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Raymond Ops
Raymond Ops
Sep 14, 2025 · Operations

Mastering Concurrency: Optimize Nginx, HAProxy & Keepalived for High‑Performance Servers

This article explains the fundamentals of concurrency, distinguishes connections from requests, shows how to calculate and tune maximum concurrent connections for Nginx and HAProxy, covers system resource limits, demonstrates real‑time monitoring with stub_status, and provides practical load‑testing and Prometheus monitoring guidance.

AB testingHAProxyNginx
0 likes · 15 min read
Mastering Concurrency: Optimize Nginx, HAProxy & Keepalived for High‑Performance Servers
Ctrip Technology
Ctrip Technology
Jul 3, 2025 · Artificial Intelligence

How Ctrip’s Non‑User AB Testing Split Algorithm Boosts Experiment Efficiency

This article presents Ctrip’s novel non‑user AB testing split algorithm that combines optimized random sampling, greedy exchange, and graph‑based community detection to achieve balanced metric distribution, reduce user traffic cross‑over, and dramatically improve split efficiency in real‑world hotel marketing experiments.

AB testinggraph community detectiongreedy optimization
0 likes · 25 min read
How Ctrip’s Non‑User AB Testing Split Algorithm Boosts Experiment Efficiency
Meituan Technology Team
Meituan Technology Team
May 22, 2025 · Fundamentals

Unlocking AB Testing: Core Statistical Principles Behind Reliable Experiments

This article explains the statistical foundations of AB testing, covering the Rubin causal model, SUTVA and randomization assumptions, parameter and confidence‑interval estimation, hypothesis‑testing procedures, and essential limit theorems such as the law of large numbers and the central limit theorem.

AB testingcausal inferencehypothesis testing
0 likes · 17 min read
Unlocking AB Testing: Core Statistical Principles Behind Reliable Experiments
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
JD Retail Technology
JD Retail Technology
Dec 24, 2024 · Industry Insights

How JD Retail Automates AB Experiment Data Pipelines with Data Weaving

This article analyzes JD Retail's approach to automating AB experiment workflows by introducing a data‑weaving framework that unifies metric definitions, streamlines logical data modeling, and enables scalable, real‑time DAG orchestration across multiple experiment scenarios.

AB testingData GovernanceData Platform
0 likes · 21 min read
How JD Retail Automates AB Experiment Data Pipelines with Data Weaving
Didi Tech
Didi Tech
Dec 12, 2024 · Product Management

Key AB Testing Interview Questions and Answers for Data Science Candidates

The article reviews common AB‑testing interview questions for data‑science candidates, explaining the role of p‑values, Type I/II errors, the difference between statistical and business significance, why effects can vanish when scaling, and how to improve experiment sensitivity through larger samples, variance‑reduction methods, and careful metric design.

AB testingInterview PreparationMDE
0 likes · 12 min read
Key AB Testing Interview Questions and Answers for Data Science Candidates
DataFunSummit
DataFunSummit
Dec 1, 2024 · Big Data

Data Weaving for AB Experiment Automation: Architecture, Challenges, and Solutions

This article presents a comprehensive overview of JD Retail's data‑weaving approach to AB experiment automation, detailing the challenges of consistency, scientific rigor, and timeliness, the logical data platform architecture, key technologies, metric modeling, automated DAG orchestration, current progress, and future directions.

AB testingBig Data
0 likes · 21 min read
Data Weaving for AB Experiment Automation: Architecture, Challenges, and Solutions
Tencent Cloud Developer
Tencent Cloud Developer
Nov 27, 2024 · Artificial Intelligence

Tencent Cloud AI Code Assistant: Product Evolution, Architecture, and Technical Implementation

Tencent Cloud AI Code Assistant has evolved from token‑level IDE completions to LLM‑driven multi‑modal coding and chat features, employing a dual‑loop R&D system, Hunyuan‑based code models, and sophisticated trigger, prompt, stop, and display strategies to deliver context‑aware, secure, and efficient code generation within IDE and review environments.

AB testingAI code assistantAST analysis
0 likes · 15 min read
Tencent Cloud AI Code Assistant: Product Evolution, Architecture, and Technical Implementation
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 testingCUPEDExperiment Platform
0 likes · 15 min read
Challenges and Solutions in Recommendation AB Testing on Xiaohongshu's Experiment Platform
DataFunTalk
DataFunTalk
Aug 7, 2024 · Artificial Intelligence

Multi-Scenario Modeling for NetEase Cloud Music Recommendation: Architecture, Challenges, and Results

This article presents NetEase Cloud Music's multi‑scenario recommendation modeling work, detailing background, overall system architecture, key modules, modeling goals, technical difficulties, performance improvements, future outlook, and a comprehensive Q&A session that addresses practical deployment challenges.

AB testingAIModel architecture
0 likes · 14 min read
Multi-Scenario Modeling for NetEase Cloud Music Recommendation: Architecture, Challenges, and Results
DataFunSummit
DataFunSummit
Jul 5, 2024 · Artificial Intelligence

Building and Applying a User Profile Tagging System: Practices and Insights

This article presents a comprehensive overview of constructing and deploying a user and item profiling tag system at Qunar, covering tag taxonomy, integration challenges, technical architectures, algorithmic methods such as classification, recommendation, knowledge‑graph and causal inference, as well as real‑time streaming, ID‑mapping, and practical applications in marketing, attribution and A/B testing.

AB testingTagging Systemdata engineering
0 likes · 21 min read
Building and Applying a User Profile Tagging System: Practices and Insights
Huolala Tech
Huolala Tech
Jul 4, 2024 · Big Data

How Huolala Built a High‑Impact Metric Library to Power Data‑Driven Decisions

Huolala’s data team created a comprehensive metric library platform that centralizes metric definitions, classifications, data, and analysis, enabling data‑driven decision‑making, operational efficiency, service optimization, and strategic business growth across its freight services.

AB testingBusiness AnalyticsData Platform
0 likes · 11 min read
How Huolala Built a High‑Impact Metric Library to Power Data‑Driven Decisions
DataFunSummit
DataFunSummit
Jun 2, 2024 · Artificial Intelligence

Construction and Application of a User Profile Tag System: Methods, Platforms, and Use Cases

This article presents a comprehensive overview of building a user profile tag system—including tag taxonomy, platform architecture, construction methods, update cycles, access patterns, common algorithmic tags, and real‑world applications such as marketing, metric attribution, and A/B testing—illustrated with examples and a detailed Q&A session from a data‑mining senior manager at Qunar.

