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Bayesian vs. Frequentist A/B Testing: What's the Difference?

There’s a philosophical statistics debate in the A/B testing world: Bayesian vs. Frequentist.

This is not a new debate. Thomas Bayes wrote “An Essay towards solving a Problem in the Doctrine of Chances” in 1763, and it’s been an academic argument ever since.

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When to Run Bandit Tests Instead of A/B/n Tests

When should you use bandit tests, and when is A/B/n testing best?

Though there are some strong proponents (and opponents) of bandit testing, there are certain use cases where bandit testing may be optimal. Question is, when?

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10 Google Analytics Reports That Tell You Where Your Site is Leaking Money

Your website is leaking money. Everybody’s is.

The first step toward plugging the leaks is identifying where the leaks are. Which funnel steps, which layers of your site, which specific pages are leaking money? Google Analytics can provide answers.

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How to Build Robust User Personas in Under a Month

Customer personas are often talked about in marketing and product design, but they’re almost never done well.

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How to Deal with Outliers in Your Data

One thing many people forget when dealing with data: outliers.

Even in a controlled online A/B test, your data set may be skewed by extremities. How do you deal with them? Do you trim them out, or is there another way?

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12 A/B Testing Mistakes I See All the Time

A/B testing is fun. With so many easy-to-use tools, anyone can—and should—do it. However, there’s more to it than just setting up a test. Tons of companies are wasting their time and money.

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How to Analyze Your A/B Test Results with Google Analytics

A/B testing tools like Optimizely or VWO make testing easy, and that’s about it. They’re tools to run tests, and not exactly designed for post-test analysis. Most testing tools have gotten better at it over the years, but still lack what you can do with Google Analytics – which is like everything.

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Survival of the Fittest Variation: Evolutionary Algorithms in Optimization

If you read this blog regularly, you probably don’t need an introduction to CRO or A/B testing. You know the major players, best practices, and you’ve likely tested your fair share of ideas.

But, as an expert, you likely know some of the persistent frustrations with current approaches. To name just a pair:

  • Testing simply takes time.
  • Our best instincts are often wrong.

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How to Do Conversion Attribution Modeling

Customers don’t usually see one ad and then click over to purchase.

In reality, the path is much more complex, and usually includes various marketing channels – organic and paid search, referral, social media, television.

But if you’re a rigorous and data-driven marketer, the question has to cross your mind: how much credit can I give each channel for this conversion?

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How Many Variations Can You Have in an A/B/n Test?

Just when you start to think that A/B testing is fairly straightforward, you run into a new strategic controversy.

This one is polarizing: how many variations should you test against the control?

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How to change your marketing during and after the crisis

The world has already changed. Your marketing should too.

Check out our Live Panel series with experts in four different industries.

These leaders will discuss how to navigate uncertain times in:

  • Saas & subscription – with Guillaume “G” Cabane from G2 and Patrick Campbell from ProfitWell
  • eLearning – with Dan Layfield from Codeacademy and Dan McGaw from Effin Amazing
  • B2b (coming soon)
  • Ecommerce (coming soon)
Register today

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