Mastering Experimentation for Data-Driven Product Decisions

Experimentation is essential for tech products to uncover causal relationships and drive business impact. This session will dive into the fundamentals of experimentation, covering how to define meaningful metrics, design robust experiments, and navigate key trade-offs in decision-making. We’ll explore statistical techniques used to analyze results, ensuring reliable insights that inform product strategies. Whether you're a product manager, data scientist, or engineer, this session will equip you with the knowledge to run impactful experiments and optimize product and business outcomes effectively.

Key Takeaways:

• Learn how to design robust experiments that uncover causal relationships and drive business impact.
• Understand key statistical techniques for analyzing results and making data-driven decisions.
• Explore best practices for defining meaningful metrics and navigating trade-offs in experimentation.
• Gain actionable insights to optimize product strategies through effective experimentation.

Ashish Jethani is a data scientist with 9 years of experience across various product and consulting companies and currently with working with Meta. He has expertise in machine learning, AI, NLP, deep learning, and big data. Skilled in tools like Python, SQL, R, and C++, he has worked with Hitachi, Bosch, Mu Sigma, and nexquare. At Mu Sigma, he led macro sales analysis, customer lifetime value modeling, and forecasting frameworks. Ashish has also developed big data applications, analytics chatbots, and real-time dashboards to optimize business performance. He holds a B.Tech in Electronics from NIT Karnataka. You can reach him on LinkedIn.