Data-Driven UX Design Course

Lesson 1 • Types of UX Data

Surveys quantitative, qualitative, behavioural, and attitudinal data. Connects each type to specific design decisions students will encounter later.

Lesson 2 • Framing Research Questions

Teaches how to translate a design problem into a testable research question. Proper framing prevents wasted data collection and misaligned insights.

Lesson 3 • What Data-Driven UX Means

Defines data-driven UX and contrasts it with intuition-led design. Sets the mindset shift required for evidence-based practice throughout the course.

Lesson 4 • The UX Research Ecosystem

Maps the tools, roles, and processes that generate UX data. Provides context for how designers interact with researchers and analysts.

Lesson 1 • Statistical Literacy for Designers

Provides the minimum statistical knowledge needed to interpret UX data correctly. Prevents common misreadings of averages, significance, and sample size.

Lesson 2 • Survey Design for UX

Covers question types, scales, and survey structure for UX contexts. Well-designed surveys yield reliable quantitative signals about user attitudes.

Lesson 3 • Web and Product Analytics

Explains how to read traffic, funnel, and engagement data from analytics platforms. Connects behavioural metrics to specific UX hypotheses.

Lesson 4 • Visualising Quantitative UX Data

Teaches chart selection and data visualisation principles for UX metrics. Clear visuals accelerate stakeholder understanding and design decisions.

Lesson 1 • Moderated Usability Testing

Guides students through planning and running moderated usability sessions. Direct observation of task performance generates actionable design findings.

Lesson 2 • Diary Studies and Longitudinal Research

Introduces diary studies for capturing user experience over time. Longitudinal data reveals patterns invisible in single-session research.

Lesson 3 • Qualitative Data Analysis

Teaches thematic analysis, affinity mapping, and coding for qualitative data. Systematic analysis transforms raw notes into reliable design insights.

Lesson 4 • User Interviews

Covers interview planning, question design, and facilitation techniques. Interviews surface motivations and mental models that quantitative data cannot reveal.

Lesson 1 • Clickstream and Session Analysis

Examines how users navigate products through click paths and session recordings. Behavioural patterns reveal friction points and unexpected usage flows.

Lesson 2 • Instrumentation and Event Tracking

Explains how to define and implement event tracking plans for UX analytics. Proper instrumentation ensures the right behavioural data is captured.

Lesson 3 • Funnel and Conversion Analysis

Analyses step-by-step user journeys to identify where conversions fail. Funnel data directly informs redesign priorities and hypothesis formation.

Lesson 4 • Retention and Engagement Metrics

Covers DAU, MAU, churn, and feature adoption metrics for UX evaluation. Retention data signals whether design changes create lasting user value.

Lesson 1 • Triangulation Techniques

Teaches how to compare and reconcile findings across data sources. Triangulation increases confidence in insights and exposes data artefacts.

Lesson 2 • Communicating Insights to Stakeholders

Teaches how to package and present mixed-methods findings for diverse audiences. Effective communication ensures insights drive real product decisions.

Lesson 3 • Mixed-Methods Research Design

Explains sequential, concurrent, and embedded mixed-methods designs. Choosing the right structure ensures qual and quant data answer the same question.

Lesson 4 • Creating Research Repositories

Covers structuring and maintaining a shared repository of UX findings. Repositories prevent duplicate research and accelerate future design decisions.

Lesson 1 • Building an Experimentation Culture

Addresses organisational practices that sustain continuous UX experimentation. Culture and process determine whether individual test wins compound over time.

Lesson 2 • Sample Size and Statistical Power

Explains how to calculate required sample sizes before launching experiments. Underpowered tests produce unreliable results that mislead design decisions.

Lesson 3 • Analysing and Interpreting Test Results

Guides students through reading experiment results and making ship decisions. Correct interpretation prevents false positives from driving bad design changes.

Lesson 4 • A/B and Multivariate Test Design

Covers experimental design choices including variant creation and traffic allocation. Proper design prevents confounding variables from invalidating results.

Lesson 1 • From Insight to Design Brief

Converts research insights into actionable design briefs with clear success criteria. Briefs align design work with the specific problems data has identified.

Lesson 2 • Continuous Discovery Practices

Introduces continuous discovery as a rhythm of ongoing user contact and data review. Regular touchpoints prevent design drift and keep teams user-centred.

Lesson 3 • Measuring Design Change Impact

Establishes methods for measuring whether a design change improved target metrics. Closing the measurement loop validates design decisions with real evidence.

Lesson 4 • Rapid Prototyping for Testing

Covers fidelity choices and prototyping techniques suited to data-driven iteration. Prototype fidelity should match the precision of the question being tested.

Lesson 1 • UX Research and Data Maturity Models

Introduces maturity models for assessing and advancing organisational UX data practice. Maturity assessment reveals the highest-leverage improvement opportunities.

Lesson 2 • UX Metrics Frameworks

Covers established frameworks for structuring UX measurement at scale. Frameworks like HEART and PULSE connect UX metrics to business outcomes.

Lesson 3 • Connecting UX to Business Outcomes

Teaches how to map UX improvements to revenue, retention, and cost metrics. Business linkage makes UX investment visible and defensible to leadership.

Lesson 4 • Designing a UX Measurement System

Guides students through building a coherent, end-to-end UX measurement system. A well-designed system captures signal at every stage of the user journey.