business metrics

DataFunSummit

Sep 3, 2024 · Artificial Intelligence

Metric Attribution on Internet Platforms: Concepts, Methods, and Tool Applications

This article explains metric attribution for internet platforms, covering its definition, a three‑step analytical framework, deterministic and probabilistic methods such as metric decomposition, machine‑learning models with SHAP values, case studies, and a practical tool that guides users through attribution analysis.

Internet PlatformsMetric AttributionSHAP

0 likes · 15 min read

Metric Attribution on Internet Platforms: Concepts, Methods, and Tool Applications

Architecture and Beyond

Dec 30, 2023 · Product Management

15 Essential SaaS Business Metrics Every Technical Professional Should Understand

This article explains the origins of SaaS, outlines the Chinese market landscape, and details fifteen crucial business metrics—including acquisition cost, LTV, MRR, ARR, NDR, and retention indicators—while also covering product development stages, GTM strategies, and growth models such as PLG and SLG for SaaS startups.

Growth StrategiesLTVMRR

0 likes · 25 min read

15 Essential SaaS Business Metrics Every Technical Professional Should Understand

Ctrip Technology

Oct 26, 2023 · Artificial Intelligence

Time Series Forecasting of Key Business Indicators: Methods, Models, and Practical Deployment

This article presents a comprehensive study on forecasting critical business metrics such as traffic, order volume, and GMV using traditional, machine‑learning, and deep‑learning time‑series models, detailing feature engineering, model design, experimental comparison, online deployment, and monitoring strategies.

AutoformerInformerProphet

0 likes · 18 min read

Time Series Forecasting of Key Business Indicators: Methods, Models, and Practical Deployment

vivo Internet Technology

Jun 21, 2023 · Game Development

Post‑Darwin Method for Game Business Effect Evaluation Using Stratified Sampling

The paper presents the ‘Post‑Darwin’ evaluation framework, which uses stratified sampling to compare participants and non‑participants across uniform payment layers, overcoming uneven user distributions and the lack of viable A/B tests in game‑business effect analysis, and demonstrates its effectiveness through real‑world promotional and reservation case studies.

business metricsdata analysiseffect evaluation

0 likes · 13 min read

Post‑Darwin Method for Game Business Effect Evaluation Using Stratified Sampling

NetEase Cloud Music Tech Team

Nov 18, 2022 · Artificial Intelligence

Machine Learning-Based Anomaly Detection for Core Business Metrics

The paper proposes a containerized, machine‑learning framework that fuses rule‑based and XGBoost‑driven anomaly detection to monitor daily active users on a cloud music platform, achieving 89 % recall, 81 % precision and up to 74 % recall improvement over traditional threshold methods, while outlining future model refinement and broader metric applicability.

3-sigmaAnomaly DetectionHolt-Winters

0 likes · 11 min read

Machine Learning-Based Anomaly Detection for Core Business Metrics

DevOps

May 5, 2022 · Product Management

Experience Measurement: A Five‑Step Framework for Driving Business Impact

The article presents a five‑step experience measurement methodology that combines operational and perception data to link customer experience with business performance, offering practical guidance on model building, metric decomposition, diagnosis, redesign, continuous monitoring, and long‑term implementation principles.

Digital TransformationROIbusiness metrics

0 likes · 10 min read

Experience Measurement: A Five‑Step Framework for Driving Business Impact

Full-Stack Internet Architecture

Nov 1, 2021 · Fundamentals

Nine Basic Data Analysis Methods for Business Insights

This article introduces nine fundamental data analysis techniques—including periodic, structural, layered, matrix, decomposition, funnel, correlation, tag, and MECE methods—explaining how to apply each to interpret business metrics, uncover insights, and guide decision‑making without requiring advanced mathematics or complex algorithms.

MEMEbasic methodsbusiness metrics

0 likes · 12 min read

Nine Basic Data Analysis Methods for Business Insights

Full-Stack Internet Architecture

Jun 10, 2020 · Operations

Understanding the “Magic Number” in Sales Operations: Common Pitfalls and Correct Approaches

Sales teams often chase arbitrary “magic numbers” like 100 calls or 100 minutes, mistaking correlation for causation; this article explains the original meaning of magic numbers in user retention analysis, highlights statistical errors, and outlines a data‑driven four‑step process to identify true performance drivers and actionable strategies.

business metricscausationdata-driven

0 likes · 9 min read

Understanding the “Magic Number” in Sales Operations: Common Pitfalls and Correct Approaches

Didi Tech

May 15, 2020 · Artificial Intelligence

Key Factors for Effective Data Product Development and Algorithm Engineer Evaluation

Effective data product development hinges on deep business understanding, clear metric decomposition, rigorous model evaluation, and translating technical performance into business impact, while algorithm engineers are best assessed by publication quality, problem significance, algorithmic contribution, and practical interview questions on model tuning and improvement.

Big DataModel Generalizationalgorithm evaluation

0 likes · 10 min read

Key Factors for Effective Data Product Development and Algorithm Engineer Evaluation

58 Tech

Mar 25, 2019 · Artificial Intelligence

Machine Learning‑Based Threshold‑Free Monitoring for Business Metrics

This article describes a monitoring system that leverages machine learning to perform threshold‑free, real‑time anomaly detection on macro business indicators such as network traffic and access volume, detailing its architecture, sample labeling, model training, and multi‑level alarm strategies.

AIAnomaly DetectionMonitoring

0 likes · 7 min read

Machine Learning‑Based Threshold‑Free Monitoring for Business Metrics

58 Tech

Feb 21, 2019 · Artificial Intelligence

Threshold‑Free Business Metric Monitoring Using Machine Learning

This article describes how a machine‑learning‑driven monitoring system replaces fixed thresholds with personalized, anomaly‑based detection for business‑level metrics such as network traffic and access volume, detailing the architecture, sample labeling, model training, alarm grading, and operational benefits.

AI OpsAnomaly Detectionalarm grading

0 likes · 8 min read

Threshold‑Free Business Metric Monitoring Using Machine Learning

Efficient Ops

Sep 17, 2018 · Operations

How Alibaba Scales Monitoring: From CMDB to AI‑Driven Full‑Link Observability

Alibaba’s monitoring evolution—from fragmented early tools to the standardized Sunfire platform and now AI‑powered full‑link observability—addresses scaling challenges, introduces business‑centric metrics, automated traceability, and intelligent anomaly detection, illustrating how massive, multi‑tenant infrastructures achieve unified, proactive operations at scale.

AIOpsAlibabaMonitoring

0 likes · 19 min read

How Alibaba Scales Monitoring: From CMDB to AI‑Driven Full‑Link Observability