AB testingcausal inferencedata mining
0 likes · 21 min read
Construction and Application of a User Profile Tag System: Methods, Platforms, and Use Cases
Bilibili Tech
Bilibili Tech
May 21, 2024 · Frontend Development

Bilibili Offline Package Solution for Accelerating H5 Page Load Speed

Bilibili's offline package solution accelerates H5 page load by pre‑downloading resources, intercepting WebView requests, offering snapshot, AB testing, QR‑code debugging, version control, and off‑peak releases; deployed across many projects, it cuts load times by roughly 20‑30% and improves first‑contentful‑paint.

AB testingH5 performanceMobile Frontend
0 likes · 35 min read
Bilibili Offline Package Solution for Accelerating H5 Page Load Speed
ByteDance Data Platform
ByteDance Data Platform
May 15, 2024 · R&D Management

How ByteDance Embeds A/B Testing into Every Stage of Product Development

This article explains how ByteDance integrates data‑driven A/B testing throughout its R&D workflow—from feature design and large‑scale refactoring to bug fixes, release safety, SQL optimization, and cultural adoption—demonstrating the ROI and sustainable practices of a data‑centric development culture.

AB testingData-drivenProduct Development
0 likes · 18 min read
How ByteDance Embeds A/B Testing into Every Stage of Product Development
DataFunSummit
DataFunSummit
May 7, 2024 · Artificial Intelligence

Regional Heterogeneity in Game AB Experiments: Detection, Decomposition, and Prediction

This article examines how game AB experiments can exhibit significant regional differences, outlines a meta‑analysis framework to detect heterogeneity, decomposes its sources into treatment‑effect and distributional factors, and demonstrates how to predict outcomes for unseen regions using machine‑learning models.

AB testingCATEcausal inference
0 likes · 11 min read
Regional Heterogeneity in Game AB Experiments: Detection, Decomposition, and Prediction
DataFunTalk
DataFunTalk
Mar 6, 2024 · Artificial Intelligence

Construction and Practical Application of a User Profile Tagging System

This article details the design, integration, and operational practices of a comprehensive user and item profiling tag system, covering tag taxonomy, construction methods, update cycles, access strategies, algorithmic implementations, and real‑world applications such as marketing, attribution analysis, and A/B testing.

AB testingTagging Systemdata mining
0 likes · 20 min read
Construction and Practical Application of a User Profile Tagging System
Huolala Tech
Huolala Tech
Feb 27, 2024 · Fundamentals

How Offline Spatiotemporal Splitting Eliminates Bias in AB Experiments

This article explains the limitations of conventional A/B testing in freight two‑sided markets, introduces offline spatiotemporal splitting to isolate treatment and control groups, discusses the bias‑variance trade‑off, and provides a step‑by‑step design process with practical risk considerations.

AB testingbias‑varianceexperiment design
0 likes · 11 min read
How Offline Spatiotemporal Splitting Eliminates Bias in AB Experiments
Test Development Learning Exchange
Test Development Learning Exchange
Feb 2, 2024 · Product Management

Understanding AB Testing: Risks, Benefits, and Best Practices

AB testing is a statistical method for comparing multiple strategies or versions to determine the most effective one, and this article explains its risks, mitigation measures, advantages, key dimensions, step‑by‑step workflow, fairness considerations, data‑cleaning techniques, target goals, design guidelines, and alternative experimental approaches.

AB testingconversion rateexperiment design
0 likes · 9 min read
Understanding AB Testing: Risks, Benefits, and Best Practices
Huolala Tech
Huolala Tech
Feb 2, 2024 · Fundamentals

How the Delta Method Improves AB Test Variance Estimation When Units Differ

This article explains why traditional hypothesis‑testing methods can mis‑estimate variance when the splitting unit and analysis unit differ in AB experiments, introduces the Delta Method as an unbiased variance estimator, compares it with Bootstrap and other corrections through simulations and real‑world case studies, and highlights its computational efficiency.

AB testingBootstrapDelta Method
0 likes · 8 min read
How the Delta Method Improves AB Test Variance Estimation When Units Differ
NetEase Cloud Music Tech Team
NetEase Cloud Music Tech Team
Jan 31, 2024 · Mobile Development

How NetEase Cloud Music Achieved Seamless RN Upgrades with a Dual‑Dynamic‑Library Gray Release

This article details NetEase Cloud Music's engineering solution for gradually upgrading its iOS React Native version using a dual dynamic‑library gray‑release strategy, covering background, challenges, symbol handling, code modifications, and practical issues to enable zero‑impact, data‑driven rollouts.

AB testingReact NativeSymbol Binding
0 likes · 14 min read
How NetEase Cloud Music Achieved Seamless RN Upgrades with a Dual‑Dynamic‑Library Gray Release
Huolala Tech
Huolala Tech
Jan 26, 2024 · Operations

Can Time‑Slice Experiments Skew Your Results? Understanding Capacity Competition and Optimal Design

This article examines how time‑slice (time‑slot) AB experiments can cause capacity competition, analyzes the resulting bias‑variance trade‑off, and provides practical guidelines for selecting slice lengths and rotation methods to ensure reliable quantitative results while preserving qualitative conclusions.

AB testingcapacity competitionexperiment design
0 likes · 12 min read
Can Time‑Slice Experiments Skew Your Results? Understanding Capacity Competition and Optimal Design
Huolala Tech
Huolala Tech
Jan 19, 2024 · Operations

How to Eliminate Pre‑Experiment Bias and Find the Optimal AB Test Grouping

This article explains how pre‑experiment bias can distort AB test results and introduces a suite of techniques—including AA retrospective analysis, SeedFinder optimal random grouping, variance reduction, and an offline splitting algorithm—to create homogeneous test groups and improve experiment reliability.

AB testingoffline splittingpre-experiment bias
0 likes · 9 min read
How to Eliminate Pre‑Experiment Bias and Find the Optimal AB Test Grouping
Huolala Tech
Huolala Tech
Jan 5, 2024 · Fundamentals

Unlocking Causal Inference: Practical AB Testing and Observational Study Techniques

This article explains how the Huolala data‑science team tackles AB‑testing challenges, pre‑experiment differences, observational (non‑AB) studies, and advanced causal‑inference methods such as CACE, heterogeneous treatment effects, mediation modeling, regression discontinuity, and instrumental variables to derive reliable business insights.

AB testingcausal inferenceheterogeneous treatment effect
0 likes · 11 min read
Unlocking Causal Inference: Practical AB Testing and Observational Study Techniques
Meituan Technology Team
Meituan Technology Team
Jan 4, 2024 · Backend Development

Top 10 Meituan Technical Articles of 2023 – Summaries and Links

The 2023 Meituan Technical roundup highlights the ten most‑read articles, ranging from the evolution of its code‑hosting platform and automatic SDK generation to risk‑visualization, trace‑ID recovery, trustworthy A/B testing, KDD research, UI intent detection, MJDK compression gains, large‑scale database high‑availability, and interactive food‑delivery recommendation, each with brief summaries and links.

