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: Benefi ts, 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.

