<aside> 🚧 DISCLAIMER: The following standards and guidelines help you execute quantitative Delivery or Post-Validation Experiments mainly. For other validation methods, please contact the respective go-to person.

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Depending on what type of person you are, this part is the most fun or most strenuous for you. An experiment is only as valuable as its' analyze, so there is no way of cutting that part short.

Experiments can come in all colors and sizes. Analyzing any experiment follows suit this constant process:

1. Define Metrics
2. Collect Data
3. Final Analysis
4. Summarize Results

Let me guide you through that process and help you avoid common pitfalls.

1. Define Metrics

As a best practice, you know your metrics already because they are stated in the acceptance criteria of your target outcome. If you haven't: state now what metrics you will look at during your analysis.

<aside> ❗ Define what metrics you want to analyze before starting the Experiment.

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Click on the toggles for more info:

• Definition of Success Metric
• Definition of Trade-Off Metric

You might also want to learn about your users' behavior with the new solution. Define in advance which supporting metrics you also want to track and check: your supporting metrics. Click on the toggle for more info:

• Definition of Supporting Metrics