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User Segmentation, Experimentation, and Retention Analytics · LearnSpace
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User Segmentation, Experimentation, and Retention Analytics

Курс от Coursera
Средний≈ 9 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

You'll learn to analyze user behavior through advanced segmentation and retention techniques that directly impact business decisions. By completing this course, you'll gain the expertise to identify distinct user groups using clustering algorithms, design statistically valid A/B tests, and calculate retention metrics that guide product strategy. You'll benefit professionally by developing skills that make you invaluable to product teams and growth organizations. What makes this unique is the integration of unsupervised learning, experimental design, and survival analysis - combining technical data science skills with business-focused analytics. You'll work with real user data to create actionable insights that drive user engagement and optimize product performance across different acquisition channels.

Навыки, которые вы освоите

Customer RetentionDriving engagementSample Size DeterminationStatistical Hypothesis TestingAnalyticsStatistical InferenceUser ResearchCustomer AnalysisScikit Learn (Machine Learning Library)Statistical AnalysisTrend AnalysisUnsupervised LearningAlgorithmsPerformance MeasurementData-Driven Decision-MakingProduct ManagementCustomer InsightsAnalysis

Программа курса

8 модулей · 53 учебных материалов

01User Clustering Analysis - Foundation6 материалов
Why Customer Segmentation Drives Product SuccessВидеоK-Means Clustering Fundamentals for Customer AnalyticsЧтениеRFM Analysis Framework: Strategic Customer Segmentation for Product AnalyticsЧтениеK-Means Customer Segmentation: Coach Dialogue ScriptDIALOGUE

Учитесь у экспертов

Professionals from the Industry

Преподаватель курса

User Segmentation, Experimentation, and Retention Analytics
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Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 9 ч

8 модулей

Язык: Английский

Часть программы вашего университета
Build Customer Segments Using K-Means ClusteringЗадание
User Clustering and RFM Analysis Knowledge CheckЗадание
02 Retention Method Evaluation - Core Application7 материалов
Why Retention Methodology Choice Impacts Business StrategyВидеоRolling-Cohort vs N-Day Retention: Core ConceptsЧтениеCalculating and Interpreting Different Retention MetricsВидеоRetention Analysis ImplementationDIALOGUECompare Retention Methods and Create Technical Recommendations ЗаданиеRetention Analysis Methodology Knowledge CheckЗаданиеUser Segmentation and Retention Analysis MasteryЗадание
03Evaluate Experiment Bias Sources6 материалов
Why Bias Detection Separates Successful A/B Tests from Costly MistakesВидеоUnderstanding Common Bias Sources in A/B TestingВидеоPractical Bias Detection Framework for Experiment ValidationЧтениеDetecting Bias in Real A/B Test Data: A Step-by-Step DemonstrationВидеоEvaluate Netflix Engagement Experiment for Bias SourcesЗаданиеBias Detection Knowledge CheckЗадание
04Design Statistically Valid Experiments7 материалов
Why Statistical Rigor Drives Business Success in A/B TestingВидеоPower Analysis Fundamentals for Reliable Business ExperimentsЧтениеCalculating Sample Sizes: Power Analysis in PracticeВидеоUsing Statistical Calculators for Experiment DesignВидеоDesign Power Analysis for Meta Advertising Platform ExperimentЗаданиеPower Analysis and Sample Size Knowledge CheckЗаданиеStatistical Power Analysis Mastery AssessmentЗадание
05Cohort Analysis Foundations7 материалов
Why Channel-Segmented Cohort Analysis Drives Marketing ROIВидеоCohort Analysis Fundamentals for Data ProfessionalsВидеоSegmentation Methodologies in Cohort Analysis ЧтениеHow to Use Channel-Segmented Cohort Analysis to Optimize Marketing SpendЧтениеFrom Cohort Data to Strategic Channel DecisionsDIALOGUEBuild and Analyze Acquisition Channel CohortsЗаданиеCohort Analysis Fundamentals AssessmentЗадание
06Retention Pattern Analysis7 материалов
The Business Impact of Pattern Recognition in Retention AnalysisВидеоInterpreting Retention Curve Patterns and Decay RatesВидеоSystematic Approaches to Seasonal vs. Fatigue Pattern DiagnosisЧтениеHow to Diagnose Retention Drops: Seasonal Behavior vs. Product ProblemsЧтениеDiagnosing Real-World Retention Pattern Scenarios DIALOGUERetention Pattern Analysis AssessmentЗаданиеAdvanced Retention Pattern Diagnosis Project Задание
07 Kaplan-Meier Survival Analysis - Core Application8 материалов
Why Netflix and Spotify Research Use Survival Analysis for Strategic DecisionsВидеоKaplan-Meier Methodology for Comparing User Retention Between GroupsЧтениеReading and Comparing Kaplan-Meier Survival Curves Between GroupsВидеоKaplan-Meier Survival Analysis in R: A How-To GuideЧтениеPreparing for Survival Analysis AssessmentDIALOGUECreate Survival Analysis for Experiment ReadoutЗаданиеSurvival Analysis Knowledge CheckЗаданиеComprehensive Survival Analysis EvaluationЗадание
08Project: User Segmentation, Experimentation, and Retention Analytics5 материалов
Why This Project MattersЧтениеProject RequirementsЧтениеGraded Assignment: Product Analytics Integration ProjectЧтениеGraded Quiz: User Segmentation, Experimentation, and Retention AnalyticsЗаданиеSolution KeyЧтение