The benefits of experimentation are well-researched and documented. But that doesn’t always equate to an increasing conversion rate.

In this episode, Jon and Ryan explore why experimentation results don’t always map one-to-one with the real-world outcomes you expect.

Check out the full episode to learn:

1. How post-launch variables make attribution less than clear.
2. Why experiment segmentation means test results aren’t summative.
3. The effect of false positives.

If you have questions, ideas, or feedback to share, connect with us on LinkedIn. We’re Jon MacDonald and Ryan Garrow.