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Conversion Rate Optimization Talk

These are the live code samples I used for a talk titled "Using Code to Beat Marketers at Their Own Game".

The subject of the talk was how I wrote a piece of code to demonstrate a very non-intuitive pair of principles A/B split testing:

  • to detect increasingly smaller effect sizes you need quadratically larger traffic volumes
  • if your traffic volume grows large enough, standard chi-squared statistical testing will increasingly give positive results for economically insignificant improvements

The code I wrote was a Monte Carlo simulation used to rapidly generate the distribution of traffic volume to minimum detectable effect sizes, and make the non-linear realationship therein transparent.

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Monte Carlo simulation used to demonstrate non-linear relationship between traffic volume and detectable effect sizes in A/B split testing

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