AB testingArtificial IntelligenceMeituan
0 likes · 10 min read
Top 10 Meituan Technical Articles of 2023 – Summaries and Links
DaTaobao Tech
DaTaobao Tech
Dec 22, 2023 · Big Data

AB Incremental Evaluation and Contamination Mitigation in Social Viral Experiments

The paper defines AB increment, shows how to calculate DAU gains from per‑user visit rates, explains how social viral experiments introduce unidirectional or bidirectional contamination that biases increment estimates, and proposes four probability‑estimation schemes—exponential smoothing, expansion coefficients, and homogeneous‑group sampling—to correct the bias based on experiment design and business context.

AB testingExperiment Evaluationcontamination
0 likes · 10 min read
AB Incremental Evaluation and Contamination Mitigation in Social Viral Experiments
Data Thinking Notes
Data Thinking Notes
Dec 21, 2023 · Product Management

Mastering Growth Metrics: Methodologies, Frameworks, and Real‑World Cases

This article explains Douyin’s growth‑analysis methodology, how to construct a comprehensive growth‑metric system with North‑Star indicators and hierarchical metric layers, the end‑to‑end analysis loop, new scenario‑driven metric applications, and a detailed case study on improving video‑submission rates.

AB testingGrowthMetrics
0 likes · 24 min read
Mastering Growth Metrics: Methodologies, Frameworks, and Real‑World Cases
DataFunSummit
DataFunSummit
Dec 20, 2023 · Artificial Intelligence

Building and Applying an Image Tagging System: Architecture, Tag Design, Algorithms, and Business Use Cases

This presentation by senior data mining manager Zhou Yuanwei of Qunar outlines the architecture of an image tagging platform, the construction of a comprehensive tagging system, common algorithmic tags, and real-world applications such as look‑alike marketing, A/B test efficiency analysis, and business attribution, helping audiences understand tag types, design considerations, and value‑driven use cases.

AB testingBusiness Analyticsdata mining
0 likes · 2 min read
Building and Applying an Image Tagging System: Architecture, Tag Design, Algorithms, and Business Use Cases
DataFunTalk
DataFunTalk
Dec 10, 2023 · Operations

Designing Experiments for Peak Surge Pricing in Two‑Sided Markets: Lessons from Uber, Lyft, DoorDash and Didi

This article examines how two‑sided platforms such as Uber, Lyft, DoorDash and Didi design and evaluate peak‑surcharge experiments, addressing network effects, bias‑variance trade‑offs, time‑space slicing, random‑saturation designs, and continuous bandit‑based testing within an operations‑focused experimental system.

AB testingOperationscausal inference
0 likes · 16 min read
Designing Experiments for Peak Surge Pricing in Two‑Sided Markets: Lessons from Uber, Lyft, DoorDash and Didi
DataFunSummit
DataFunSummit
Dec 6, 2023 · Artificial Intelligence

Huya's Experiment Science Platform: Causal Inference, AB Testing, and Uplift Modeling Practices

Huya’s data‑driven experiment platform showcases how causal inference, AB testing, and uplift modeling are applied to advertising, user activation, and growth scenarios, detailing platform evolution, metric design, statistical challenges, and practical solutions such as multi‑test correction, CUPED, RTA, and propensity‑score methods.

AB testingData ScienceExperiment Platform
0 likes · 18 min read
Huya's Experiment Science Platform: Causal Inference, AB Testing, and Uplift Modeling Practices
DataFunSummit
DataFunSummit
Dec 4, 2023 · Product Management

Designing an AB Experiment System for User Growth Scenarios

This article presents a comprehensive AB testing framework tailored for new‑user growth scenarios, detailing the challenges of early traffic allocation, the scientific validation of a new experiment system, real‑world case studies, and practical guidelines for evaluation and implementation.

AB testingMobileexperiment design
0 likes · 14 min read
Designing an AB Experiment System for User Growth Scenarios
Huolala Tech
Huolala Tech
Dec 1, 2023 · Product Management

Tackling AB Testing Pitfalls in Freight Bilateral Markets

This article explores how freight platforms can optimize transaction strategies through AB experiments, detailing common challenges such as split‑testing interference, SUTVA violations, capacity competition, homogeneity issues, and Simpson's paradox, and presents practical solutions like time‑slice routing, city isolation, and advanced statistical corrections.

AB testingData Sciencebilateral market
0 likes · 14 min read
Tackling AB Testing Pitfalls in Freight Bilateral Markets
Huolala Tech
Huolala Tech
Nov 17, 2023 · Fundamentals

Ensuring Homogeneity in AB Tests: Practical Solutions for Reliable Results

This article explains how to guarantee homogeneity in AB experiments by defining pre‑experiment bias, presenting statistical testing methods, outlining a three‑step workflow for both pre‑ and post‑experiment phases, and sharing real‑world case studies and correction techniques to improve decision‑making reliability.

AA testingAB testingCUPED
0 likes · 9 min read
Ensuring Homogeneity in AB Tests: Practical Solutions for Reliable Results
Huolala Tech
Huolala Tech
Nov 3, 2023 · Operations

How Uber, Lyft, and DoorDash Optimize Surge Pricing with Two‑Sided Market Experiments

This article examines how leading two‑sided platforms such as Uber, Lyft, and DoorDash design and run scientific experiments—ranging from time‑space slice A/B tests to random‑saturation and continuous bandit trials—to accurately measure and improve surge‑pricing strategies despite network‑effect biases.

AB testingexperiment designnetwork effects
0 likes · 14 min read
How Uber, Lyft, and DoorDash Optimize Surge Pricing with Two‑Sided Market Experiments
ByteDance Data Platform
ByteDance Data Platform
Oct 11, 2023 · Backend Development

How Volcano Engine Rebuilt Its Ad‑Testing Platform for Scalability and Reliability

This article explains how Volcano Engine identified the tangled authorization, data‑fetching, and performance problems of its advertising AB‑testing platform and refactored it by splitting services, redesigning the data model with MySQL and ClickHouse, applying DAG scheduling, time‑wheel algorithms, Domain‑Driven Design, and rigorous unit testing to achieve a more stable, extensible backend solution.

AB testingAdvertisingBackend
0 likes · 16 min read
How Volcano Engine Rebuilt Its Ad‑Testing Platform for Scalability and Reliability
DataFunTalk
DataFunTalk
Sep 27, 2023 · Product Management

Building an AB Experiment System for User Growth Scenarios

This article presents a comprehensive AB testing framework tailored for new‑user growth scenarios, detailing the challenges of early traffic splitting, the design of a scientifically validated experiment system, ID selection criteria, and real‑world case studies that demonstrate improved retention and device activation.

