Hey <!channel>! I'd like to welcome @crooked-rainbow-90115 to the team and to the community. Hampus is going to be writing about experimentation issues for GrowthBook, providing his view point as a Data Scientist who has worked on experimentation for years. The first post is about when your experiment lift doesn't tell you the whole story about your user base, and how to think about how valuable dimension breakdowns can be! • Here's the blog post: https://blog.growthbook.io/your-experiment-lift-is-an-average-which-users-actually-benefited/ • And Hampus' initial post on LinkedIn: https://www.linkedin.com/posts/hampus-poppius_potential-distributions-of-heterogeneou[…]m=member_desktop&amp;rcm=ACoAACb1sFoB7ch8-qG6noA4ddje-4coz-GOnvE Please let us know how you use dimension breakdowns in your experiment analysis, or what you'd like Hampus to write about next!

Hey everybody 👋 Very excited to join the community and help out where needed. Feel free to reach out if you need any input. I'd be super keen to hear what you find challenging in your experimentation flow and what topics you would like me to dissect next 🧐

hi Hampus! i love your name

Tack @ripe-dinner-7830! Also, we'd be really interested to hear if people are using Segments (aka Heterogeneous Treatment Effects) regularly. If you have an internal playbook for it, or any thoughts about it, I'm sure many here would be interested. I'm gonna share some practical tips in a follow-up post soon, but I'm sure many of of you are already doing great out there. Feel free to share 🙏

Really clear visuals that tell an important story - thanks for the blog post Hampus!