Experiment
on any feature.
Measure the impact of what you ship, with experimentation loved by engineers and product teams.
Eliminate experimentation friction.
Bring experimentation into your release process, using the feature flags you already trust.
Maximize impact, not risk.
Test any feature, model, or prompt. Learn from every release, adapt quickly, and improve over time.
Trust the data.
Replace hunches with statistically sound data. Get reliable insights and ship with confidence.
How it works
Build experiments where your features live; not in a separate tool.
Plan collaboratively in the same tool you use to ship features.
Preview the right audience and preview assignment logic before launch.
Test anything, from page layouts to AI-powered features.
Rest easy while your experiment runs. Gain Insights that drive progress.
Monitor metrics, traffic, and experiment health in real time.
Visualize experiment results and slice by segments for further analysis.
Spot trends early and shift traffic to winning variations with multi-armed bandit experiments.
Make data-informed decisions. Ship winners with one click, or remix your test in real time.
Instantly ship when statistical significance is reached, no redeploys required.
Add more variants and metrics, or adjust targeting as you learn.
Optimize AI-driven features by adjusting logic, inputs, or prompts across iterations, without starting over.
Dive into the why behind each release, then turn insight into your next big win.
Slice results by device, geo, cohort, or any attribute you define.
Visualize results, share with your team, and turn insights into action.
Export everything to your warehouse for custom analysis on business data.
Built for experimentation teams
Engineers
- Leverage feature flags to conduct experiments directly in your workflow.
- Test anything from a simple feature to AI-powered features.
- Ship statistically valid results safely, instantly, without redeploys.
Product Managers
- Visualize experiment results and understand user behavior.
- Slice data by cohort, region, or device to uncover deeper insights.
- Connect feature launches to key business metrics, like conversion and retention.
Data Teams
- Choose the right model—Bayesian or Frequentist—for every test.
- Use trusted statistical models to deliver reliable results and segment data for deeper insights.
- Analyze results using source of truth business data from your warehouse.
Real results from real releases
"LaunchDarkly helped to democratize the experimentation practice and bring together data, product, and engineering teams working together around the same project."
David Tieba
Head of Product Analytics
"LaunchDarkly has given us much more flexibility than our previous tools for feature flagging and A/B testing. We’re able to experiment more effectively and make better data-driven decisions.”
Rema Morgan-Aluko
SVP Technology
"The ability to target experiments and analyze results efficiently has been a game-changer for us. It’s enabled us to run more tests and gain actionable insights much faster. ”
Riley Duncan
Sr. Data Analytst
"By connecting to Snowflake, we can move more quickly when new models are released, which means we can say yes to more ideas. We can take real risks on these things.”
Jon Noronha
Co-founder and Chief Product Officer
"LaunchDarkly helps us safely roll out and experiment with AI and product features without requiring engineering deploys for every variation.”
Vincent L.
Data Scientist, Information Technology and Services Company
"We can test new features with specific users, run A/B tests, and turn off features instantly if something breaks. This means fewer production issues, faster feedback, and more control over our releases.”
Jwalit Shah
Software Engineer
Experiment with confidence.
Ship what works.
Advanced experimentation built in.
Design and launch any experiment, from page layouts to AI-powered features, with the control, flexibility, and statistical rigor required.
Advanced experimentation built in.
Design and launch any experiment, from page layouts to AI-powered features, with the control, flexibility, and statistical rigor required.
Mutual exclusion
Ensure experiments don’t interfere with each other by simply controlling which users see which tests.
Multi-armed bandits
Automatically shift traffic toward winning variations to maximize impact faster.
AI experimentation
Run experiments across prompts, models, and agents to learn what performs best in production.
Data insights made clear.
Slice, segment, and visualize results. Share clear insights that turn learnings into action.
Data insights made clear.
Slice, segment, and visualize results. Share clear insights that turn learnings into action.
Intuitive results summaries
View experiment performance at a glance and share clear, actionable experiment summaries.
Results segmentation
Slice results by device, geo, cohort, or any attribute you define.
Add metrics and attributes anytime
Explore your experiments on the fly by tracking new metrics or audience attributes without restarting.
Data flexibility for all teams.
Leverage source-of-truth metrics, get deeper analysis, and understand feature impact on the business level.
Data flexibility for all teams.
Leverage source-of-truth metrics, get deeper analysis, and understand feature impact on the business level.
Custom events import
Leverage your organization’s trusted metrics to measure experiments against your team's KPIs.
Data export
Export experiment results to your data warehouse for custom reporting and analysis.
Warehouse native experimentation
Run LaunchDarkly experiments on top of your existing data and measure against trusted metrics.
Vestiaire Collective leads retail innovation with A/B testing
Streamlined
experimentation process
/ /
LaunchDarkly is really useful. It saves us a lot of time. It doesn't make sense for us to build our own internal tooling for these kinds of processes. We would never have a return on investment on that.
Read more
Gamma generates viral conversion growth with warehouse-native experiments for AI features
20%
lift in paid subscriptions
/ /
Now that we can join our LaunchDarkly experiments to our Snowflake data, we can measure real user and business outcomes. We can take bigger risks in the kinds of AI features we build, and we can validate that they're worth it because we can see downstream impacts all the way through.
Read moreSavage X Fenty keeps shoppers engaged with rapid, reliable experiments.
15%
improvement in site performance
/ /
LaunchDarkly gave the business teams the confidence that experiments could be run reliably and the data could be trusted.
Read moreBuilding a culture of experimentation at Stash
Advanced
back-end experimentation
/ /
LaunchDarkly has allowed us to leverage back-end-driven experimentation across all of our client platforms (iOS, Android, Web, etc.).
Read more
Learn more about Experimentation.
Webinar
Scaling AI and Feature Experiments
with LaunchDarkly, AWS & Gravity9
Blog
Why unifying feature delivery and experimentation is essential.
What makes experimentation with LaunchDarkly stand out among other tools on the market?
Blog
When does experimentation add value? A product manager’s guide.
10 compelling situations where you should consider running an experiment.
webinar
Experimentation Excellence: Real-Life Examples and Best Practices Using LaunchDarkly.
Continuous experimentation is key to data-driven product development and innovation.
webinar
Warehouse Native Experimentation for Engineering, Product, and Data Teams.
Explore how LaunchDarkly Experimentation integrates with Snowflake AI Data Cloud.
Blog
How to design, prioritize, and run high-impact experiments
Run fewer, higher-impact experiments with clear metrics and minimal noise.
Want to measure the impact of what you ship?
