Brought to you by Mixpanel—Event analytics that everyone can trust, use, and afford | Round—The private network built by tech leaders for tech leaders | Eppo—Run reliable, impactful experiments—Ronny Kohavi, PhD, is a consultant, teacher, and leading expert on the art and science of A/B testing. Previously, Ronny was Vice President and Technical Fellow at Airbnb, Technical Fellow and corporate VP at Microsoft (where he led the Experimentation Platform team), and Director of Data Mining and Personalization at Amazon. He was also honored with a lifetime achievement award by the Experimentation Culture Awards in September 2020 and teaches a popular course on experimentation on Maven. In today’s podcast, we discuss:• How to foster a culture of experimentation• How to avoid common pitfalls and misconceptions when running experiments• His most surprising experiment results• The critical role of trust in running successful experiments• When not to A/B test something• Best practices for helping your tests run faster• The future of experimentation—Enroll in Ronny’s Maven class: Accelerating Innovation with A/B Testing at https://bit.ly/ABClassLenny. Promo code “LENNYAB” will give $500 off the class for the first 10 people to use it.—Find the transcript for this episode and all past episodes at: https://www.lennyspodcast.com/episodes/. Today’s transcript will be live by 8 a.m. PT.—Where to find Ronny Kohavi:• Twitter: https://twitter.com/ronnyk• LinkedIn: https://www.linkedin.com/in/ronnyk/• Website: http://ai.stanford.edu/~ronnyk/—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• Twitter: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Ronny’s background(04:29) How one A/B test helped Bing increase revenue by 12%(09:00) What data says about opening new tabs(10:34) Small effort, huge gains vs. incremental improvements (13:16) Typical fail rates(15:28) UI resources(16:53) Institutional learning and the importance of documentation and sharing results(20:44) Testing incrementally and acting on high-risk, high-reward ideas(22:38) A failed experiment at Bing on integration with social apps(24:47) When not to A/B test something(27:59) Overall evaluation criterion (OEC)(32:41) Long-term experimentation vs. models(36:29) The problem with redesigns(39:31) How Ronny implemented testing at Microsoft(42:54) The stats on redesigns (45:38) Testing at Airbnb(48:06) Covid’s impact and why testing is more important during times of upheaval (50:06) Ronny’s book, Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing(51:45) The importance of trust(55:25) Sample ratio mismatch and other signs your experiment is flawed(1:00:44) Twyman’s law(1:02:14) P-value(1:06:27) Getting started running experiments(1:07:43) How to shift the culture in an org to push for more testing(1:10:18) Building platforms(1:12:25) How to improve speed when running experiments(1:14:09) Lightning round—Referenced:• Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing: https://experimentguide.com/• Seven rules of thumb for website experimenters: https://exp-platform.com/rules-of-thumb/• GoodUI: https://goodui.org• Defaults for A/B testing: http://bit.ly/CH2022Kohavi• Ronny’s LinkedIn post about A/B testing for startups: https://www.linkedin.com/posts/ronnyk_abtesting-experimentguide-statisticalpower-activity-6982142843297423360-Bc2U• Sanchan Saxena on Lenny’s Podcast: https://www.lennyspodcast.com/sanchan-saxena-vp-of-product-at-coinbase-on-the-inside-story-of-how-airbnb-made-it-through-covid-what-he8217s-learned-from-brian-chesky-brian-armstrong-and-kevin-systrom-much-more/• Optimizely: https://www.optimizely.com/• Optimizely was statistically naive: https://analythical.com/blog/optimizely-got-me-fired• SRM: https://www.linkedin.com/posts/ronnyk_seat-belt-wikipedia-activity-6917959519310401536-jV97• SRM checker: http://bit.ly/srmCheck• Twyman’s law: http: