Maven

Chelsea Wilson

test

TEST 1

Amazon

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Learn from a world-leading expert how to design and analyze trustworthy A/B tests to evaluate ideas, integrate AI/ML, and grow your business

Author of best-selling A/B testing book

Microsoft

Airbnb

Dr. Ronny Kohavi

Technical fellow and VP at Microsoft & Airbnb, co-author of A/B testing book

9 March 2026

1 June 2026

Through multiple real examples of well-run experiments and stories from Microsoft, Amazon, and Airbnb, you will see the humbling reality that we are terrible at assessing the value of ideas.Trivial changes can be surprisingly useful, whereas large efforts often fail. Accelerate innovation by building Minimum Viable Products (MVPs) and features, and make the organization more evidence-based and humble as it adopts and learns to use evidence from the gold standard in science—the controlled experiment.You will understand the challenges in designing and running trustworthy randomized controlled experiments (A/B tests), including the importance of the Overall Evaluation Criterion (OEC), scaling, common pitfalls, and Twyman's Law. We cover cultural challenges, institutional memory, maturity model, observational causal studies, offline evaluation, AI/Machine learning and triggering, build-vs-buy trade-offs, challenges, and requested topics. The Advanced Topics course is designed as a technical follow-on: <a target="_blank" rel="noopener noreferrer nofollow" href="https://bit.ly/AdvancedABFS">https://bit.ly/AdvancedABFS</a>

Empower your organization to be data-driven and innovative

Internalize the humbling reality: we are poor at assessing the value of ideas

Understand the key advantages and limitations of A/B testing

Learn how to design metrics and the Overall Evaluation Criterion

Learn how to design trustworthy A/B tests

Learn about the cultural challenges

Learn about the relationship to AI and Machine Learning Modeling

Data science managers and scientists will be able to design and interpret the experimental results in a trustworthy manner

Program managers focused on growth, revenue, conversions, and prioritization will understand how to provide the org with robust clear metric

Engineering leaders will be able to make organizations more data-driven and efficient with fewer severe incidents through A/B tests

Learn advanced A/B-testing topics from a world-leading expert. Ten topics in three days of 2 hours each.

⚠️ Warning: Advanced course 

23 March 2026

15 June 2026 - Advanced

We cover advanced topics not typically addressed in courses and books and leave significant time for interactions and Q&amp;A.Classes are small: typically ~15 live attendees. The course assumes you already took <a target="_blank" rel="noopener noreferrer nofollow" href="https://bit.ly/ABCourseRonKohavi">https://bit.ly/ABCourseRonKohavi</a> or have equivalent knowledge.

Improve your A/B testing capabilities and build trust

Improve your A/B Testing capabilities and trust

Discuss your own questions

Designed as a follow-on to the flagship course: https://maven.com/kohavi/abtesting. 

Take that course first, or have equivalent knowledge

Follow-on to flagship course

Good understanding of p-value misconceptions, statistical power, OEC.

Statistics of A/B Testing

Data science managers and scientists who understand the basics of A/B testing and want to better understand advanced topics

Product and program managers who want to advance their understanding of A/B testing

Bad Learning Design Is Costing You Customers — Here's the Science Behind It

Learning Scientist | L&D Strategist

Vanorsdale Learning Lab

Great Game of Business

Docebo

National Alliance on Mental Illness Florida

English Like a Native

Dr. Christie Vanorsdale, Ed.D, Ms.Ed.

Researcher. Practitioner. 15 years translating learning science into results

Cohort 1

You've updated the onboarding. Rebuilt the knowledge base. Added walkthrough videos, help articles, live training sessions. Your customers still aren't adopting the product the way you need them to.The instinct is to fix the content. More of it. Make it Better, or Shorter. More visual. But, the problem isn't the content.It's that content was never designed to produce learning in the first place.Human beings don't retain complex knowledge because they watched a video or completed a walkthrough. Retention requires intentional sequencing, cognitive scaffolding, and an architecture that reduces friction rather than creates it. Most customer onboarding violates every one of those principles — not because the people who built it weren't smart, but because they were never taught what learning science actually says about how knowledge transfers.This workshop gives founders and leaders the diagnostic framework to identify exactly where their customer education breaks down — and the research-backed principles to fix it. You'll leave with a clear line of sight between learning architecture and the revenue outcomes you actually care about: adoption, retention, and renewal.

Learn the science behind knowledge transfer and leave with a diagnostic framework that connects learning architecture to business outcomes.

Understand why customers aren't retaining your product using learning science

Pinpoint exactly where your customer onboarding breaks down

Apply three evidence-based principles to improve product adoption

Connect learning design decisions to churn, adoption, and renewal.

The Scaling Founder Complex product. Customers churn before reaching value. Onboarding feels broken but there's no framework to diagnose why

The Customer Success Leader Owns onboarding and renewals. Content exists but adoption is flat. Needs a framework and internal buy-in.

The L&amp;D Manager Fixing customer education with no infrastructure or alignment. Knows training theory. Missing the revenue impact language

 In one day, validate YOUR AI Opportunity & leave with a 90-day plan.

ICF MCC · MBA ESSEC · 6,500+ sessions 

Judith Glory

ESSEC MBA · ICF MCC · Executive Coach · 6,500+ sessions

Stop debating about AI. In one day, validate your opportunity and leave with a 90-day plan.

Cohort 2

The pressure to act on AI is real. But most leaders are making decisions based on hype, vendor pressure, or fear of being left behind — not on evidence.The result is predictable: pilots that fade, budgets wasted on tools that never get used, and leadership teams that keep debating instead of deciding.This workshop exists because there is a better way. In one structured day, you apply a proven framework to your team's specific reality — not AI in general, not someone else's use case. You evaluate what you do today. You identify where AI could genuinely help. You name every risk and price it. And you make a clear go or no-go call you can stand behind.Not every team should move forward with AI right now. If your numbers say no, this workshop will tell you that clearly — and give you the conditions under which yes becomes the right answer. A No-Go decision backed by data is worth more than a yes driven by pressure.

Managers and leaders navigating the AI moment who need clarity, not inspiration — and a plan they can defend to senior leadership team.

Team managers, VPs, and senior leaders who sense the AI opportunity but need evidence to act — or to confidently say not yet.

Leaders responsible for team output who are ready to validate their AI opportunity once and for all — no tech background needed.

TEST 1

What you'll learn

Why this topic matters

You'll learn from

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