Archive

Monthly Archives: October 2019

Micro vs. Macro Conversions with A/B Testing

Which metric should you use to call a successful test winner, your macro conversion or the micro conversions? This is one of the most common questions I see. A/B testers need to understand which metrics they should use for evaluating test results.

This video will help you learn about choosing the best split testing metrics.

In this video, you will learn several things to improve your testing efforts including:

  • What a macro conversion is
  • What a micro conversion is
  • How to choose the best metrics for your testing programs
  • When to prioritize micro conversions first

Testing Theory is where professional testers turn to do better A/B testing and get more conversions.

Monetizing A/B Test Results

Split test results that don’t show an annualized impact aren’t as good for a number of reasons. Get more buy-in for testing by annualizing your A/B testing results.

This video will help you learn a ton about foundational tests to jumpstart your split testing.

In this video, you will learn several things to improve your testing efforts including:

  • 4 benefits of monetizing your test results
  • 4 inputs into the annualizing formula
  • The exact annualized monetization formula I use on my test results

Testing Theory is where professional testers turn to do better A/B testing and get more conversions.

Perfect Amount of Traffic Per Test Variation

How much traffic should you have per test? What about the ability to choose the percent of the audience per experience? How should you split the traffic among your different variations?

There is a perfect amount of traffic to include with each test and each tested variation.

In this video, you will learn about 4 strategic reasons for including more traffic in each test:

  • Segmentation implications
  • Statistical confidence implications
  • Population representation implications
  • Speed and timing of results implications

Testing Theory is where professional conversion rate optimizers turn to do better A/B testing and get more conversions.

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