Understand Bias

Are you pitting winners against losers? See how selection bias can mislead you.

Controlled Experiments

Too much data? Learn how to use experiment design to create simple and elegant analytics.

Churn reduction

Why do churn reduction programs fail? See how data can make us pursue wrong targets for churn reduction.

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Latest Thoughts

Yes, you can run and measure two campaigns simultaneously!

Measurement of overlapping campaigns when using controlled experiment design has been a bit of sticky point for many controlled experiment proponents. Some claim that you have to hold other campaigns when measuring, which is a difficult proposition, especially if the goal is to measure every campaign as BAU. My position is different. You have to both test and measure campaigns exactly as they are supposed to be run in the messy BAU world. It makes no sense to measure a campaign under the laboratory conditions only to see that it is not nearly as effective when implemented in the real […]

Universal Control Groups and Advanced Experiments in Marketing

Universal control groups are control groups that are being held out of multiple marketing communications. They are used to measure the cumulative impact of all of the communications the group is excluded from. In compound experiments universal control groups are used in combination individual campaign control groups, providing very powerful tools for sales attribution. Universal control groups are commonly used to achieve these goals: Measure cumulative impact of sequential marketing communications. Measure cumulative impact of concurrent marketing communications. Measure multiple location based tests in retail. Measuring sequential marketing communications with universal control group Marketers believe that advertising has effects that outlive the duration of campaigns, […]

Should you start your Y-axis at zero or is truncating OK?

Answer: Truncating Y-axis is misleading only if you do not show the numbers in context. For example, this :   This is an intentionally poor chart that uses fake data and does not provide context for the numbers. In real life, you should never use a chart like this precisely because you want to tell a story about your data point, and for that you need to show how it relates to other data in comparison. In real life, we use data like these: And the point of the chart is much clearer when you truncate the Y axis on both sides: Let me address other concerns […]

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The is site was created by Tanya Zyabkina using instructions by NYC Tech Club. Free images by Unsplash.