Netflix on Balancing Data with Judgment for Better Insights

Using data to gain customer insights can be difficult. Using data to gain customer insights from an ever-growing, ever-changing entertainment audience presents a much steeper challenge. In this episode, Elizabeth Stone, VP, Data & Insights at Netflix, explains how her dedicated team reflects the larger Netflix culture, balancing hard data with a mindset of learning and experimentation to make decisions that improve the Netflix experience. 

Tune in to learn:

• Elizabeth’s role as head of Netflix’s data and insights team (2:46)
• How Netflix is leveraging machine learning (11:13)
• The continued culture of innovation at Netflix (13:44)
• Using data to inform intuition and choice (18:00)
• How the data and insights team engages with other stakeholders (22:30)
• How Elizabeth obtains the resources she needs (25:37)
• The importance of cross-functional understanding and collaboration (32:13)

Mentions:

• Gartner Data and Analytics Conference
• Lyft
• Randy Bean, author of Fail Fast, Learn Faster
• ChatGPT/OpenAI
• Daft Punk / Hot Chip / LCD Soundsystem

Guest Bio: 

Elizabeth Stone leads Netflix’s Data & Insights org. Data & Insights is a centralized and globally distributed team that includes: data engineering, metrics development, analytic insights and tooling, research and development of machine learning algorithms, optimization and automation, experimentation and causal inference, and consumer research. The Data & Insights team applies this functional expertise to improve and evolve all parts of Netflix's business including the member-facing product, streaming delivery, content, studio production, games, ads, business operations, and growth. Elizabeth previously worked in finance, both as a trader and as an economic consultant, before transitioning to the tech industry, where she led teams at Nuna and Lyft. She is a graduate of MIT and Stanford University.

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