Latest Experimentation Posts

New Experimentation tools for PMs who test, learn, and move fast

Test, learn, and ship faster with new Experimentation tools.

Allison Rogers

The Metrics glow-up: Smoother, smarter, simpler

Experience a faster, simpler way to build, manage, and trust your metrics.

Sruthy Kumar

Multiple Multi-Armed Bandits

Run multiple MABs on one flag to optimize experiences in parallel.

Scott Shindeldecker

Dig deeper into the data powering your charts

Explore the data behind your charts to validate results and make informed decisions

Neha Julka

How to learn more from the features you ship

Turn every feature into a chance to learn.

Allison Rogers

Data Export: Now available for BigQuery and Databricks

Export to BigQuery and Databricks in a few clicks.

Allison Rogers

The ecommerce metrics that turn browsers into buyers

Identify the lifecycle metrics that tie customer actions directly to revenue, loyalty, and long-term growth.

Neha Julka

Mastering product-centric delivery: accelerating outcomes with feature management and experimentation

Deliver like a product team by moving quickly, testing often, and measuring what works.

Allison Rogers

Less clutter, more insight: Slice metrics from one event

LaunchDarkly now supports filters for Custom Metric Events.

Eric Wang

Your instincts are good... and instincts + feedback are even better

Teams need real feedback, not just gut instinct, to know what’s actually working.

LaunchDarkly

How to design, prioritize, and run high-impact experiments

Run fewer, higher-impact experiments with clear metrics and minimal noise.

LaunchDarkly

Why MABs are not just fancy A/B tests

Know when it’s smarter to let a bandit optimize in real time.

Jimmy Jin

How to run experiments on high-traffic websites & apps

Running experiments on high-traffic websites creates a unique paradox.

Jesse Sumrak

Making experimentation work for product managers

LaunchDarkly Experimentation is the missing puzzle piece in the PM workflow.

Joni Rustulka

LaunchDarkly and Snowflake help you build, test, and learn—right where your data lives

LaunchDarkly and Snowflake empower engineering, product, and data teams to do more

Neha Julka

How to build strong hypotheses for more insightful experiments

A thoughtful hypothesis can improve A/B tests

Jimmy Jin

Introducing Product Analytics: Understand user behavior directly from your data warehouse

Neha Julka

Randomization units as the foundation of reliable product experiments

The choice of randomization unit is tied to the set of metrics you want to measure.

Jimmy Jin

Watch LaunchDarkly and Snowflake in action with our demo

A new way for engineering, product, and data teams to accelerate experimentation.

Neha Julka

Experimentation starts with engineering

Why unifying feature delivery and experimentation is essential.

Scott Shindeldecker

When does experimentation add value? A product manager’s guide

10 compelling situations where you should consider running an experiment.

Valerie Kroll

LaunchDarkly + Snowflake: Introducing Warehouse Native Experimentation and Product Analytics

New: use Snowflake AI Data Cloud data to measure the impact of LaunchDarkly experiments.

Neha Julka

LaunchDarkly on LaunchDarkly: How we build better web experiences with experimentation

Experimentation capabilities in the LaunchDarkly platform have transformed how the team improves the website.

Emily Coleman

Introducing Event Explorer: Your new tool for creating smarter metrics 

Event Explorer enables users to track, verify, and investigate events sent to LaunchDarkly, simplifying metric creation and improving data transparency.

Giannis Psaroudakis