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Supriya N/A

Supriya N/A

Staff Product Manager

London, United Kingdom

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Staff PM with ~10 years of experience spanning engineering, fintech, ad-tech, and consumer tech — with hands-on technical roots as a software and data engineer at Microsoft
Ran multi-country A/B tests at the scale of tens of millions of users, improving ecosystem health through data-driven product decisions during a critical business transition
Shipped a Gen AI feature covered by TechCrunch that directly improved women's D1 retention — a core north-star metric — by improving match quality at scale

Area of Expertise

  • Business & Management
  • Consumer Goods & Services
  • Transports & Logistics

Topics

  • Product Management
  • Technology Product Management
  • Product Management & AI
  • AI & product management
  • Machine Learning
  • GenAI
  • AI & Machine Learning
  • Artificial Intelligence
  • Recommendation Algorithms
  • Data Analysis
  • Predictive Analytics
  • A/B Testing
  • Large-Scale Experimentation
  • Data Engineering
  • Business Intelligence
  • Microservices
  • Performance Testing Frameworks
  • Automated Functional Testing
  • DevOps
  • Agile Methodologies
  • HTML
  • JavaScript
  • Web Monetization
  • Two-Sided Marketplaces

Why Many A/B Tests Are Lying to You — and What to Do Instead

A/B testing is treated as the gold standard of product decision-making, yet most teams are drawing the wrong conclusions from their experiments. In this talk, Supriya Subudhi draws on a decade of experimentation experience — running multi-country tests at the scale of tens of millions of users across consumer tech and fintech — to expose the most common ways teams misinterpret test results. From peeking problems and novelty effects to metric selection bias and Simpson's paradox, this session will walk through real failure modes and the frameworks that fix them. Attendees will leave with a sharper instinct for when to trust their data — and when to question it.

Supriya N/A

Staff Product Manager

London, United Kingdom

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