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

ℹ️ EPISODE INFO

Released

November 9, 2023

Duration

1h 23m

Channel

Lenny's Podcast

Watch on YouTube

▶ Open ↗

📝 EPISODE DESCRIPTION

Ramesh Johari is a professor at Stanford University focusing on data science methods and practice, as well as the design and operation of online markets and platforms. Beyond academia, Ramesh has advised some incredible startups, including Airbnb, Uber, Bumble, and Stitch Fix. Today we discuss:

• What exactly a marketplace is, if you boil it down
• What you need to get right to build a successful marketplace
• How to optimize any marketplace
• An easy litmus test to see if there’s an opportunity to build a marketplace in the space
• The role of data science in successful marketplaces
• Ramesh’s philosophy on experimentation and AI
• Advice on implementing rating systems
• Why learning isn’t free

— Brought to you by Sanity—The most customizable content layer to power your growth engine: https://www.sanity.io/lenny | Hex—Helping teams ask and answer data questions by working together: https://www.hex.tech/lenny | Eppo—Run reliable, impactful experiments: https://www.geteppo.com/ Find the full transcript at: https://www.lennyspodcast.com/marketplace-lessons-from-uber-airbnb-bumble-and-more-ramesh-johari-stanford-professor-startup/ Where to find Ramesh Johari:

• LinkedIn: https://www.linkedin.com/in/rameshjohari/
• Website: https://web.stanford.edu/~rjohari/
• X: https://twitter.com/rameshjohari

Where to find Lenny:

• Newsletter: https://www.lennysnewsletter.com
• X: https://twitter.com/lennysan
• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/

In this episode, we cover: (00:00) Ramesh’s background (04:31) A brief overview of what a marketplace is (08:10) The role of data science in marketplaces (11:21) Common flaws of marketplaces (16:43) Why every founder is a marketplace founder (20:26) How Substack increased value to creators by driving demand (20:58) An example of overcommitting at eBay (22:24) An easy litmus test for marketplaces (25:52) Thoughts on employees vs. contractors (28:02) How to leverage data scientists to improve your marketplace (34:10) Correlation vs. causation (35:27) Decisions that should be made using data (39:29) Ramesh’s philosophy on experimentation (41:06) How to find a balance between running experiments and finding new opportunities (44:11) Badging in marketplaces (46:04) The “superhost” badge at Airbnb (49:59) How marketplaces are like a game of Whac-A-Mole (52:41) How to shift an organization’s focus from impact to learning (55:43) Frequentist vs. Bayesian A/B testing (57:50) The idea that learning is costly (1:01:55) The basics of rating systems (1:04:41) The problem with averaging (1:07:14) Double-blind reviews at Airbnb (1:08:55) How large language models are affecting data science (1:11:27) Lightning round Referenced:

• Riley Newman on LinkedIn: https://www.linkedin.com/in/rileynewman/
• Upwork (formerly Odesk): https://www.upwork.com/
• Ancient Agora: https://en.wikipedia.org/wiki/Ancient_Agora_of_Athens
• Trajan’s Market: https://en.wikipedia.org/wiki/Trajan%27s_Market
• Kayak: https://www.kayak.com/
• UrbanSitter: https://www.urbansitter.com/
• Thumbtack: https://www.thumbtack.com/
• Substack: https://substack.com/
• Ebay: https://www.ebay.com/
• Coase: “The Nature of the Firm”: https://en.wikipedia.org/wiki/The_Nature_of_the_Firm
• Stitch Fix: https://www.stitchfix.com/
• A/B Testing with Fat Tails: https://www.journals.uchicago.edu/doi/abs/10.1086/710607
• The ultimate guide to A/B testing | Ronny Kohavi (Airbnb, Microsoft, Amazon): https://www.lennyspodcast.com/the-ultimate-guide-to-ab-testing-ronny-kohavi-airbnb-microsoft-amazon/
• Servaes Tholen on LinkedIn: https://www.linkedin.com/in/servaestholen/
• Bayesian A/B Testing: A More Calculated Approach to an A/B Test: https://blog.hubspot.com/marketing/bayesian-ab-testing
• Designing Informative Rating Systems: Evidence from an Online Labor Market: https://arxiv.org/abs/1810.13028
• Reputation and Feedback Systems in Online Platform Markets: https://faculty.haas.berkeley.edu/stadelis/Annual_Review_Tadelis.pdf
• How to Lie with Statistics: https://www.amazon.com/How-Lie-Statistics-Darrell-Huff/dp/0393310728
• David Freedman’s books on Amazon: https://www.amazon.com/stores/David-Freedman/author/B001IGLSGA
• Four Thousand Weeks: Time Management for Mortals: https://www.amazon.com/Four-Thousand-Weeks-Management-Mortals/dp/0374159122
• The Alpinist on Prime Video: https://www.amazon.com/Alpinist-Peter-Mortimer/dp/B09KYDWVVC
• Only Murders in the Building on Hulu: https://www.hulu.com/series/only-murders-in-the-building-ef31c7e1-cd0f-4e07-848d-1cbfedb50ddf

Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com. Lenny may be an investor in the companies discussed.

🎤 SPEAKERS

• Ramesh Johari

  guest

• Lenny Rachitsky

  host

🧾 EPISODE SUMMARY

In this episode of Lenny's Podcast, featuring Ramesh Johari and Lenny Rachitsky, Marketplace lessons from Uber, Airbnb, Bumble, and more | Ramesh Johari (Stanford professor) explores Stanford expert reveals data, friction, and flywheels behind marketplaces Stanford professor Ramesh Johari explains that marketplaces like Uber and Airbnb don’t sell rides or rooms; they sell the removal of transaction friction for both sides of the market. He frames marketplace design as a continuous Whac-A-Mole exercise of reallocating attention and inventory, inevitably creating winners and losers with every product or algorithm change. A major throughline is the centrality of data and experimentation—moving from pure prediction to causal decision-making, embracing learning as a paid, intentional activity, and avoiding over-reliance on short-term, “winner/loser” A/B test thinking. The conversation also covers how to start a marketplace (hint: don’t start as a marketplace founder), how to design fairer rating systems, and how AI expands hypotheses while increasing the need for strong human judgment.

🔗 RELATED EPISODES

Redefining success, money, and belonging | Paul Millerd (The Pathless Path)

The ultimate guide to product operations | Melissa Perri and Denise Tilles

Brian Chesky’s new playbook

Mastering product strategy and growing as a PM | Maggie Crowley (Toast, Drift, TripAdvisor)

Unpacking Amazon’s unique ways of working | Bill Carr (author of Working Backwards)

Reflections on a movement | Eric Ries (creator of the Lean Startup methodology)