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Change & Measure: Before You Launch Your AB Test

New

5 Days

Cohort-based Course

9 checks for fewer throwaway results before you launch your a/b test

This course is popular

5 people enrolled last week.

Change & Measure: Before You Launch Your AB Test

New

5 Days

Cohort-based Course

9 checks for fewer throwaway results before you launch your a/b test

This course is popular

5 people enrolled last week.

Hosted by

Jakub Linowski

Experimentation & Design Leader • GoodUI Founder | Coached ~100 Growth Teams

Jakub Linowski

Experimentation & Design Leader • GoodUI Founder | Coached ~100 Growth Teams

Worked with, learned from and/or coached

Course overview

Is your A/B test design destined for a throw away result?

There are at least 9 ways to improve the quality of your experiments. While working with, coaching and learning from over ~100 teams, some include:

❌ Loosely set triggers dilute your test, extending its duration and causing a loss of power.

✔️ Learn to set better test triggers.

❌ Underpowered tests are more likely to end up insignificant.

✔️ Learn to estimate and set your Minimum Detectable Effects more accurately using historical data.

❌ Compromise and confounding often washes out effects.

✔️ Learn to separate and structure tests with minimum compromise.

❌ Lack of iteration and giving up on an a/b test too quickly leads to wasted effort.

✔️ Learn to design your a/b tests in ways that enables you to iterate.

❌ Too few supporting metrics makes deciding on a/b test results difficult.

✔️ Learn to create custom metrics that reinforce or challenge your hypothesis.

❌ Lack of segmenting may hide the effect in the general sample.

✔️ Learn to setup your tests with custom segments that may have effects in a smaller subset of users.

❌ Some changes may be too weak for you to see any difference.

✔️ Learn to setup your tests with different intensities.

❌ Some ideas & patterns have lower success probabilities, while others may have better odds.

✔️ Learn to use past A/B test data as inputs to increase your odds of detecting signal.

❌ Your first idea may not be the best.

✔️ Learn to explore and generate more A/B test ideas so you have more to choose from.

Who this course is for

You're a UI, UX or CRO Test Designer who is frustrated with too many insignificant experiment results.

You're an Experimentation & Optimization Strategist responsible for leading A/B testing programs your team and your clients can trust.

You're a CRO, Growth or Ecommerce Manager responsible for increasing metrics such as revenue and sales with impactful A/B test results.

You're a UI, UX or CRO Test Designer who is frustrated with too many insignificant experiment results.

You're an Experimentation & Optimization Strategist responsible for leading A/B testing programs your team and your clients can trust.

You're a CRO, Growth or Ecommerce Manager responsible for increasing metrics such as revenue and sales with impactful A/B test results.

By the end of this 1 week course, you'll:

Learn to check your A/B test designs to minimize the odds of insignificant and false positive results

Design A/B tests with more sensitivity

Have fewer throw-away test results

Speed up your experiments

Receive a downloadable template with the A/B test checklist you can use on your projects

Learn from 10-20 common A/B test design scenarios and setups

Join an optional A/B test review session where we'll discuss actively designed experiments and apply the learnings

This course includes

3 interactive live sessions

Lifetime access to course materials

In-depth lessons

Direct access to instructor

Projects to apply learnings

Guided feedback & reflection

Private community of peers

Course certificate upon completion

Maven Satisfaction Guarantee

This course is backed by Maven’s guarantee. You can receive a full refund within 14 days after the course ends, provided you meet the completion criteria in our refund policy.

Course syllabus

Week 1

Jan 28—Feb 1

Course Day 1

Jan
28
Session 1
Tue 1/284:00 PM—6:00 PM (UTC)

Course Day 2

Jan
30
Session 2
Thu 1/304:00 PM—6:00 PM (UTC)

Course Day 3: Your A/B Test Reviewed

Jan
31
Group A/B Test Reviews (Optional)
Fri 1/314:00 PM—5:30 PM (UTC)
Optional

What people are saying

Jakub's coaching profoundly impacted our A/B testing in the last few years. His blend of creativity, analytical sharpness, and mastery of A/B testing not only deepened our understanding of experiment results but dramatically improved our success and conversion rates. Check out Jakub's course to bring your experimentation to the next level.

Daria Kurchinskaia

Senior Product Manager at FINN

Jakub Linowski has built the best UI pattern repository with over 130 patterns at GoodUI.org. These are tied to over 500 A/B tests to help assess their impact. Because the industry success rate of experiments is only 10-20%, using proven patterns is a great way to raise your success rate and impact.

Ron (Ronny) Kohavi

Vice President and Technical Fellow | Data Science, Engineering | Controlled Experiments | Ex-Airbnb, Ex-Microsoft, Ex-Amazon

Jakub is a veteran in the industry and an innovative thinker with a lot to share from years of meticulously collecting and cataloguing his own experience, as well as that of others. Couple this with a strong understanding of the statistics of A/B testing and it is easy to see how his course will help you avoid common pitfalls in experimentation.

Georgi Georgiev

Author of "Statistical Methods in Online A/B Testing" | Founder of Analytics-Toolkit.com

Jakub has a unique ability to blend rigorous statistical analysis with practical UX insights, hard-earned through years of extensive experimentation. He was an instrumental partner in helping us drive meaningful improvements to our on-site funnel, and I'd recommend the opportunity to learn from him.

Harish Venkatesan

Co-founder/CEO at Designlab

We have been actively using GoodUI to strengthen our test hypothesis for a while already. Jakub has not only built up the most comprehensive catalog of experiment patterns but more over developed one of the best understandings for what works and what doesn’t. Working with Jakub as a coach and designing experiments has been revealing and impactful.

Clemens Grave

Head of Product @ TourRadar

Collaborating with Jakub has been invaluable for expanding our experimentation roadmap. His insights on data and testing patterns bring clarity and consistently add fresh, impactful ideas to our backlog. Each conversation is engaging and enlightening—I leave every session with new perspectives and actionable takeaways.

Craig Kistler

Sr. Director Personalization & Experimentation at Signet Jewelers

Meet your instructor

Jakub Linowski

Jakub Linowski has been practicing UI Design (since ~2000) & designing experiments (since 2014). He ❤️ inspiring successful replications by growth and experimentation teams.

He also founded GoodUI.org as an active repository of experiments (with winning, flat and losing results) to separate the more generalizable UI, interaction and copy patterns from the more noisy and less predictable ones.

Over the years, Jakub has either been hired, interacted with, shared results, coached and/or learned from over 100 experimentation teams, including: Microsoft, Thomasnet, Booking, Backstage, Yummly, Elevate, Designlab, Reverb, VivaReal, ZAP, Volders, Rollbar, Kenhub, Expert Institute, Drip Agency, FINN, 3Dhub, Metro to name a few.

Jakub is also known to pay close attention to leaders such as: Netflix, Amazon, Airbnb, Bol, Booking, Etsy and Walmart by simply observing what UI changes they A/B test and then writing about some of their publicly visible experiments.

Jakub holds two design degrees, including a MSc in Design for Interaction (Delft, Netherlands).

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