AB testingdata analysismobile apps
0 likes · 12 min read
Building an AB Experiment System for User Growth Scenarios
Volcano Engine Developer Services
Volcano Engine Developer Services
Sep 25, 2023 · Operations

How Player-Level Tweaks Can Slash Video On-Demand Costs by Up to 20%

This article explains how video on‑demand cost is dominated by CDN bandwidth, how player‑side optimizations—such as reducing cache waste, using dynamic buffering levels, smarter range requests, precise preloading, and resolution adjustments—can cut bandwidth by 8% and overall costs by 20% while preserving user experience.

AB testingCDNCost Optimization
0 likes · 17 min read
How Player-Level Tweaks Can Slash Video On-Demand Costs by Up to 20%
DataFunSummit
DataFunSummit
Sep 21, 2023 · Product Management

Avoiding Deceptive Conclusions in LinkedIn Advertising AB Tests and the Budget‑Splitting Method

This article explains how LinkedIn’s advertising teams prevent misleading AB‑test results, describes the challenges of large‑scale ad experiments such as cannibalization, reviews industry solutions, and introduces their innovative budget‑splitting experiment that dramatically improves statistical power.

AB testingAdvertisingLinkedIn
0 likes · 15 min read
Avoiding Deceptive Conclusions in LinkedIn Advertising AB Tests and the Budget‑Splitting Method
DataFunSummit
DataFunSummit
Aug 31, 2023 · Product Management

Internet Growth Analysis: Strategic & Product-Level Metrics, Marginal ROI, and Advertising Market Dynamics under Cost‑Reduction

This article explains how internet growth analysis combines strategic and product‑level metrics, introduces core profit formulas, critiques traditional ROI calculations, demonstrates the advantages of marginal ROI based on AB experiments, and discusses the implications for advertisers and platforms in a cost‑reduction environment.

AB testingROIgrowth analysis
0 likes · 12 min read
Internet Growth Analysis: Strategic & Product-Level Metrics, Marginal ROI, and Advertising Market Dynamics under Cost‑Reduction
JD Cloud Developers
JD Cloud Developers
Aug 22, 2023 · Artificial Intelligence

A Practical Guide to Recommendation System Architecture and Methods

This article provides a concise overview of recommendation systems, covering their definition, core framework of recall, ranking, and re‑ranking, various recall strategies including multi‑path and vector‑based methods, similarity calculations, and practical implementation details such as AB testing and code examples.

AB testingVector Embeddinginformation retrieval
0 likes · 14 min read
A Practical Guide to Recommendation System Architecture and Methods
vivo Internet Technology
vivo Internet Technology
Aug 2, 2023 · Game Development

Pre‑Experiment User Stratification Model for Improving AB Test Uniformity in Vivo Game Center

The paper introduces a pre‑user stratification model that uses covariate‑balancing algorithms to create separate strata for distribution and revenue metrics, ensuring equal user allocation in Vivo game‑center AB tests, which reduces metric variance, improves gray‑release effectiveness, and saves significant investigation effort.

AB testingGame AnalyticsSampling
0 likes · 14 min read
Pre‑Experiment User Stratification Model for Improving AB Test Uniformity in Vivo Game Center
Xiaohongshu Tech REDtech
Xiaohongshu Tech REDtech
Jul 26, 2023 · Industry Insights

Human‑Perception‑Based End‑Cloud Super‑Resolution: Cutting Bandwidth, Boosting Quality

The LiveVideoStackCon 2023 session revealed how a human‑perception‑driven end‑cloud super‑resolution framework, AI‑based no‑reference video quality assessment, and rigorous AB‑testing methods can dramatically reduce video bandwidth while enhancing visual quality, illustrating the broader challenges and opportunities in modern audio‑video systems.

AB testingAI assessmentaudio-video industry
0 likes · 13 min read
Human‑Perception‑Based End‑Cloud Super‑Resolution: Cutting Bandwidth, Boosting Quality
Bilibili Tech
Bilibili Tech
Jul 25, 2023 · Artificial Intelligence

Bilibili Game Center Recommendation System: Architecture, Core Technologies, and Experimental Results

The Bilibili Game Center recommendation system combines a unified feature platform, multi‑stage recall, ranking and re‑ranking models, online services, and AB experimentation to deliver personalized game suggestions, resulting in up to 78% higher click‑through, 76% higher conversion, and substantial increases in user engagement and revenue.

AB testingfeature engineeringgame-platform
0 likes · 26 min read
Bilibili Game Center Recommendation System: Architecture, Core Technologies, and Experimental Results
DataFunTalk
DataFunTalk
Jul 23, 2023 · Backend Development

Rearchitecting the Advertising AB Testing Platform: Service Decomposition, Data Modeling, DAG Scheduling, and DDD Practices

The article describes how Volcano Engine's DataTester team refactored the advertising AB testing platform by splitting services, redesigning the data model with MySQL and ClickHouse, introducing DAG‑based scheduling and a time‑wheel algorithm, and applying domain‑driven design and rigorous unit testing to improve stability, scalability, and maintainability.

AB testingDAG schedulingDomain-Driven Design
0 likes · 16 min read
Rearchitecting the Advertising AB Testing Platform: Service Decomposition, Data Modeling, DAG Scheduling, and DDD Practices
Baidu App Technology
Baidu App Technology
Jul 10, 2023 · Mobile Development

Baidu App iOS Package Size Optimization: Code Optimization Techniques

The article explains how Baidu App reduces its iOS package size by analyzing Link Map files and applying six code‑optimization techniques—unused class and module slimming, unused method pruning with LLVM, duplicate‑code detection, utility‑method consolidation, and A/B‑test hardening—yielding up to 8 MB of savings.

AB testingLink MapMach-O
0 likes · 15 min read
Baidu App iOS Package Size Optimization: Code Optimization Techniques
IT Services Circle
IT Services Circle
Jul 7, 2023 · Operations

Implementing Gray Release with Nginx, Docker, and NestJS

This guide explains how to set up a gray‑release (canary) deployment using Nginx as a reverse‑proxy gateway, Docker containers for isolation, and two versions of a NestJS service, with traffic split controlled by cookies and configurable percentages.

AB testingNginxOperations
0 likes · 8 min read
Implementing Gray Release with Nginx, Docker, and NestJS
DataFunSummit
DataFunSummit
Jul 2, 2023 · Big Data

Building a One‑Stop AB Testing Platform at NetEase Cloud Music: Architecture, Metric Infrastructure, Scientific Evaluation, and Efficiency

The article describes how NetEase Cloud Music designed and deployed a comprehensive AB testing platform, covering system infrastructure, metric modeling, scientific experiment validation (including SRM mitigation and statistical power), and operational efficiency improvements to support rapid product iteration across multiple devices.

