Resources

Research papers and documents

  • A Causal Test of the Weak Ties

    Karthik Rajkumar et al

  • A Dirty Dozen - Twelve Common Metric Interpretation Pitfalls in Online Controlled Experiments

    Pavel Dmitriev et al.

  • A Note on Type S/M Errors in Hypothesis Testing

    Jiannan Lu et al.

  • A/B Integrations - Seven Lessons Learned from Enabling A/B testing as a Product Feature

    Aleksander Fabijan et al.

  • A/B Testing Intuition Busters

    Kohavi et al.

  • A/B Testing with Fat Tails

    Eduardo Azevado et al.

  • A/B Testing - A Systematic Literature Review

    Federico Quin et al.

  • Always Valid Inference - Continuous Monitoring of A/B Tests

    Ramesh Johari et al.

  • Bayesian A/B Testing for Business Decisions

    Shafi Kamalbasha et al.

  • Building a Culture of Experimentation

    Stefan Thomke

  • Causal Inference in Economics and Marketing

    Hal Varian

  • Concise Summarization of Heterogeneous Treatment Effect Using Total Variation Regularized Regression

    Alex Deng et al.

  • Controlled Experiments on the Web - Survey and Practical Guide

    Ronny Kohavi et al.

  • Data-Driven Metric Development for Online Controlled Experiments - Seven Lessons Learned

    Alex Deng et al.

  • Design and Analysis of Experiments in Networks: Reducing Bias From Interference

    Dean Eckles et al.

  • Design and Analysis of Switchback Experiments

    Iavor Bojinov et al.

  • Designing and Deploying Online Field Experiments

    Etan Backshy et al.

  • Diagnosing Sample Ratio Mismatch in Online Controlled Experiments: A Taxonomy and Rules of Thumb for Practitioners

    Aleksander Fabijan et al.

  • Exact P-values for Network Interference

    Susan Ethay et al.

  • Experimental Design in Two-Sided Platforms - An Analysis of Bias

    Ramesh Johari et al.

  • Experimentation and Startup Performance - Evidence From A/B Testing

    Rembrand Koning et al.

  • Experimentation at Yelp

    Iavor Bojinov et al.

  • False Discovery Rate Controlled Heterogeneous Treatment Effect Detection for Online Controlled Experiments

    Yuxiang Xie et al.

  • From Infrastructure to Culture - A/B Testing Challenges in Large Scale Social Networks

    Ya Xu et al.

  • Harvard Business Review - Iterative Coordination and Innovation

    Sourobh Ghosh et al.

  • Harvard Business Review - The Effects of Hierarchy on Learning and Performance in Business Experimentation

    Sourobh Ghosh et al.

  • How to Build a Growth Team

    Andrew Chen

  • ICE Done Right

    Itamar Gilad

  • Improving the Sensitivity of Online Controlled Experiments - Case Studies at Netflix

    Huizhi Xie et al.

  • Improving the Sensitivity of Online Controlled Experiments by Utilizing Pre-Experiment Data

    Alex Deng et al.

  • Intuit - Field Guide to Rapid Experimentation

    Intuit

  • It Takes a Flywheel to Fly - Kickstarting and Growing the A/B Testing Momentum at Scale

    Aleksander Fabijan et al.

  • Learning Sensitive Combinations of A/B Test Metrics

    Eugene Kharitonov et al.

  • Long-term Causal Inference Under Persistent Confounding via Data Combination

    Guido Imbens et al.

  • Network A/B Testing - From Sampling to Estimation

    Huan Gui et al.

  • Novelty and Primacy - A Long-Term Estimator for Online Experiments

    Soheil Sadeghi et al.

  • On Post-Selection Inference in A/B Testing

    Alex Deng et al.

  • Online Controlled Experiments and A/B Tests

    Ronny Kohavi et al.

  • Online Controlled Experiments at Large Scale

    Ronny Kohavi et al.

  • Online Experimentation at Microsoft

    Ronny Kohavi et al.

