Data-Driven Product Management

Course Info

Length: 1 Week

Type: Online

Available Dates

Fees

  • Sep-23-2024

    1,550

  • Oct-14-2024

    1,550

  • Nov-04-2024

    1,550

  • Dec-02-2024

    1,550

  • Jan-06-2025

    1,550

  • Feb-10-2025

    1,550

  • Mar-17-2025

    1,550

  • Apr-28-2025

    1,550

  • May-19-2025

    1,550

  • June-16-2025

    1,550

  • July-07-2025

    1,550

  • Aug-11-2025

    1,550

  • Sep-22-2025

    1,550

  • Oct-27-2025

    1,550

  • Nov-17-2025

    1,550

  • Dec-15-2025

    1,550

Course Details

Course Outline

5 days course

Fundamentals of Modern Product Management 


  • Overview of product management 
  • Understanding lean product methodology in product management 
  • Developing mission, vision, and value to develop product strategy from business strategy 
  • Defining Objective and Key Results (OKRs) 
  • Utilizing OKRs to design product roadmaps

Data-Driven Approach 


  • Defining data-driven product management and its significance 
  • Exploring types of product data:


  1. Customer Data
  2. Performance Data 
  3. Progress Data


  • Understanding Data Product Journey and its elements:


  1. People 
  2. Processes
  3. Technology 


  • Defining varieties of data products


  1. Raw data
  2. Derived data
  3. Algorithms
  4. Decision support
  5. Automated decision-making 


  • Understanding data-driven product strategy

Data Analysis and Metrics Definition 


  • Leveraging data to segment users based on behavior and needs 
  • Utilizing the market-sizing process to analyze the market 
  • Utilizing prioritization methods:


  1. RICE Scoring Model
  2. Lines in the Sand Framework 



  • Defining metrics that matter for different product stages 
  • Exploring the characteristics of actionable metrics that enable data-driven decision-making

Data-Driven Experimentation and Storytelling 


  • Understanding the steps of structuring statistical experiments 
  • Exploring AB testing best practices 
  • Understanding the concept “Definitions of Done” and its importance 
  • Utilizing stories to communicate data insights with stakeholders 
  • Utilizing data visualizations for presentations and reports

Product Analytics 


  • Exploring product analytics tools:



  1. Google Analytics 
  2. Amplitude 
  3. Google Sheets/Excel
  4. SQL 


  • Familiarizing with important types of product analysis:


  1. Funnel analysis 
  2. Cohort analysis 
  3. Repeat rates 
  4. Churn rates 


  • Understanding the ethical considerations related to the usage of data in product management 
  • The importance of promoting transparency around data collection and usage
  • Course recap and Q&A