AB testingBig DataData Infrastructure
0 likes · 13 min read
Building a One‑Stop AB Testing Platform at NetEase Cloud Music: Architecture, Metric Infrastructure, Scientific Evaluation, and Efficiency
DataFunTalk
DataFunTalk
Apr 28, 2023 · Artificial Intelligence

Causal Inference and Uplift Modeling for Insurance Recommendation and Explainability

This article explains how uplift sensitivity prediction, Bayesian causal networks, and decision‑path construction are applied to improve insurance product, coupon, and copy recommendations on the Fliggy platform, detailing modeling approaches, evaluation metrics, and practical outcomes of the causal inference framework.

AB testingBayesian networksInsurance Recommendation
0 likes · 16 min read
Causal Inference and Uplift Modeling for Insurance Recommendation and Explainability
DeWu Technology
DeWu Technology
Feb 21, 2023 · Backend Development

Design and Implementation of a Traffic Control Platform for E-commerce Search and Recommendation

The article describes a modular traffic‑control platform for e‑commerce search and recommendation that lets operators quickly adjust strategies for emergencies, cold‑start items, and experiments, replacing costly multi‑team development with a unified operation center, service center, data hub, algorithmic PID controller, real‑time metrics, independent recall chain, and cross‑scene AB testing, while outlining future extensions.

AB testingPID controllerplatform architecture
0 likes · 16 min read
Design and Implementation of a Traffic Control Platform for E-commerce Search and Recommendation
Spring Full-Stack Practical Cases
Spring Full-Stack Practical Cases
Feb 20, 2023 · Cloud Native

Mastering Gray Release with Spring Cloud Gateway: A Step‑by‑Step Guide

This article explains gray (canary) release concepts, compares canary, A/B testing, and blue‑green strategies, and provides a complete Spring Cloud Gateway implementation—including custom load balancer, global filter, and configuration—so you can smoothly roll out new features while preserving system stability.

AB testingCloud Nativecanary deployment
0 likes · 13 min read
Mastering Gray Release with Spring Cloud Gateway: A Step‑by‑Step Guide
DataFunSummit
DataFunSummit
Jan 30, 2023 · Fundamentals

Understanding AB Testing: Design, Execution, and Analysis

This article explains the purpose, methodology, and practical examples of AB testing, describing how randomized traffic segmentation, logging, and metric analysis enable data‑driven product decisions across various industries while also noting its widespread adoption and promotional resources.

AB testingData-drivenexperiment design
0 likes · 7 min read
Understanding AB Testing: Design, Execution, and Analysis
DaTaobao Tech
DaTaobao Tech
Jan 13, 2023 · Artificial Intelligence

Improving Low-Response AB Experiments via Propensity Score Matching and Instrumental Variable Methods

The paper tackles low-response A/B tests by applying instrumental-variable techniques and optimized propensity-score matching, showing that IV methods recover treatment effects for compliant users and that a refined PSM pipeline dramatically boosts lift detection, turning previously non-significant results into statistically significant business insights.

AB testingPropensity Score Matchingcausal inference
0 likes · 20 min read
Improving Low-Response AB Experiments via Propensity Score Matching and Instrumental Variable Methods
DataFunTalk
DataFunTalk
Dec 4, 2022 · Artificial Intelligence

Key Insights on Causal Inference: Motivation, Applications, Challenges, and Links to A/B Testing, ML, and Deep Learning

This article summarizes the motivations behind causal inference, its typical business applications such as intelligent decision‑making and prediction, the practical challenges of validation and data, and its relationship with A/B testing, machine learning, and deep learning, providing a concise overview for newcomers.

AB testingBusiness AnalyticsDeep Learning
0 likes · 10 min read
Key Insights on Causal Inference: Motivation, Applications, Challenges, and Links to A/B Testing, ML, and Deep Learning
网易UEDC
网易UEDC
Nov 15, 2022 · Product Management

How NetEase Payment Found Its Niche: From Risky Game Trades to Targeted User Journeys

This article analyzes how NetEase Payment identified its product positioning in the gaming market by addressing virtual asset trade risks, high‑value transaction challenges, and unsuitable mainstream payment platforms, then outlines a data‑driven user journey with segmentation, targeted incentives, AB testing, and iterative refinements to boost adoption.

AB testingUser Segmentationgaming payments
0 likes · 8 min read
How NetEase Payment Found Its Niche: From Risky Game Trades to Targeted User Journeys
vivo Internet Technology
vivo Internet Technology
Oct 13, 2022 · Cloud Native

Vivo Platformization: Overview of Platform Products and Case Studies

Vivo’s platformization strategy consolidates shared capabilities—such as content review, AB testing, version release, cloud services, points, and account systems—into reusable, standards‑driven platforms that accelerate development, improve safety and user experience, and illustrate how the company tackles complexity and rapid business iteration.

AB testingCloud Servicescontent moderation
0 likes · 16 min read
Vivo Platformization: Overview of Platform Products and Case Studies
ByteFE
ByteFE
Sep 9, 2022 · Frontend Development

Curated Technical Articles: A/B Testing Sample Size, React Alternatives, TypeScript Incremental Compilation, JavaScript new Function, Front‑End Quality Tips, Browser‑Extension Development, Online Code Editors

This collection highlights recent technical articles covering A/B testing sample‑size calculation, the diminishing relevance of React, TypeScript incremental compilation, the JavaScript new Function construct, practical front‑end quality improvements, a step‑by‑step guide to building a browser image‑scraping extension, and a roundup of useful online code editors.

AB testingbrowser extension
0 likes · 6 min read
Curated Technical Articles: A/B Testing Sample Size, React Alternatives, TypeScript Incremental Compilation, JavaScript new Function, Front‑End Quality Tips, Browser‑Extension Development, Online Code Editors
DataFunTalk
DataFunTalk
Aug 21, 2022 · Artificial Intelligence

User Interest Segmentation and Clustering: Data Science Practices at iQIYI

The article presents iQIYI's data‑science‑driven approach to user interest segmentation, covering the design of weighted interest tags, their validation through blind surveys and AB‑tests, the creation of factual behavior tags, and advanced content‑based clustering methods for more precise audience targeting.

