Overview

This course offers a structured approach to conversion design, blending user experience principles with business objectives. You'll explore how to align design efforts with measurable outcomes and enhance business performance. Throughout the course, you'll learn how to build scalable strategies that incorporate data-driven decision-making, from insight gathering to testing and optimization. By the end, you'll be able to design experiments that deliver results and improve product impact. What sets this course apart is its blend of theory and real-world application. You’ll apply research techniques to generate testable hypotheses, prioritize design ideas based on feasibility, and validate solutions using data-centered methods. This course is ideal for UX professionals, product designers, and strategists eager to advance their design skills through a data-driven approach. Familiarity with research or testing methods will be beneficial but is not required. Copyright @ 2024 Erin Weigel. All rights reserved. Originally published by Rosenfeld Media, LLC. This course edition is published by Packt Publishing under license from Rosenfeld Media LLC. No part of this material may be reproduced, distributed, or transmitted in any form or by any means—electronic, mechanical, photocopying, recording, or otherwise—without prior written permission from the author or the publisher.

Syllabus

Conversion Design Drives Impact

In this section, we replace opinion-driven decisions with a seven-step Conversion Design workflow, using A/B tests and isolated metrics to compound user value and business impact.

The Understand Phase: Uncovering Impactful Insights

In this section, we blend qualitative observation with quantitative analytics to craft mixed-method UX research, prioritize high-value customer problems, and translate evidence-based insights into measurable product and business gains.

The Hypothesize Phase: Think Clear Logical Thoughts

In this section, we apply the scientific method to business experimentation, formulating null and alternate hypotheses, implementing randomized sampling, detecting sample ratio mismatches, and interpreting results for data-driven decisions.

The Prioritize Phase: The Work and the Workflow

In this section, we learn to prioritize high-impact experiments, allocate effort with a 60/40 foundational-innovation split, and deploy Kanban to surface bottlenecks, blockers, and bloat, accelerating validated learning.

The Create Phase: Set Your Idea Up For Success

In this section, we design conversion experiments by prioritizing accessibility, usability, and culturally aware localization, then leverage aesthetic cues and feedback loops to motivate engagement and collect reliable test insights.

The Test Phase: Test Like You're Wrong

In this section, you will learn to craft hypothesis-driven variant-A-versus-B tests, compute minimum detectable effect and sample size, and interpret confusion matrices to support confident, evidence-based product choices.

The Analyze Phase: Learn From The Data

In this section, you will interpret experiment data with p-values, confidence intervals and conversion math while avoiding peeking bias and volatility, enabling sound, evidence-based design decisions.

The Decide Phase: Make An Optimal Choice

In this section, we expose cognitive biases that distort experiment analysis and apply guardrail metrics and peer review boards to drive balanced, evidence-based product decisions.

Scale It: Drive Impact Across Your Organization

In this section, we analyze cultural levers, build reinforcement systems, and embed norms, traditions, and artifacts that reward rigorous A/B experimentation, scaling Conversion Design's data-driven impact across the organization.