  • Online Experimentation - Benefits, Operational and Methodological Challenges, and Scaling Guide

    Iavor Bojinov et al.

  • Online Experiments - Lessons Learned

    Ronny Kohavi et al.

  • Overlapping Experiment Infrastructure - More, Better, Faster Experimentation

    Diane Tang et al.

  • Peeking at A/B Tests

    Ramesh Johari et al.

  • Practical Guide to Controlled Experiments on the Web - Listen to Your Customers Not to The HiPPO

    Ronny Kohavi et al.

  • Quantifying the Value of Iterative Experimentation

    Jialiang Mao et al.

  • Rapid Regression Detection in Software Deployments Through Sequential Testing

    Michael Lindon et al.

  • Safe Velocity - A Practical Guide to Software Deployment at Scale Using Controlled Rollout

    Tong Xia et al.

  • Sequential Estimation of Quantiles With Applications to A/B Testing and Best-Arm Identification

    Steven Howard et al.

  • Seven Pitfalls to Avoid When Running Controlled Experiments on the Web

    Thomas Crook et al.

  • Seven Rules of Thumb for Web Site Experimenters

    Ronny Kohavi et al.

  • Statistical Challenges in Online Controlled Experiments - A Review of A/B Testing Methodology

    Nicholas Larsen et al.

  • Testing Product Ideas Handbook

    Itamar Gilad

  • The Amplitude Guide to Product Metrics

    Amplitude

  • The Anatomy of a Large-Scale Online Experimentation Platform

    Somit Gupta et al.

  • The Comprehensive Guide to Churn

    ProfitWell

  • The Evolution of Continuous Experimentation in Software Product Development

    Aleksander Fabijan et al.

  • The Surprising Power of Online Experiments

    Ronny Kohavi et al.

  • Time Series Experiments and Causal Estimands - Exact Randomization Tests and Trading

    Iavor Bojinov et al.

  • Trustworthy Online Controlled Experiments - Five Puzzling Outcomes Explained

    Ronny Kohavi et al.

  • Trustworthy Online Marketplace Experimentation with Budget-Split Design

    Min Liu et al.

  • Where Are Randomized Trials Necessary - Are Smoking and Parachutes Good Counterexamples?

    Kerrington Powell et al.

  • Your Guide to Scaling Product Led Experimentation

    Amplitude x Reforge

  • Zero to Hero - Exploiting Null Effects to Achieve Variance Reduction in Experiments with One-Sided Triggering

    Alex Dang et al.

  • History of Controlled Experiments

    Ronny Kohavi

  • Intuit Rapid Experimentation Overview

    Bennett Blank

  • Top Challenges From the First Practical Online Controlled Experiments Summit

  • Statistical Challenges in Online Controlled Experiments: A Review of A/B Testing Methodology

    Nicholas Larsen et al.

  • Controlled Experiments on the Web: Survey and Practical Guide

    Ronny Kohavi et al.

  • Controlled Experimentation in Continuous Experimentation: Knowledge and Challenges

    Florian Auer et al.

  • Online Experimentation: Benefits, Operational and Methodological Challenges, and Scaling Guide

    Iavor Bojinov & Somit Gupta

  • Experimentation and Startup Performance: Evidence From A/B Testing

    Rembrand Koning et al.

  • Peeking at A/B Tests: Why it Matters, And What to do About it

    Ramesh Johari et al.

  • AI Playbook For Research, CRO & Experimentation

    Craig Sullivan et al.

  • Online Experiments: Practical Lessons

    Ronny Kohavi et al.

  • 150 Successful Machine Learning Models: 6 Lessons Learned at Booking.com

    Lucas Bernardi et al.

  • Communities of Practice: The Organisational Frontier

    Etienne Wenger and William Snyder

  • Improving the Sensitivity of Online Controlled Experiments: Case Studies at Netflix

    Huizhi Xie et al.

  • Measuring Average Treatment Effect from Heavy-tailed Data

    Jason Wang et al.