AB testingUser Segmentationcontent recommendation
0 likes · 10 min read
User Interest Segmentation and Clustering: Data Science Practices at iQIYI
ByteDance Data Platform
ByteDance Data Platform
Aug 19, 2022 · Product Management

How ByteDance Boosted New User Retention with Incentives and AB Testing

This article reviews ByteDance's practical growth case where the new video recommendation product “M” used a data‑driven incentive system and extensive AB testing to improve first‑week user retention, outlining the design, implementation steps, and methods for identifying core product functions.

AB testingGrowth HackingIncentive Design
0 likes · 9 min read
How ByteDance Boosted New User Retention with Incentives and AB Testing
Python Crawling & Data Mining
Python Crawling & Data Mining
Aug 14, 2022 · Product Management

Unlocking Growth: How AB Testing Validates Causality and Measures Impact

This article explains AB testing—from its biomedical origins and online adoption to its types, three essential components, core values of causal validation and quantitative growth, and key characteristics of pre‑evaluation and parallelism—providing a comprehensive guide for data‑driven product optimization.

AB testingcausal inferencedata-driven growth
0 likes · 25 min read
Unlocking Growth: How AB Testing Validates Causality and Measures Impact
Baidu MEUX
Baidu MEUX
Jul 22, 2022 · Frontend Development

How Responsive Grid Design Boosted User Engagement on a Short‑Video Platform

This case study details how Haokan Video’s PC site was transformed with a responsive 24‑column grid, streamlined navigation, visual‑noise reduction, and feed‑style content loading, resulting in higher content exposure, improved click‑through rates, and stable user retention after a month‑long AB test.

AB testingResponsive DesignUI/UX
0 likes · 9 min read
How Responsive Grid Design Boosted User Engagement on a Short‑Video Platform
NetEase LeiHuo UX Big Data Technology
NetEase LeiHuo UX Big Data Technology
Jul 20, 2022 · Game Development

Correlation vs Causation in Game Design: How to Avoid Misleading Data Interpretations

The article explains how spurious correlations can mislead game designers and product managers, illustrates the difference between correlation and causation with real‑world examples, and offers practical methods such as focusing on passive variables, ensuring hard stratification, and using behavior‑chain matching to draw more reliable conclusions.

AB testingUser Segmentationcausation
0 likes · 9 min read
Correlation vs Causation in Game Design: How to Avoid Misleading Data Interpretations
Xingsheng Youxuan Technology Community
Xingsheng Youxuan Technology Community
Jun 17, 2022 · Frontend Development

How Prism Transformed Front‑End Monitoring at Scale: Architecture, Challenges & Insights

This article details the design, challenges, and solutions behind Prism, a self‑built front‑end monitoring platform that collects multi‑device SDK data, processes it through Kafka, Flink and ClickHouse, visualizes metrics, integrates with A/B testing, and outlines future enhancements for broader enterprise adoption.

AB testingfrontendmonitoring
0 likes · 14 min read
How Prism Transformed Front‑End Monitoring at Scale: Architecture, Challenges & Insights
Zhuanzhuan Tech
Zhuanzhuan Tech
Mar 2, 2022 · Backend Development

Iterative Development and Scaling of ZuanZuan's Push Notification System

This article details the end‑to‑end evolution of ZuanZuan's push notification platform, covering terminology, architecture, large‑scale holiday pushes, real‑time data handling, performance optimizations, multi‑channel integration, AB testing, and monitoring to achieve high throughput and reliability.

AB testingDistributed Systemsbackend scaling
0 likes · 10 min read
Iterative Development and Scaling of ZuanZuan's Push Notification System
Baobao Algorithm Notes
Baobao Algorithm Notes
Feb 15, 2022 · Industry Insights

Why Your Algorithm Gains May Still Drag Down Overall Business: 6 Hidden Pitfalls

Even when individual algorithm modules show higher accuracy or revenue, the overall platform can decline due to factors like competitor encroachment, macro‑economic shifts, concept drift, overlapping marginal returns, attribution errors, and coupled A/B experiments, all of which require careful analysis and mitigation.

AB testingMetricsalgorithm
0 likes · 7 min read
Why Your Algorithm Gains May Still Drag Down Overall Business: 6 Hidden Pitfalls
DataFunSummit
DataFunSummit
Feb 5, 2022 · Artificial Intelligence

Causal Analysis: Challenges, Methodology, and Practice at Beike

This article introduces causal analysis, outlines its major challenges such as correlation versus causation, confounding factors, and selection bias, explains a three‑step framework (association, intervention, counterfactual), and details how Beike applied these principles in a smart client‑management tool with rigorous A/B experiments.

AB testingAIBeike
0 likes · 14 min read
Causal Analysis: Challenges, Methodology, and Practice at Beike
IT Architects Alliance
IT Architects Alliance
Feb 4, 2022 · Backend Development

How Our Recommendation Engine Evolved from V1.0 to V3.0

This article details the three‑stage evolution of an e‑commerce recommendation framework—V1.0’s simple strategy‑factory design, V2.0’s vertical business split, and V3.0’s configurable pipeline with dynamic server‑client configuration, addressing scalability, isolation, and AB‑testing challenges.

AB testingBackend ArchitectureMicroservices
0 likes · 14 min read
How Our Recommendation Engine Evolved from V1.0 to V3.0
JD.com Experience Design Center
JD.com Experience Design Center
Dec 20, 2021 · Frontend Development

Boosting JD’s 11.11 Home Appliance Sales with Immersive Design and Front‑End Optimization

This case study details JD.com's 11.11 home‑appliance campaign, covering project background, brand goals, consumer‑centric design thinking, visual creativity with interactive scenes, front‑end performance optimizations, AB‑testing results, and insights on turning design into measurable commercial value.

AB testinge‑commercefrontend
0 likes · 12 min read
Boosting JD’s 11.11 Home Appliance Sales with Immersive Design and Front‑End Optimization
Alimama Tech
Alimama Tech
Dec 1, 2021 · Industry Insights

How to Measure Brand Impact: Audience Reach, Coverage Models, and Causal Testing

This article presents a comprehensive framework for evaluating brand effectiveness by measuring audience communication ability, applying target‑audience coverage and incremental coverage models, assessing brand awareness through online behavior and surveys, and using AB testing and propensity‑score matching to derive causal insights.

AB testingPropensity Score Matchingaudience reach
0 likes · 13 min read
How to Measure Brand Impact: Audience Reach, Coverage Models, and Causal Testing
Sohu Tech Products
Sohu Tech Products
Nov 24, 2021 · Frontend Development

Modularization Practices in Vivo Game Center: Componentization, Configuration, and Experimentation

This article explains how Vivo Game Center adopted a modular architecture—combining componentization, configuration, and experiment-driven deployment—to enable rapid, flexible UI layout adjustments, unified backend processes, and data-driven A/B testing, thereby improving development efficiency and user‑targeted operations.

