Lenny's PodcastThe ultimate guide to A/B testing | Ronny Kohavi (Airbnb, Microsoft, Amazon)
Ronny KohaviguestLenny Rachitskyhost
CHAPTERS
- 0:00 – 4:29
Ronny’s background
- 4:29 – 9:00
How one A/B test helped Bing increase revenue by 12
- 9:00 – 10:34
What data says about opening new tabs
- 10:34 – 13:16
Small effort, huge gains vs. incremental improvements
- 13:16 – 15:28
Typical fail rates
- 15:28 – 16:53
UI resources
- 16:53 – 20:44
Institutional learning and the importance of documentation and sharing results
- 20:44 – 22:38
Testing incrementally and acting on high-risk, high-reward ideas
- 22:38 – 24:47
A failed experiment at Bing on integration with social apps
- 24:47 – 27:59
When not to A/B test something
- 27:59 – 32:41
Overall evaluation criterion (OEC)
- 32:41 – 36:29
Long-term experimentation vs. models
- 36:29 – 39:31
The problem with redesigns
- 39:31 – 42:54
How Ronny implemented testing at Microsoft
- 42:54 – 45:38
The stats on redesigns
- 45:38 – 48:06
Testing at Airbnb
- 48:06 – 50:06
Covid’s impact and why testing is more important during times of upheaval
- 50:06 – 51:45
Ronny’s book, Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing
- 51:45 – 55:25
The importance of trust
- 55:25 – 1:00:44
Sample ratio mismatch and other signs your experiment is flawed
- 1:00:44 – 1:02:14
Twyman’s law
- 1:02:14 – 1:06:27
P-value
- 1:06:27 – 1:07:43
Getting started running experiments
- 1:07:43 – 1:10:18
How to shift the culture in an org to push for more testing
- 1:10:18 – 1:12:25
Building platforms
- 1:12:25 – 1:14:09
How to improve speed when running experiments
- 1:14:09 – 1:23:07
Lightning round
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