AB testing mastery – Ton Wesseling

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Become great at A/B testing

Start making more money with your online experiments

Online course: A/B testing mastery course

By Ton Wesseling, Founder of Online Dialogue

Course length: 5h 10min

Learn to get more value out of your online experiments

Discover approaches that work, pitfalls you will encounter, and lots of smart solutions to common issues.

This course will teach you how to get more wins, bigger wins and more insights from your experimentation efforts.

In just 18 lessons, you’ll learn how to

• Get more wins through a long term impact optimization process.
• Calculate where to run experiments, and with what impact.
• Make a hypothesis based on data and psychology.
• Prioritize test hypotheses and experiments.
• Design, start and stop experiments at the right time.
• Come up with proper insights from experiments run.
• Build up a knowledge library on validated user insights.
• Scale your digital experimentation efforts.

Here’s why most of your tests are flat (or losing)

With today’s tools, anyone can run A/B tests – but it’s not the tool that determines the outcome of the test. The most powerful tool is still your brain.

The outcomes of your experiments are mostly determined by what you test and the right treatments. Most people who run tests, but are not getting uplifts, are just doing it wrong. They’re either doing spaghetti testing (“maybe this will work!”), building tests based on gut feelings, or are just tinkering with the small stuff (button colors or font sizes) instead of solving problems.

This course is designed to teach you optimal testing strategies, so you can start winning

The “secret sauce” to getting more wins – and bigger wins – is about the process for identifying the biggest opportunities, and coming up with optimal solutions. It’s also about statistics: knowing when you have a false negative on your hands, and when to stop the tests to begin with.

Sometimes it’s the post-test analysis that will give you the insights you need to turn a failing test into a win. You need to know what to look for when you crunch the data.

This course is right for you if…

• You’re responsible (even partially) for the conversion rate of your digital channels.
• You’re part of a team that runs – or should be running – online experiments.
• Your company or client has at least 1,000 conversions coming in per month.

This course is probably not for you if…

• An advanced statistics guru that knows everything about frequentist and Bayesian statistics, including the fact that false negatives are a way bigger problem than false positives.
• Part of an organization with the highest testing maturity level: Evidence-based optimization is in the DNA of how the company operates.
• Working at a company (or for clients) with fewer than 1,000 conversions coming in per month (the first four lessons are still valuable, but the last four won’t apply to your situation).

Skills you should have before taking this course

• Basic digital analytics know-how
• Basic user research knowledge
• Some experience with running online experiments (or you’re going to join a team soon that is doing this)

Your full course curriculum

Pillar 1 – “Intro”

This whiteboard lessons will give you an overview on:

• The history of A/B-testing
• The value it can bring to your company
• When to use A/B-testing

Pillar 2 – “Planning”

This is where you will get from “no idea what to A/B-test” to a “prioritized A/B-test roadmap”:

• Do you have enough data to conduct A/B-tests?
• Which KPI to pick?
• Research to get insights for your A/B-tests
• Hypothesis setting
• Prioritize your A/B-tests

Pillar 3 – “Execution”

Now you know which A/B-test you are going to execute it’s time to get it done!

• Design, Develop and QA your A/B-test
• Configure your A/B-test in your tool
• How to calculate the length of your A/B-test
• Monitoring your A/B-test

Pillar 4 – “Results”

Your A/B-test is finished, it’s time to dive in the results with the following lessons:

• A/B-test outcomes
• Presenting your learnings
• Business case calculations

Pillar 5 – “Outro”

You are not here for 1 A/B-test, you want to run a A/B-test program, so the next lessons are:

• Scaling up testing
• Sharing and scaling insights

Pillar 6 – “Bonus”

These bonus lessons are created because of frequently asked questions of students from the A/B-testing mastery course:

• What impact have data tracking issues on my A/B-test?
• What about Multi Arm Bandits, Bandits and AI solutions to experimentation?
• Bayesian or Frequentistic?
• What’s the right A/B-test tool for my company?

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