AB testingBackendSoftware Architecture
0 likes · 17 min read
Modularization Practices in Vivo Game Center: Componentization, Configuration, and Experimentation
vivo Internet Technology
vivo Internet Technology
Nov 10, 2021 · Game Development

Modularization Practices in Vivo Game Center: Componentization, Configuration, and Experimentation

To meet rapid growth and diverse user needs, Vivo’s Game Center adopted a modular architecture that separates visual templates from data, enabling reusable UI components, configurable page assembly, and AB‑test driven experimentation, which together cut release cycles, streamline backend workflows, and boost scalability and developer productivity.

AB testingComponent-Based Architecturebackend configuration
0 likes · 17 min read
Modularization Practices in Vivo Game Center: Componentization, Configuration, and Experimentation
Alimama Tech
Alimama Tech
Nov 3, 2021 · Product Management

Common Pitfalls in AB Testing: Design and Analysis Issues

AB testing often fails because practitioners skip power analysis, peek at interim results, set unrealistic null hypotheses, randomize at inappropriate units, ignore sample‑ratio mismatches, choose misleading metrics, and fall prey to segmentation errors like Simpson’s paradox, any of which can invalidate conclusions.

AB testingMetricsSample Ratio Mismatch
0 likes · 15 min read
Common Pitfalls in AB Testing: Design and Analysis Issues
58UXD
58UXD
Oct 29, 2021 · Operations

How the CST Model Boosts User Conversion: A Design Case Study

This article examines how applying the CST design model, user segmentation, and psychological principles such as mental accounting and social proof can significantly improve conversion rates for a savings membership product.

AB testingCST modelOperations
0 likes · 7 min read
How the CST Model Boosts User Conversion: A Design Case Study
Alimama Tech
Alimama Tech
Oct 20, 2021 · Big Data

Designing Evaluation Metrics and Building an Overall Evaluation Index (OEC) for AB Testing

The article explains how to design experiment evaluation metrics—from top‑down objectives to core, quality, and observation types—and construct an Overall Evaluation Criterion by processing, weighting, and aggregating metrics, providing a robust, scalable framework for credible AB‑test assessment and product optimization.

AB testingAnalyticsData Science
0 likes · 11 min read
Designing Evaluation Metrics and Building an Overall Evaluation Index (OEC) for AB Testing
Alimama Tech
Alimama Tech
Oct 13, 2021 · Artificial Intelligence

Bootstrap Methods for Statistical Inference in AB Testing

The article explains how the non‑parametric Bootstrap resampling method provides a practical, computationally efficient way to perform statistical inference in AB testing—especially with small samples, skewed data, or ratio metrics—by generating confidence intervals and hypothesis tests via repeated sampling, outperforming traditional approaches.

AB testingBootstrapData Science
0 likes · 9 min read
Bootstrap Methods for Statistical Inference in AB Testing
Alibaba Terminal Technology
Alibaba Terminal Technology
Sep 1, 2021 · Mobile Development

Unlocking Faster Mobile UI with Fish-Redux 2.0’s Dynamic FlowAdapter

This article explains how Fish-Redux has been adopted across Xianyu’s core mobile flows, the limitations of its original static and dynamic adapters, and the architectural evolution that led to a unified FlowAdapter delivering dynamic page composition, component reuse, AB testing and improved developer productivity.

AB testingDynamic AdapterFish Redux
0 likes · 10 min read
Unlocking Faster Mobile UI with Fish-Redux 2.0’s Dynamic FlowAdapter
iQIYI Technical Product Team
iQIYI Technical Product Team
Aug 27, 2021 · Backend Development

iQIYI AB Testing Platform: Architecture, Workflow, and Statistical Practices

iQIYI’s AB testing platform integrates a layered traffic‑splitting architecture, real‑time SDK and API delivery, log‑replay data collection, and rigorous T‑test statistical analysis to enable fast, reliable product, algorithm, and operations experiments, exemplified by a UI redesign that boosted watch time by 17.85%.

AB testingExperiment PlatformiQIYI
0 likes · 12 min read
iQIYI AB Testing Platform: Architecture, Workflow, and Statistical Practices
Kuaishou Tech
Kuaishou Tech
Aug 13, 2021 · Industry Insights

How Kuaishou Uses Causal Inference to Optimize Live‑Streaming Experiments

This article analyzes Kuaishou's live‑streaming ecosystem, detailing causal‑inference frameworks, observational and experimental techniques such as DID, double machine learning, causal forests, uplift meta‑learners, and complex experiment designs like dual‑sided and time‑slice rotation to evaluate product and recommendation strategies.

AB testingKuaishoucausal inference
0 likes · 17 min read
How Kuaishou Uses Causal Inference to Optimize Live‑Streaming Experiments
Xianyu Technology
Xianyu Technology
Aug 10, 2021 · Product Management

Design of Full-Traffic AB Experiments for Seller Growth on Xianyu

The article describes a full‑traffic A/B testing framework for Xianyu that hashes seller IDs to create exclusive experiment and control groups, ensuring each seller sees only one strategy, and demonstrates that a chat‑incentive for new or churned sellers boosted chat exposure by 22 % and modestly improved overall buyer‑seller metrics without harming transaction efficiency.

AB testingdata analysisexperiment design
0 likes · 9 min read
Design of Full-Traffic AB Experiments for Seller Growth on Xianyu
DataFunSummit
DataFunSummit
Aug 5, 2021 · Artificial Intelligence

Embedding‑Based Item‑to‑Item Similarity Recommendation for Homestay Platforms

This article describes how Tujia applied embedding techniques, inspired by word2vec and skip‑gram models, to build item‑to‑item similarity vectors for homestay recommendations, detailing the background challenges, the embedding solution, training methodology, evaluation results, practical improvements, and future development plans.

AB testingEmbeddinghomestay
0 likes · 13 min read
Embedding‑Based Item‑to‑Item Similarity Recommendation for Homestay Platforms
DataFunTalk
DataFunTalk
Jul 29, 2021 · Fundamentals

Offline Sampling in AB Testing: Challenges and Experimental Techniques

The article explains offline sampling for AB testing, detailing why it is needed, the main challenges of limited sample size, population heterogeneity, and non‑random interventions, and presents variance‑reduction, stratified sampling, IPW, and matching methods to address these issues.

AB testingcausal inferenceoffline sampling
0 likes · 15 min read
Offline Sampling in AB Testing: Challenges and Experimental Techniques
IT Architects Alliance
IT Architects Alliance
Jul 18, 2021 · Operations

How to Achieve Smooth Releases and AB Testing with Nginx: A Step‑by‑Step Guide

This article details a practical smooth‑release process for a cloud‑office system, explains how to use Nginx health‑check endpoints to take instances offline, and presents three AB‑testing routing strategies—IP‑based, cookie‑based, and AB‑cluster proxy—complete with configuration examples, pros and cons, and deployment steps.

