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Ramesh Johari

Professor of Management Science and Engineering at Stanford University, with extensive experience in online experimentation and marketplaces.

Top 3 podcasts with Ramesh Johari

Ranked by the Snipd community
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228 snips
Nov 9, 2023 • 1h 24min

Marketplace lessons from Uber, Airbnb, Bumble, and more | Ramesh Johari (Stanford professor, startup advisor)

Ramesh Johari, Stanford professor and startup advisor, discusses marketplace design and optimization. Topics include building successful marketplaces, role of data science, implementing rating systems, and the impact of AI. Also mentioned are experimentation, the launch of the super host badge at Airbnb, and favorite products and life motto.
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21 snips
Oct 3, 2019 • 1h 12min

Marketplaces Deep Dive with Ramesh Johari

We're joined by Stanford professor and senior advisor to Airbnb, Uber, Stitch Fix, and Wave Capital, Ramesh Johari, who is one of the world's leading experts in marketplaces. Ramesh has been advising David and his partners at Wave since day one, and we're super excited to bring his incredible experience and insights to all of our ACQ2 listeners. In this conversation we dive deep into nearly every aspect of starting, building and then operating a marketplace at scale. Whether you are a marketplace entrepreneur, employee, investor, or just curious about how some of the most powerful businesses of our time work, this is not one to miss!Sponsors:Vanta
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4 snips
Nov 7, 2024 • 51min

Episode 4: How to Build an Experimentation Machine and Where Most Go Wrong

Ramesh Johari, a Professor at Stanford University, dives into the evolution of online experimentation, especially for tech companies and marketplaces. He discusses how organizations can shift to self-learning models and the common pitfalls they encounter, such as risk aversion. The conversation touches on the transformative impact of generative AI on experimentation processes. Ramesh also shares strategies for cultivating a culture of learning from failure and integrating data scientists to enhance business value, all while moving beyond traditional A/B testing methods.