Netflix model testing process
Refine your feature development strategy with the Netflix Model Testing Process example.
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about this example
Data-driven decision-making is at the heart of Netflix's approach to feature rollouts. This example diagram illustrates a testing process informed by this philosophy:
- Hypothesis Formulation: Begins with an initial hypothesis that leads to the decision-making on the model.
- Model Testing: Details the iterative process of training the model, testing it offline, and validating the hypothesis.
- A/B Testing: Describes designing an A/B test, choosing a control group, and rolling out a prototype to observe behavior.
- Results and Rollout: Shows how results are analyzed and, if successful, how the feature is rolled out to all members.
When to use
- Feature Experimentation: When experimenting with new features and needing a structured approach to validate assumptions.
- Performance Analysis: When analyzing the performance of different models or features before a full-scale rollout.
- Continuous Improvement: When iterating over product features to ensure significant improvement in user experience or performance.
How to use
- Start editing: Duplicate the example file and double-click on the diagram to customize it according to your feature testing needs.
- Customize diagram: Add or modify nodes, groups, and relationships to mirror your organization's testing and decision-making process.
- Customize layout: Drag elements on the diagram directly on the canvas to create a clear and actionable test flow.
- Collect feedback: Share the diagram with your product team and stakeholders to gather insights and achieve consensus on the process.
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