AB testingBlue‑Green deploymentCloud Native
0 likes · 9 min read
How to Achieve Smooth Releases and AB Testing with Nginx: A Step‑by‑Step Guide
DataFunTalk
DataFunTalk
Jul 11, 2021 · Fundamentals

Understanding Online Experiments: Origins, Types, and Applications

This article explains the concept, history, and various forms of online experiments such as AB testing, ABn, AA, and multivariate tests, highlighting their role in causal inference, value evaluation, risk control, and product optimization within modern internet businesses.

AB testingcausal inferenceexperiment design
0 likes · 16 min read
Understanding Online Experiments: Origins, Types, and Applications
Alibaba Cloud Developer
Alibaba Cloud Developer
Jun 21, 2021 · R&D Management

Can Growth‑Hacking Principles Supercharge Software Development Efficiency?

By adapting growth‑hacking concepts such as north‑star metrics, conversion funnels, and A/B testing to the software development lifecycle, this article proposes a data‑driven “efficiency hacker” model that visualizes demand delivery paths, classifies tasks with the RIW framework, and guides teams toward faster, more transparent project outcomes.

AB testingGrowth HackingMetrics
0 likes · 10 min read
Can Growth‑Hacking Principles Supercharge Software Development Efficiency?
58 Tech
58 Tech
Jun 7, 2021 · Artificial Intelligence

AI‑Driven CRM: Intelligent Opportunity Distribution and Sales Voice Assistant at 58.com

This article details how 58.com’s AI Lab applied machine‑learning, recommendation, search, speech and NLP technologies to transform its CRM system into an intelligent opportunity distribution platform and sales voice assistant, describing the underlying models, the "Michigan" workflow, AB‑testing results and future AI‑driven enhancements.

AB testingAICRM
0 likes · 21 min read
AI‑Driven CRM: Intelligent Opportunity Distribution and Sales Voice Assistant at 58.com
iQIYI Technical Product Team
iQIYI Technical Product Team
Mar 19, 2021 · Backend Development

Performance Optimization Practices for iQIYI International Site Backend

The iQIYI International backend team boosted global video delivery by introducing a web‑cache layer, Brotli compression, and a two‑level Caffeine‑Redis caching system with pub/sub synchronization, achieving up to 6% faster First Contentful Paint, near‑100% cache‑hit rates, and measurable revenue gains.

AB testingSSRWeb Performance
0 likes · 19 min read
Performance Optimization Practices for iQIYI International Site Backend
DeWu Technology
DeWu Technology
Feb 26, 2021 · Backend Development

Design and Implementation of an AB Testing Platform with Traffic Allocation Algorithms

The paper presents an AB‑testing platform that structures experiments into scenes, buckets, layers and traffic, uses a salted‑hash based allocation and a two‑step “multi‑withdraw‑fill” algorithm to adjust percentages while preserving user‑experiment stability, and describes a lightweight, cache‑centric system architecture with staggered config reloads and safeguards against database spikes and zombie nodes.

AB testingExperiment PlatformSystem Design
0 likes · 11 min read
Design and Implementation of an AB Testing Platform with Traffic Allocation Algorithms
21CTO
21CTO
Feb 26, 2021 · Artificial Intelligence

Why One Metric Isn't Enough: Multi‑Dimensional Evaluation of Recommendation Systems

The article explains why relying on a single metric like click‑through rate is insufficient for recommendation systems, and outlines a comprehensive, multi‑dimensional evaluation framework that combines business indicators, user behavior metrics, and algorithmic performance measures such as recall, precision, and AUC.

AB testingAIAUC
0 likes · 10 min read
Why One Metric Isn't Enough: Multi‑Dimensional Evaluation of Recommendation Systems
ITFLY8 Architecture Home
ITFLY8 Architecture Home
Feb 23, 2021 · Artificial Intelligence

How Meituan Built a One‑Stop Machine Learning Platform for Delivery Optimization

This article explains how Meituan’s delivery business has transitioned from data online to AI‑driven decision making by building a comprehensive, one‑stop machine learning platform that includes model management, data graph, feature store, AB testing, and a machine‑learning definition language to accelerate algorithm iteration and reduce operational costs.

AB testingAI PlatformDelivery Logistics
0 likes · 5 min read
How Meituan Built a One‑Stop Machine Learning Platform for Delivery Optimization
Xueersi Online School Tech Team
Xueersi Online School Tech Team
Jan 15, 2021 · Artificial Intelligence

Recommendation System Architecture and Engineering Overview

This article presents a comprehensive overview of a recommendation system, covering its business background, purpose, detailed engineering architecture—including data sources, computation, storage, online learning, service and access layers—and discusses key challenges, module design, and practical reflections.

AB testingTensorFlowdata engineering
0 likes · 14 min read
Recommendation System Architecture and Engineering Overview
58UXD
58UXD
Dec 15, 2020 · Product Management

How to Make Operational Design Click with Users: A Step‑by‑Step Case Study

This article breaks down operational design into three key questions—design basis, user connection, and result validation—using real‑world case studies, visual analysis, and AB testing data to show how designers can create evidence‑driven, conversion‑focused experiences.

AB testingUser Researchconversion optimization
0 likes · 10 min read
How to Make Operational Design Click with Users: A Step‑by‑Step Case Study
Tencent Cloud Developer
Tencent Cloud Developer
Dec 4, 2020 · Artificial Intelligence

Building User Interest Tags in WeChat's Recommendation System

The paper presents a WeChat recommendation system that estimates user interest tags via multi‑class classification, using hierarchical intra‑ and inter‑domain attention and dense feature‑crossing to capture diverse preferences, aggregates click‑tag preferences rather than treating all tags equally, and demonstrates superior offline and online performance over baselines such as YouTube‑DNN, AFM, NFM, DCN, and AUTOINT.

AB testingHierarchical Attentionfeature crossing
0 likes · 8 min read
Building User Interest Tags in WeChat's Recommendation System
Liulishuo Tech Team
Liulishuo Tech Team
Oct 26, 2020 · Fundamentals

Causal Inference Methods for Quantifying Product Impact in Data Analytics

This article explains how data analysts can use experimental and observational research methods, including randomized controlled trials, quasi‑experiments, difference‑in‑differences, regression discontinuity, synthetic control, and Bayesian structural time‑series, to assess the causal impact of product and marketing changes on business metrics.

AB testingcausal inferencedifference-in-differences
0 likes · 7 min read
Causal Inference Methods for Quantifying Product Impact in Data Analytics