LaunchDarkly’s experimentation feature simplifies the process of setting up, running, and analyzing experiments. It supports multivariate tests, real-time data visualization, and seamless integration with feature flags, enabling teams to optimize and enhance user experiences effectively.
Vendor
LaunchDarkly
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Product experimentation
Maximize the business impact of every software feature you ship.
Realize the promise of experimentation
LaunchDarkly removes silos and complexity from the experimentation process, allowing any team to easily set up, run, and act upon valid experiments.
Multivariate (A/B/n) experiments
Quickly test multiple feature variations with multivariate experiments.
Metric groups
Create reusable metric groups that track how experiments affect key funnel metrics.
Traffic allocation
Define your experiment audience—either a targeted segment or a random sample percentage of users. Prevent carryover bias.
Shipping experiment winners
Release winning feature variations with a few clicks by connecting experiments to the engineering process.
Feature flags + experiments = revenue growth
LaunchDarkly layers experimentation on top of feature management, making it easy to run controlled experiments and ship winning features from experiments. **1 **Create a flag Wrap every new feature in a feature flag. **2 **Create and assign metrics Define the performance data you want to collect: conversions, clicks, page load time, etc. **3 **Define your sample audience Create a targeted experiment sample or select a random percentage of users tied to a funnel stage. **4 **Start recording Record data for assigned metrics and tweak the experiment as needed. **5 **Visualize results Illustrate data stories with reliable data, giving key stakeholders a shared view of results. **6 **Identify and ship the winner Release the winning feature variation to the full intended audience immediately.
Full-stack product analytics and optimization
Unlike the scores of visual editors on the market, LaunchDarkly lets engineers run back-end and infrastructure optimization experiments. For example, you can…
- Easily run an experiment to measure the impact of a new API on page load times
- Measure the impact of a new database implementation on system performance
- Measure the impact of a new search feature in your mobile app on latency