Full Stack project Hrtag Build
experiments Hrtag QA and
troubleshoot Hrtag Analyze
results Hrtag Join the
Full Stack allows you to run experiments anywhere in your technology stack. This page will help find you resources for building and running experiments and learning from your results.
Before you build experiments, configure your settings.
- Get started with Full Stack: Introduction and FAQ.
- Full Stack projects: Learn about your account.
- Set up a Full Stack project: Set up your project space.
- Access the datafile: All the instructions that the SDK needs.
- Datafile management: Best practices for synchronization.
- Set up a webhook: Register a URL for datafile updates.
- Integrations: Custom analytics, audience, and event integrations.
- Working with CDNs: Strategies for handling caching.
- Microservices: Options for service-oriented tech stacks.
- Implementation checklist: Set up Full Stack for a production environment.
Set up experiments, target them to certain users, and track key behaviors.
- Create a feature: Enable feature test and rollouts.
- Create a feature test: Experiment on features that you're developing.
- Create a feature rollout: Mitigate risk by progressively rolling out features.
- Create a standalone A/B test: Run one-time tests on your application.
- Create audiences and attributes: Target experiments to specific groups of users.
- Create an event: Track key user behaviors on your application.
- Create mutually exclusive experiments: Isolate interaction effects.
- How bucketing works: Understand Optimizely's bucketing logic.
- Interactions between feature tests and rollouts: Use tests and rollouts together.
- Experimenting with Web and Full Stack: End-to-end experimentation.
Read our whitepaper on feature flagging to learn on how to ship products faster, with less risk and more control.
Monitor the conversion metrics and KPIs that you care about.
- The Results page: See the impact of your changes on key metrics.
- How long to run a test: Decide when to pause or stop an experiment.
- Interpret your results: Take the long view of your experiment data.
- Take action based on results: Build on winning variations, learn from losing ones, and iterate on inconclusive experiments.
- Discrepancies in third-party data: Understand and handle data discrepancies.
- How Optimizely counts conversions: View examples of how conversions are counted.