Google Analytics Smart Rules for Beginners and Analysts Course

Lesson 1 • Account and Property Structure

Maps the Organisation, Account, Property, and View hierarchy. Students configure a property correctly to ensure clean data from day one.

Lesson 2 • Navigating the Analytics Interface

Orients students to the reporting UI, date controls, and segment selectors. Fluency here accelerates work in every reporting chapter.

Lesson 3 • Installing the Tracking Code

Covers tag placement, Google Tag Manager basics, and verification methods. Correct installation is the prerequisite for all data collection topics ahead.

Lesson 1 • Advanced Custom Filters

Introduces regex-based filters for hostname, subdirectory, and field transformations. Builds on basic filter knowledge to handle complex data-shaping needs.

Lesson 2 • Filter Auditing and Maintenance

Establishes a process for documenting, testing, and reviewing filters over time. Prevents data loss from misconfigured or outdated filter rules.

Lesson 3 • How Data Flows Into Analytics

Traces the hit lifecycle from browser to report. Understanding this flow is essential before applying any filter or rule.

Lesson 4 • Excluding Internal and Bot Traffic

Targets the most common data-quality threats: employee visits and bot crawlers. Students configure IP exclusions and bot filtering to protect report accuracy.

Lesson 1 • Event Tracking for Goal Triggers

Links event category, action, and label data to goal completion. Requires tracking code knowledge from Chapter 1 and filter knowledge from Chapter 2.

Lesson 2 • Goal Funnels and Visualization

Interprets funnel visualisation and goal flow reports to find drop-off points. Students translate funnel data into actionable optimisation recommendations.

Lesson 3 • Goal Validation and Troubleshooting

Diagnoses common goal misconfiguration issues including double-counting and missed conversions. Ensures data integrity before goals feed into channel reports.

Lesson 4 • Configuring Destination Goals

Covers URL matching options, funnel steps, and goal value assignment. Students build a checkout funnel goal and verify it in real-time reports.

Lesson 1 • Audience Building for Remarketing

Converts Analytics segments into remarketing audiences for ad platforms. Requires goal and event data from Chapter 3 to define high-value audience rules.

Lesson 2 • Building Custom Segments

Walks through demographic, technology, behaviour, and sequence condition builders. Students create segments that answer specific business questions.

Lesson 3 • Segment Comparison and Reporting

Applies multiple segments simultaneously to standard reports for side-by-side analysis. Students document segment insights in a structured analysis framework.

Lesson 4 • Segment Fundamentals

Defines user-level vs. session-level segments and explains scope implications. Correct scope selection prevents misleading comparisons in later analysis.

Lesson 1 • Campaign Troubleshooting

Diagnoses inflated direct traffic, missing campaign data, and self-referrals. Applies filter and tagging knowledge from earlier chapters to resolve attribution errors.

Lesson 2 • UTM Parameter Tagging

Covers the five UTM parameters, naming conventions, and the Campaign URL Builder tool. Consistent tagging is the prerequisite for reliable campaign reports.

Lesson 3 • Acquisition Reports Deep Dive

Navigates All Traffic, Campaigns, and Keywords reports to evaluate channel performance. Students connect acquisition data to goal completions from Chapter 3.

Lesson 4 • Multi-Channel Funnels

Reveals how multiple touchpoints contribute to a single conversion using path and attribution reports. Challenges last-click thinking with data-driven evidence.

Lesson 1 • Creating Custom Alerts

Walks through the custom alert builder: metric selection, condition operators, and notification settings. Students build alerts for traffic drops and conversion spikes.

Lesson 2 • Scheduling and Automating Alert Reviews

Integrates alerts into a recurring analytics operations cadence. Ensures alerts remain calibrated as site behaviour and business goals evolve.

Lesson 3 • Intelligence Events Overview

Introduces automatic and custom Intelligence Events and their statistical basis. Understanding how Analytics detects anomalies sets the stage for custom alert design.

Lesson 4 • Responding to Alert Triggers

Defines a structured investigation workflow when an alert fires. Students practise diagnosing root causes using segments and acquisition reports from prior chapters.

Lesson 1 • Dashboard Design Principles

Applies data visualisation principles to widget layout, metric selection, and audience alignment. A well-designed dashboard reduces time-to-insight for stakeholders.

Lesson 2 • Sharing and Importing Report Assets

Uses the Solutions Gallery to import community templates and share custom assets. Accelerates report setup and promotes consistency across team members.

Lesson 3 • Scheduled Reports and Email Delivery

Configures automated report delivery to stakeholders on defined schedules. Reduces manual reporting effort and ensures consistent data distribution.

Lesson 4 • Custom Report Builder Fundamentals

Covers Explorer, Flat Table, and Map Overlay report types with dimension and metric selection. Students build a report that answers a specific business question.

Lesson 1 • Integrating Search Console Data

Links Search Console to surface query-level organic data inside Analytics. Connects acquisition channel knowledge from Chapter 5 with on-site behaviour metrics.

Lesson 2 • Data Studio Integration Basics

Connects Analytics as a Data Studio data source to build shareable, interactive reports. Extends dashboard skills from Chapter 7 into a more flexible visualisation layer.

Lesson 3 • Hypothesis-Driven Analysis Framework

Structures analysis around a business question, hypothesis, data pull, and recommendation. Transforms raw Analytics data into evidence-based strategic decisions.

Lesson 4 • Presenting Analytics Insights to Stakeholders

Translates technical findings into executive-ready narratives with supporting visuals. Students deliver a capstone analysis presentation using data from all prior chapters.