirements. Covers build vs. buy decisions.

Lesson 4 • Building a Data-Driven Marketing Team

Defines the roles, skills, and operating models needed to execute a data marketing strategy. Covers hybrid team structures and capability development.

Lesson 5 • Auditing Current Data Marketing Maturity

Provides a structured framework for assessing data, technology, talent, and process maturity. Identifies gaps between current state and strategic goals.