On-Demand: Using experimentation to tackle your big product goals in 2023 | Statsig

Platform

Developers

Resources

Sign In Book a Live Demo

Platform

Developers

Resources

Feature Management

Ship faster and more confidently with insights into the impact of your rollouts on business metrics

Experimentation

Run randomized, controlled, multivariate experiments to observe the impact of your rollouts

Data Warehouse

Seamlessly integrate Statsig's warehouse-native analytics with your existing infrastructure

Dynamic Configs

Dynamically manage your application's behavior for each user without deploying new code

Make your product and business as observable as all of your distributed systems

Always deliver a consistent user experience even when users don't see new features

Separate the signal from the noise and double down on the features that outperform

View your events, users, custom metrics, and all available unit types in one place with customizable views

Let your app's usage choose the optimal configuration with Statsig's automatic multi-armed bandit

Documentation

Documentation to get you started with implementation, completely self-servable

Walkthrough Guides

Guides to get you started on your first Experiment, all the way to advanced Holdouts

SDKs and APIs

Explore REST API and Open Source SDKs in more than 20 languages/frameworks

Open Source Code

All our SDKs and supporting libraries are Open Source and regularly updated

Integration

Learn more about running on the edge, or ingesting data from your Data warehouse

Product Updates

We ship fast, to help you ship faster. Check out all our product updates

How Statsig Works

Get under the hood and check out how Statsig scales with you, without compromising on reliability

Build vs. Buy

Looking to build your own? We understand, and we'll gladly help you build it

Experimentation Community

Have more technical questions? Join the experimentation community, we're there to answer your questions

Peak Velocity

The Statsig Blog. Peak Velocity covers the latest in experimentation, A/B testing and more

Customer Stories

Find out how leading companies are leveraging experimentation to achieve awesome results

A/B Testing Calculator

Looking for a place to start your A/B test? Try different combinations in our calculators

Feature Flags Liberated

Gating features is a core part of the development process. And with Statsig, it's free.

Optimizing AI Model Temp

Autotune can optimize model temperature for any apps that use language models.

What is Product Observability?

Product observability means being able to monitor, control, and gain insight into all of your features.

Experiments with Generative AI

We built a generative AI app in reactJS using OpenAI’s API and Statsig. Here’s what we learned:

Experimentation Platforms

The decision to build versus buy an experimentation and feature flagging platform is not an easy one.

CUPED Explained

CUPED is an implementation that uses pre-experiment data to explain the variance in the result data.

Platform

Developers

Resources

Sign In Book a Live Demo

Feature Management

Ship faster and more confidently with insights into the impact of your rollouts on business metrics

Experimentation

Run randomized, controlled, multivariate experiments to observe the impact of your rollouts

Data Warehouse

Seamlessly integrate Statsig's warehouse-native analytics with your existing infrastructure

Dynamic Configs

Dynamically manage your application's behavior for each user without deploying new code

Make your product and business as observable as all of your distributed systems

Always deliver a consistent user experience even when users don't see new features

Separate the signal from the noise and double down on the features that outperform

View your events, users, custom metrics, and all available unit types in one place with customizable views

Let your app's usage choose the optimal configuration with Statsig's automatic multi-armed bandit

Documentation

Documentation to get you started with implementation, completely self-servable

Walkthrough Guides

Guides to get you started on your first Experiment, all the way to advanced Holdouts

SDKs and APIs

Explore REST API and Open Source SDKs in more than 20 languages/frameworks

Open Source Code

All our SDKs and supporting libraries are Open Source and regularly updated

Integration

Learn more about running on the edge, or ingesting data from your Data warehouse

Product Updates

We ship fast, to help you ship faster. Check out all our product updates

How Statsig Works

Get under the hood and check out how Statsig scales with you, without compromising on reliability

Build vs. Buy

Looking to build your own? We understand, and we'll gladly help you build it

Experimentation Community

Have more technical questions? Join the experimentation community, we're there to answer your questions

Peak Velocity

The Statsig Blog. Peak Velocity covers the latest in experimentation, A/B testing and more

Customer Stories

Find out how leading companies are leveraging experimentation to achieve awesome results

A/B Testing Calculator

Looking for a place to start your A/B test? Try different combinations in our calculators

Feature Flags Liberated

Gating features is a core part of the development process. And with Statsig, it's free.

Optimizing AI Model Temp

Autotune can optimize model temperature for any apps that use language models.

What is Product Observability?

Product observability means being able to monitor, control, and gain insight into all of your features.

Experiments with Generative AI

We built a generative AI app in reactJS using OpenAI’s API and Statsig. Here’s what we learned:

Experimentation Platforms

The decision to build versus buy an experimentation and feature flagging platform is not an easy one.

CUPED Explained

CUPED is an implementation that uses pre-experiment data to explain the variance in the result data.

VIDEO FEATURED

On-Demand: Using experimentation to tackle your big product goals in 2023

Tue Jan 31 2023

Morgan Scalzo

Community and Event Manager

We kicked off the new year with our first virtual meetup hosted by John Wilke with guests Craig Sexauer and Pierre Estephan. This new format offers insight into how the Statsig team thinks about implementing experimentation into project plans for anyone who considers themselves a builder. If you weren’t able to join us live, catch the on-demand conversation below!

Video: Using Experimentation to Tackle Product Goals in 2023

About this virtual meetup:

Product teams are responsible for scaling to achieve aggressive annual KPI targets, often with limited resources. Tune in to get an inside look at the importance of scaling and building with experimentation to hit demanding product targets.

Statsig Data Scientist Craig Sexauer and Engineering Manager Pierre Estephan covered:

How to pick the “right” metrics
Why measuring all product changes matter
Why smaller, scrappy experiments are crucial in H2 to prioritize product features
What insights long-term Holdouts offer that a single experiment does not

Enjoy this on-demand viewing and we hope you can join us live in the future! Morgan Scalzo Community and Event Manager Statsig

Stay Ahead of the Curve

Get Experimentation Insights in Your Inbox!

Permalink: https://www.statsig.com/blog/using-experimentation-product-goals-webinar

Try Statsig Today

Get started for free
Add your whole team!

On a big team? Contact Sales

Recent Posts

Seattle AI Meetup: The wave is here

AI technology has been here for years, but the new wave of AI products and features is game-changing. We covered this, and other topics, at the Seattle AI Meetup.

How to create an experiment review culture (with templates!)

Building a culture of experimentation benefits greatly from things like reviewing experiments regularly and discussing the results.

KNOWLEDGE CULTURE

Why people love Statsig’s customer support

Thanks to our support team, our customers can feel like Statsig is a part of their org and not just a software vendor. We want our customers to know that we're here for them.

What migrating experimentation platforms actually entails

Migrating experimentation platforms is a chance to cleanse tech debt, streamline workflows, define ownership, promote democratization of testing, educate teams, and more.

Understanding sample size

Calculating the right sample size means balancing the level of precision desired, the anticipated effect size, the statistical power of the experiment, and more.

Recency bias: The silent saboteur in statistics

The term 'recency bias' has been all over the statistics and data analysis world, stealthily skewing our interpretation of patterns and trends.

We use cookies to ensure you get the best experience on our website.

Privacy Policy