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Didi Tech
Didi Tech
Apr 10, 2025 · Product Management

AA Testing and Rerandomization Techniques for Reliable AB Experiments

The article outlines how AA testing and rerandomization can detect and correct non‑uniform traffic splits in short‑term AB experiments, detailing three solutions—AA tests, seed‑based rerandomization, and retrospective AA analysis—along with theoretical guarantees, empirical error‑rate reductions, and remaining challenges for long‑term or clustered designs.

AA testingAB testingCUPED
0 likes · 17 min read
AA Testing and Rerandomization Techniques for Reliable AB Experiments
DataFunSummit
DataFunSummit
Aug 18, 2024 · Artificial Intelligence

Challenges and Solutions in Recommendation AB Testing on Xiaohongshu's Experiment Platform

The article examines the key challenges of recommendation AB testing at Xiaohongshu—including change stability, single‑experiment precision, and multi‑strategy packaging—and presents a series of engineering and statistical solutions such as SDK‑based AB architecture, virtual PreAA experiments, CUPED/DID adjustments, and reverse experiments to improve reliability and metric impact.

AB testingCUPEDPreAA
0 likes · 15 min read
Challenges and Solutions in Recommendation AB Testing on Xiaohongshu's Experiment Platform
Tencent Advertising Technology
Tencent Advertising Technology
Jul 13, 2021 · Fundamentals

Experiment Design in Two‑Sided Markets – Key Insights from Tencent Advertising Live Session

In a July 8 live broadcast, Tencent Advertising’s strategy algorithm team explained experimental design for two‑sided markets, covering control‑variable selection, CUPED variance reduction, Bayesian smoothing, and bias metrics, and answered participant questions with practical examples and guidance.

Advertising AnalyticsBayesian smoothingCUPED
0 likes · 4 min read
Experiment Design in Two‑Sided Markets – Key Insights from Tencent Advertising Live Session