Coursera

Product Analytics Unlocked: Metrics to Meaningful Insight Specialization

Coursera

Product Analytics Unlocked: Metrics to Meaningful Insight Specialization

Build Product Analytics for Data-Driven Growth.

Transform user behavior data into strategic business decision that drive measurable product success.

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Get in-depth knowledge of a subject
Intermediate level

Recommended experience

4 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
Intermediate level

Recommended experience

4 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Build scalable SQL data pipelines that transform millions of product events into optimized analytical datasets for business intelligence.

  • Apply advanced statistical techniques including clustering algorithms, A/B testing, and survival analysis for user segmentation and retention.

  • Design interactive dashboards and diagnostic frameworks that identify funnel bottlenecks and communicate performance insights effectively

  • Develop strategic prioritization skills using RICE methodology and data storytelling to influence product roadmaps and business decisions.

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Taught in English
Recently updated!

March 2026

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Specialization - 4 course series

What you'll learn

  • Build scalable data pipelines using SQL and Pandas to transform 10+ million rows of raw event data into structured analytics datasets.

  • Design and optimize star schemas with Type-2 slowly changing dimensions to track historical changes in product analytics data.

  • Compare and implement advanced SQL window functions across different dialects like Presto and Spark for cross-platform compatibility.

  • Evaluate existing data warehouse schemas and propose performance refinements using aggregation techniques and indexing strategies.

Skills you'll gain

Category: Performance Analysis
Category: Data Warehousing
Category: Star Schema
Category: Extract, Transform, Load
Category: Database Design
Category: Data Transformation
Category: Pandas (Python Package)
Category: Time Series Analysis and Forecasting
Category: Big Data
Category: SQL
Category: JSON
Category: Data Manipulation
Category: Performance Tuning
Category: Data Validation
Category: Data Quality
Category: Apache Airflow
Category: Real Time Data
Category: Data Pipelines

What you'll learn

  • Apply k-means clustering to segment users and create actionable profiles that inform targeted marketing strategies and product decisions.

  • Design A/B tests with proper power analysis and identify common biases that can invalidate experimental results and business insights.

  • Calculate and compare N-day vs rolling retention metrics to evaluate user engagement and distinguish between seasonal and churn patterns.

  • Build Kaplan-Meier survival curves to analyze retention across user groups and determine statistical significance of differences.

Skills you'll gain

Category: Algorithms
Category: Customer Analysis
Category: Marketing Analytics
Category: Strategic Decision-Making
Category: Analysis
Category: Unsupervised Learning
Category: Performance Measurement
Category: User Research
Category: Customer Insights
Category: Trend Analysis
Category: Statistical Inference
Category: Product Management
Category: Analytics
Category: Customer Retention
Category: Sample Size Determination
Category: Statistical Analysis
Category: Data-Driven Decision-Making
Category: Scikit Learn (Machine Learning Library)
Category: Business Intelligence

What you'll learn

  • Build interactive dashboards that translate business KPI requests into self-service analytics tools with drill-through functionality.

  • Create retention heatmaps with event annotations and evaluate visualizations for accessibility and clarity improvements.

  • Design optimized user activation funnels by selecting critical events and identifying process redundancies for consolidation.

  • Apply statistical methods to analyze engagement metrics and validate predictive relationships between activation and retention.

Skills you'll gain

Category: Analytics
Category: Process Analysis
Category: Key Performance Indicators (KPIs)
Category: Dashboard
Category: Predictive Analytics
Category: Customer Analysis
Category: Process Optimization
Category: Process Design
Category: Statistical Analysis
Category: Performance Metric
Category: Business Analytics
Category: Interactive Data Visualization
Category: Customer Retention
Category: Customer Insights
Category: Marketing Analytics
Category: Data Visualization
Category: Business Requirements
Category: Requirements Analysis
Category: Web Analytics
Category: Heat Maps

What you'll learn

  • Design tracking systems by translating product features into event schemas and diagnose funnel regressions to pinpoint user drop-off causes.

  • Apply RICE prioritization framework to evaluate features and create decision memos linking data trends to strategic roadmap recommendations.

  • Analyze churn logs to identify attrition root causes and establish success criteria with counter-metrics for new product features.

  • Build predictive models using decision trees and logistic regression, then present insights using structured data storytelling frameworks.

Skills you'll gain

Category: Statistical Methods
Category: Business Analytics
Category: Root Cause Analysis
Category: User Flows
Category: Analytics
Category: Data Capture
Category: Customer Analysis
Category: Predictive Modeling
Category: Resource Allocation
Category: Performance Analysis
Category: Data Storytelling
Category: Forecasting
Category: Data-Driven Decision-Making
Category: Prioritization
Category: Performance Metric
Category: Product Roadmaps
Category: Strategic Prioritization
Category: Customer Retention
Category: Product Management
Category: Web Analytics

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267 Courses 38,605 learners

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