Data Driven Product Management Training Course

Highlights

• Product management fundamentals

• Defining Product Strategy from Company Strategy

• Opportunity analysis

• Defining metrics

• Growth frameworks

• Baking analytics into requirements

• Working with Product Analytics tools

• Product analytics warchest

• Management Reporting

Course Details

Introduction, modern product management fundamentals

• Iterative, lean product methodology centered on validated learnings and ‘build-measure-learn’

• The mindset and activities required by self-organising, hands-on product teams

Defining Product Strategy from Company Strategy

• Using KPIs to cascade Mision vision and value through to day to day work

• OKR frameworks and goal driven roadmaps

• Product rather than project mindset

Opportunity analysis

• Customer segmentation

• Market sizing

• RICE

Defining metrics

• How to choose a Metric that Matters?

• What makes an metric actionable?

Growth frameworks

• Pirate Metrics / Lean Analytics / North Star

• Actionable funnels

• 30 minute exercise – making a framework for a product

Experimentation

• How to structure an experiment

• Setting the line in the sand

• AB testing best practice

Baking analytics into requirements

• How to define event metrics in story writing

• Analytics ’definitions-of-done’

• Shared ownership with product teams

Working with Product Analytics tools

• Guide walkthrough of a tool – Google Analytics / Amplitude

• Use of basic tooling like Google Sheets

• Introduction to SQL

Product analytics warchest

• Funnels

• Cohort tables

• Repeat rates

• Churn rates

Management Reporting

• Ingraining data into the sprint

• Engaging stakeholders with data

• Data visualizations

Wrapping up

• Commitments made by attendees with next steps

Who should attend

Anyone involved in the software development life cycle – from Business Analysts, Project Managers, Planners, Technical Architects through to Coders and Test Analysts.

It assumes a basic understanding of the principles of agile product management in a software engineering environment, using frameworks such as Scrum or Kanban. It requires basic technical literacy, but does not require advanced knowledge of computer or data science.