Web Analytics Course

Lesson 1 • The Analytics Measurement Cycle

Explains the plan-collect-analyse-act cycle that governs effective analytics programmes. Connects measurement planning to actionable business outcomes.

Lesson 2 • Key Performance Indicators in Analytics

Teaches how to select and define KPIs aligned to business goals rather than vanity metrics. Students can draft a KPI framework for a given website.

Lesson 3 • Core Metrics and Dimensions

Introduces sessions, users, pageviews, bounce rate, and dimensions such as source and device. Students can identify and define standard metrics in any analytics report.

Lesson 4 • Data Privacy and Ethical Foundations

Covers user consent, data minimization, and privacy-by-design principles relevant to analytics collection. Prepares students to implement compliant measurement strategies.

Lesson 1 • Introduction to Tag Management Systems

Explains how tag management systems centralise script deployment and reduce developer dependency. Students can describe the container, tag, trigger, and variable model.

Lesson 2 • Setting Up an Analytics Account

Walks through account creation, property configuration, and data stream setup. Students leave with a fully configured analytics property ready to receive data.

Lesson 3 • Overview of Analytics Platforms

Surveys major web analytics platforms, comparing their data models, pricing tiers, and use cases. Students can select an appropriate platform for a given business context.

Lesson 4 • Deploying Analytics Tags via TMS

Demonstrates deploying an analytics tracking tag through a tag management system using triggers and variables. Students can publish a working analytics tag without editing site code.

Lesson 1 • Tracking Clicks, Scrolls, and Forms

Implements click, scroll-depth, and form-interaction tracking using tag management triggers. Students can capture the most common on-page interactions without custom code.

Lesson 2 • Custom Dimensions and Metrics

Explains how to extend the default data model with user-defined dimensions and metrics for richer segmentation. Students can register, populate, and report on custom dimensions.

Lesson 3 • Event-Based Data Models Explained

Contrasts session-based and event-based data models and explains why modern platforms favour events. Provides the conceptual basis for all custom tracking work in this chapter.

Lesson 4 • Designing an Event Taxonomy

Teaches a structured approach to naming, categorising, and documenting events before implementation. Students produce a reusable event taxonomy document aligned to business goals.

Lesson 1 • Audience Demographics and Interests

Explores age, gender, interest, and affinity data available in analytics platforms and their limitations. Students can use audience data to inform content and targeting decisions.

Lesson 2 • UTM Parameters and Campaign Tracking

Teaches UTM parameter syntax and best practices for tagging marketing campaigns to ensure accurate attribution. Students can build and audit a UTM tagging strategy.

Lesson 3 • Cohort and Retention Analysis

Introduces cohort analysis to measure how user groups return and engage over time. Students can build a cohort report and draw retention conclusions.

Lesson 4 • Behaviour Flow and User Journeys

Uses flow visualisation and path reports to map how users navigate through a site. Students can identify drop-off points and high-value navigation paths.

Lesson 1 • Attribution Modelling Basics

Introduces last-click, first-click, linear, and data-driven attribution models and their impact on conversion credit. Students can compare models and select the most appropriate one for a campaign.

Lesson 2 • Micro-Conversions and Engagement Goals

Identifies micro-conversions such as newsletter signups and video plays that signal intent before a macro-conversion. Students can build a layered conversion model linking micro to macro goals.

Lesson 3 • Defining and Configuring Conversions

Explains conversion types—destination, event, duration, and pages per session—and how to configure them. Students can set up and verify conversion tracking for common business goals.

Lesson 4 • E-Commerce Tracking Implementation

Covers standard and enhanced e-commerce data collection including product impressions, clicks, and transactions. Students can implement and validate a complete e-commerce tracking setup.

Lesson 1 • Exploration and Ad Hoc Analysis

Introduces free-form exploration, path analysis, and funnel exploration tools for open-ended investigation. Students can navigate exploration workspaces to answer unstructured business questions.

Lesson 2 • Building Segments in Analytics Platforms

Demonstrates creating user, session, and event-scoped segments using platform segment builders. Students can construct and save reusable segments for ongoing analysis.

Lesson 3 • Custom Reports and Dashboards

Teaches how to build custom reports and dashboards tailored to specific stakeholder needs. Students can design a dashboard that surfaces the right KPIs for a given audience.

Lesson 4 • Principles of Effective Segmentation

Explains why segmentation reveals insights that aggregate data conceals and outlines segment types. Students can articulate a segmentation strategy aligned to a business question.

Lesson 1 • Hypothesis Formation and Test Design

Teaches how to write testable hypotheses and design controlled experiments with clear success metrics. Students can produce a documented test plan ready for development.

Lesson 2 • Running A/B and Multivariate Tests

Covers the mechanics of launching A/B and multivariate tests using experimentation platforms. Students can configure, launch, and monitor a live experiment.

Lesson 3 • Iterating and Scaling Experimentation

Describes how to build a continuous experimentation culture and scale testing across an organisation. Students can design an experimentation roadmap and governance process.

Lesson 4 • CRO Fundamentals and Research Methods

Defines conversion rate optimisation and the research methods used to identify optimisation opportunities. Students can conduct a structured CRO audit using quantitative and qualitative data.

Lesson 1 • Analytics Governance and Team Structure

Covers data governance policies, analytics team roles, and processes for maintaining a healthy analytics ecosystem. Students can design a governance framework and define team responsibilities.

Lesson 2 • Predictive Analytics and Machine Learning Basics

Introduces predictive metrics, churn probability, and purchase propensity models available in analytics platforms. Students can interpret predictive insights and apply them to audience targeting.

Lesson 3 • Multi-Channel Attribution and Media Mix

Explores advanced attribution approaches including data-driven models and media mix modeling concepts. Students can evaluate attribution model trade-offs and recommend an approach for a given budget.

Lesson 4 • Building a Measurement Strategy

Guides students through creating a measurement plan that aligns analytics activities to organizational strategy. Students produce a complete measurement strategy document for a real or simulated business.