• Decide how "sensitive" an experiment should be
• Estimate how long an experiment will take
• Prioritize the experiments

## Decide how "sensitive" an experiment should be

Once you decide on a hypothesis, you’ll design an experiment. How many variations to test? They are based on your expertise to generate enough data to determine the best choice. The minimum detectable effect (MDE) represents the relative minimum improvement over the original variant.

Minimum detectable effect (MDE, also known as Minimum Detectable Lift) is a number that estimates the minor improvement you’re willing to be able to detect over control. It determines how "sensitive" an experiment is, and in other words, it's an anticipated lift over the control, that can be measured with a degree of certainty.

MDE is the smallest possible change that would be worth investing the time and money to design the test and implement the change permanently on the site. It's important to know: a lower MDEs means increase traffic to ensure that a smaller lift is truly valid.

Use MDE to estimate how long an experiment will take given the following:

• Baseline conversion rate
• Statistical significance
• Traffic allocation

To get the data to evaluate your hypothesis, you need to run an experiment based on a simple calculation based on MDE, visitors and precision.

Usually, the parameters to consider as standard are the following:

• Statistical significance: 95%
• MDE at least 20%

Using these parameters, adding a number of visitors on each variant, benchmark how long to run an experiment and the impact on the business.

## Estimate how long an experiment will take

The time for experiments is a crucial factor, and it can be calculated using the following formula, or you can use of the following links: