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Slice by Experiment Group in Metrics Explorer

Statsig Product Updates
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1/17/2024
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Analyze Product Metrics by Experiment Group in Metrics Explorer

One of the most valuable aspects of any analytics product is illuminating how your product is performing for different groups. This is useful for general product understanding (is some key product metric over-performing for one group of users vs another?), debugging (is some key perf metric spiking for a specific group), and detailed segment analysis (what’s going on for a specific product feature for macOS 14.1.0 users in Seattle?). Doing these type of analyses for users in different experiment groups hasn’t really been possible until now.

In our product analytics surface, Metrics Explorer, you can now select any metric and split the metric out by experiment group. This unlocks many powerful scenarios such as getting a general sense of how a metric is performing for different groups in experiment, viewing the long term effect of an experiment on different groups, or monitoring and debugging the performance of different experiment variants.

Try out this feature by navigating to Metrics Explorer and clicking on the “Metrics” tab in the navigation bar on the left. Select the metric you are interested in, add a “Group-By” and select “Experiment Group”. Now choose the experiment of interest and see how the metric performance varies between groups in an experiment. You can do all the analysis you expect from Metrics Explorer like adding property filters, changing views (stacked lines, bar charts, etc), or scoping to a specific event based cohort.

Group-By Experiment Group
Metric broken out by experiment groups

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What builders love about us

OpenAI OpenAI
Brex Brex
Notion Notion
SoundCloud SoundCloud
Ancestry Ancestry
At OpenAI, we want to iterate as fast as possible. Statsig enables us to grow, scale, and learn efficiently. Integrating experimentation with product analytics and feature flagging has been crucial for quickly understanding and addressing our users' top priorities.
OpenAI
Dave Cummings
Engineering Manager, ChatGPT
Brex's mission is to help businesses move fast. Statsig is now helping our engineers move fast. It has been a game changer to automate the manual lift typical to running experiments and has helped product teams ship the right features to their users quickly.
Brex
Karandeep Anand
CPO
At Notion, we're continuously learning what our users value and want every team to run experiments to learn more. It’s also critical to maintain speed as a habit. Statsig's experimentation platform enables both this speed and learning for us.
Notion
Mengying Li
Data Science Manager
We evaluated Optimizely, LaunchDarkly, Split, and Eppo, but ultimately selected Statsig due to its comprehensive end-to-end integration. We wanted a complete solution rather than a partial one, including everything from the stats engine to data ingestion.
SoundCloud
Don Browning
SVP, Data & Platform Engineering
We only had so many analysts. Statsig provided the necessary tools to remove the bottleneck. I know that we are able to impact our key business metrics in a positive way with Statsig. We are definitely heading in the right direction with Statsig.
Ancestry
Partha Sarathi
Director of Engineering
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