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Gayatree GanuVice President, Data Science, Facebook
Biography: Gayatree Ganu leads the Engagement Ecosystem and Monetization Data Science teams at Facebook. The Engagement Ecosystem team’s mission is to inform Facebook’s strategy through better understanding and forecasting the health of the app. The Monetization team’s mission is to give everyone a voice and to champion economic prosperity. Gayatree leads a Data Science team with a diverse portfolio spanning modeling and machine learning, product optimizations of user experience, and strategic innovations. Gayatree has a PhD in Computer Science in Search and Recommendations from Rutgers University. She joined Facebook (now Meta) in 2013 and has worked on several problems and product areas through the last 10 years.
Gayatree believes deeply in fairness and equality in opportunity and is passionate about bringing more representation and providing sustained support to women and under-represented minorities in Tech. She leads recruiting for all Data Science roles at Meta, and is helping build an organization that values diverse perspectives as well as strong technical and analytical skills. |
Put the horse before the cart: Why “users first” is important for a good monetization strategy
Meta has over 3B users on our platform engaging with our different products and services. Meta also makes over $100B annually through advertising. There is a strong connection between user engagement on our platform and how we build a sustainable business. Our mission statement for ads at Meta is "Make meaningful connections between people and businesses". Connecting users to monetization or ads is an important part of Meta’s long term success. In this talk I will describe the frameworks to connect user engagement and revenue potential, allowing us to focus our products and services. We will also discuss how high quality and relevant ads can actually bring more engagement to our platform, making it a win-win situation. We will cover a lot of fun and challenging data science topics from weighted metrics, producer-consumer experimental setups, counterfactuals, incrementality, all at an extraordinary scale of 3B users and $100B!