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Why A/A Testing is a Waste of Time

The title may seem a bit controversial, a fairly common question I get from large (and small) companies is—“Should I run A/A tests to check whether my experiment is working?”

The answer might surprise you.

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Statistical Significance Does Not Equal Validity (or Why You Get Imaginary Lifts)

A very common scenario: A business runs tens and tens of A/B tests over the course of a year, and many of them “win.” Some tests get you 25% uplift in revenue, or even higher.

Yet when you roll out the change, the revenue doesn’t increase 25%. And 12 months after running all those tests, the conversion rate is still pretty much the same. How come?

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mouse trap

Even if your A/B tests are well planned and strategized, when run, they can often lead to non-significant results and erroneous interpretations. 

You’re especially prone to errors if incorrect statistical approaches are used.

In this post we’ll illustrate the 10 most important statistical traps to be aware of, and more importantly, how to avoid them.

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Can You Run Multiple A/B Tests at the Same Time?

As a marketer and optimizer it’s only natural to want to speed up your testing efforts. So now the question is—can you run more than one A/B test at the same time on your site?

Let’s look into the “why you shouldn’t” and “why you should” run multiple tests at once.

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Google Analytics & Optimization: 10 Experts Share Their Favorite Reports

Google Analytics helps us identify conversion uplift opportunities. Traffic is precious, and we don’t want to waste it on tests that don’t result in learning or uplifts.

That’s why we want good data for:

  1. Which pages have uplift opportunities;
  2. Specific page issues.

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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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Enroll in the Predictive Analytics: Live Workshop

Introducing our new two-day live interactive training program.

In this program, you will learn the art and science behind no-code predictive analytics. If you want to learn how to apply prediction to your business using supervised machine learning, this live workshop is for you.

Enroll Today

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