Master Product Metrics Video Course: Leveraging Data, Metrics and AI to Drive Customer & Business Impact

Become a Data Driven Product Leader 📈

Every product role requires working with data. Build your confidence with metrics and learn how to leverage analytics & AI tools to drive customer and business impact.

Concise and purposefully created video lessons + attachments, from strategy to execution. Bonus: get free feedback on your key metrics!

The self paced video course is complimentary to my Amazon #1 New Release book The Insights Driven Product Manager, but also covers many more examples, how to build your analytics tools stack and how to use AI to gather customer insights faster.

12 Video Modules From Strategy to Implementation

• Aligning Metrics to Strategy
• Defining Key Metrics
• Building Your Tools Stack
• AI Tools for Better Insights
• Metrics 101 Best Practises
• Pitfalls to Avoid
• Creating a Data Driven Culture

3.5h of Concise & Purposefully Created Video Lessons

Maximise your learning experience, without sacrificing depth or clarity with high quality video lessons and slides, purposefully recorded and edited for this course.

10 Practical Templates & Reference Sheets

• Metrics One Pager
• A/B Testing Planning
• Qual vs Quant Data
• How to Share Data Insights
• Metrics 101 Checklist
• Metrics Definitions
• Leading vs Lagging Metrics

This course is best for

• Product leaders of technology products - Product Managers, business leaders, founders, but also design and engineering leaders in the product team
• I focused on creating concise content with depth, so it’s manageable for someone preparing for a product role interview, or upskilling alongside their busy day to day

About the Instructor

Corinna Stukan is a product executive, startup advisor and investor with 15 years experience leading B2B and B2C products across APAC, Europe and the US. She currently serves on the advisory board of Impact Chain and advises a range of AI and FinTech startups in New Zealand.  She leverages her pragmatic German approach to help organisations connect data insights with strategy - by tracking less, but better. Her book "The Insights Driven Product Manager" hit #1 Amazon New Release in two categories and was recommended by analytics leader Amplitude as one of the top 20 books for Senior Product Managers.

Why I created this course

Every product role requires working with data these days. Especially in today's fast moving environments, product leaders need to be able to leverage data to spot early signals and closely monitor customer and business outcomes to course correct and stay competitive. 

Ultimately, if you become more data driven and are able to articulate the impact you are having on both the customers and the business, you'll be able to not only drive greater results, but also help your career as a product leader. 

The content is complimentary to my Amazon #1 New Release book The Insights Driven Product Manager, but also covers many more examples, how to build your analytics tools stack and how to use AI to gather customer insights faster.

Course Curriculum

0. Introduction

• Course Objectives: What You Will Learn and Achieve
• Why I Created This Course: The Journey to Mastering Metrics
• Instructor Introduction: Corinna Stukan
• Course Outline & Structure: Overview of the Modules

Module 1: The Importance of Becoming More Data-Driven

• Aligning Metrics with Strategy: Connecting Goals and Actions
• Connecting Customer and Business Impact: Measuring What Matters
• Challenges in Becoming Data Driven: Common Barriers and Solutions
• Why Data-Driven Decision Making Matters: Examples of Business Impact
  

Module 2: Overview of Popular Metrics Frameworks

• Google’s HEART Framework: Measuring User Experience
• Pirate Metrics (AARRR): Growth Funnel Metrics
• SaaS Metrics: Operational and Financial Metrics
• OKRs & Goal Setting Frameworks: Aligning Goals Across Teams
• Strengths and Gaps of Each Framework: When and How to Use Them
  

Module 3: Essential Metrics to Track

• Key Customer Metrics: Acquisition, Activation, Engagement, Retention
• Key Business Metrics: Revenue, Customer Acquisition Cost (CAC), Lifetime Value (LTV)
• How to Understand Business & Financial Context: Interpreting Key Metrics
• Examples: Finding Your Product’s “Aha” Moment
• Examples: Identifying Meaningful Engagement Measures
  

Module 4: Alignment Through the Metrics One-Pager

• Introduction to the Metrics One-Pager: A Holistic View of Metrics
• Steps to Create Your Metrics One-Pager: Breaking Down Goals and Metrics
• Connecting Business Goals and Customer Metrics: Linking Strategy to Metrics
• Examples and Templates: Practical Applications
  

Module 5: Leading vs. Lagging Metrics

• Definitions and Key Differences: Understanding Leading and Lagging Metrics
• When to Use Leading vs. Lagging Metrics: Choosing the Right Approach
• Examples: Using Leading Metrics to Course Correct
• How to Find Your Activation Metric: Techniques and Tools
  

Module 6: Metrics 101 - Avoiding Common Pitfalls

• Pitfall #1: Metrics No One Understands
• Pitfall #2: Only Tracking Lagging Metrics
• Pitfall #3: Vanity Metrics and How to Avoid Them
• Pitfall #4: Metrics Overload
• Metrics 101 Checklist for Actionable Metrics: Ensuring Impactful Metrics

Module 7: A/B Testing & Experimentation Fundamentals

• Key Elements: Control Groups vs. Variants
• Setting Hypotheses & Success Criteria: Establishing Clear Goals
• How to Determine Your Sample Size: Ensuring Statistical Significance
• A/B Testing Tools Stack: Popular Tools for Experimentation
• Examples & Case Studies: Practical Applications of A/B Testing
• Template: Planning and Executing Experiments
  

Module 8: Qualitative vs. Quantitative Data

• Definitions and When to Use Which: Complementary Data Types
• Quant Data Examples: Dashboards, A/B Tests, Ratings
• Qual Data Examples: Interviews, Reviews, Open Surveys
• The Concept of Correlation vs. Causation: Avoiding Misinterpretations
• How to Balance Quant & Qual Data: Best Practices
  

Module 9: Creating Your Analytics Tool Stack

• Categories of Analytics Tools: Overview and Use Cases
• Experimentation Platforms: Tools for Testing and Validation
• Product Analytics Tools: Tracking Key Metrics
• Feedback and Qualitative Data Tools: Gathering Customer Insights
• Fundamentals of Event Instrumentation: Setting Up Accurate Tracking
• Example Use Cases: Real-Life Applications
  

Module 10: AI Capabilities for Metrics and Insights

• How AI is Transforming Product Analytics: Opportunities and Challenges
• Using AI for Predictive Modelling: Forecasting Customer Behaviour
• AI Insights Examples from Analytics Tools: Practical Use Cases
• Natural Language Processing for Sentiment Analysis: Analysing Feedback
• Practical Applications of GenAI for Faster Insights: Unlocking Efficiency
• The Future of GenAI & Analytics: Trends and Predictions
• Demo: Creating Your Own Analytics Dashboard with AI
  

Module 11: How to Share Insights and Create a Data-Driven Culture

• Embedding Data-Driven Practices in Your Organisation: Building Habits
• The Mindset of Learning from Data: Turning Failures into Insights
• Template: Sharing Data Insights with Stakeholders
  

Module 12: Master Product Metrics - Course Summary

• Recap of Key Learnings, Concepts, and Frameworks: Summarising Takeaways
• How to Move from Strategy to Implementation: Steps to Turn Strategy into Action
• Additional Resources and Tools: Continuing Your Learning Journey