GrowthBook 0.9.0 — North Star Metrics, Ad-Hoc Reports, and Huge Performance Improvements⚡️

Graham McNicoll
GrowthBook
Published in
3 min readDec 13, 2021

Just in time for the holidays, this release of the GrowthBook open source experimentation platform includes a number of the most requested features, as well as some huge performance improvements. We cut the number of executed SQL queries in half and the ones that remain are now up to 10x more efficient! Here are some highlights:

North Star Metrics

North Star Metrics show the impact of experiments on metrics

It’s common for a company to set one or two North Star metrics to rally the team behind and drive experimentation efforts. Now you can specify these important metrics in GrowthBook and see how they are improving over time and which experiments had a measurable impact on them.

Ad-hoc experiment reports

You can now create ad-hoc reports of experiment results, and adjust parameters such as dates, metrics, and even add custom SQL filters. This allows data teams to really dive into things and explore without affecting the main experiment results for anyone else. And if you need to move beyond what a report can do, you can easily export to a Jupyter notebook at any time to keep going deeper.

Experiment Update Frequency

We now support adjusting the update frequency for experiment results. You can choose to refresh automatically based on the age of results, a fixed Cron schedule, or even turn off automatic updates entirely. This gives you complete control over how and when queries hit your data source.

Custom metric aggregations

We’re continuing to make metrics more flexible and customizable so they can support all of your use cases. The latest feature lets you control how metrics are aggregated for each user in an experiment if they happen to have multiple conversions. Previously the only option was to sum the values of the conversions, but now you can do anything supported by your SQL engine (avg, median, min, max, etc).

Other improvements:

  • Improved metric query performance, plus added support for SQL template variables for more advanced optimizations
  • Added a cache layer for faster experiment queries
  • Automatic CDN invalidation for experiment changes on GrowthBook Cloud.

Plus numerous other enhancements and bug fixes. You can read about the full list of changes here.

As always, if you have any questions or feedback we would love to hear from you- you can reach us on slack.

We wish you all the best for the holiday season, and a happy new year!

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Graham McNicoll
GrowthBook

Co-founder of GrowthBook (growthbook.io) — open source feature flagging and experimentation. Previously CTO of an ed-tech startup and 3x founder.