When data isn’t enough – A case study from Uber payments

This session will give you a practical example of launching an experiment at scale within the payments  team at Uber. You’ll see step by step how our product team ideated, implemented, & analyzed the impact of this change using data and more. You’ll also learn about the surprising results we saw and our process to deep dive into these results. Hint: It wasn’t easy!  This session is especially for audiences interested in product data science or working cross functionally as part of a product team.

• Global product changes often require familiarity with local market trends, user preferences, & more
• Experimentation can’t explain everything
• Language, translations, and icons shouldn’t be overlooked

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Claire Hempel – Manager, Data Science, Tech | Uber

Professional with a background in statistics, sociology, and business. Currently leads a team of data scientists which use data to help Uber make better decisions about their Payments Products for users on their Eats and Ride apps.