February was the month of feature flags! Last month we rolled out our new free feature management offering so naturally we wanted to dive deeper into why Statsig loves feature flags and why you should too.
This virtual meetup offered insight into some really interesting customer use cases, some history on Statsig’s SDK architecture, and answered all of our audience's hard-hitting questions.
Feature flags are table stakes when it comes to building and optimizing products.
Statsig product manager MA Seger and Engineering Lead Tore Hanssen discuss how feature flags work, best practices for using them, and what makes Statsig’s Feature Management offering unique.
They also cover some of the early architecture decisions Statsig’s SDK team made when building our feature flagging infrastructure, as well as how customers continue to evolve our platform in creative ways. Enjoy this on-demand viewing and we hope you can join us live in the future!
Hypothesis Testing often confuses data scientists due to mixed teachings on p-values and significance testing. This article clarifies 10 key concepts with visuals and intuitive explanations.
I discussed 8 A/B testing mistakes with Allon Korem (Bell Statistics) and Tyler VanHaren (Statsig). Learn fixes to improve accuracy and drive better business outcomes.
Introducing Differential Impact Detection: Identify how different user groups respond to treatments and gain useful insights from varied experiment results.
Identify power users to drive growth and engagement. Learn to pinpoint and leverage these key players with targeted experiments for maximum impact.
Simplify data pipelines with Statsig. Use SDKs, third-party integrations, and Data Warehouse Native Solution for effortless data ingestion at any stage.
Learn how we use Statsig to enhance our NestJS API servers, reducing request processing time and CPU usage through performance experiments.