Candidates are expected to demonstrate the judgement of a working Product Manager: weighing incomplete information, competing stakeholder demands, and trade-offs between customer value, business value, and delivery constraints, and choosing the most defensible next action.
Detailed domain specifications
Domain 1 · 5% · 2 questions
Product Management Foundations
Establish the candidate's understanding of what Product Management is, how the role differs from Project Management, Program Management, and Business Analysis, and how a PM creates value.
Learning objectives
- Explain the PM's accountability for value
- Distinguish PM from adjacent roles
- Describe the PM's relationship to engineering, design, and the business
Knowledge
- Core PM responsibilities
- Value vs. output vs. outcome
- The PM as a decision-maker under uncertainty
- How PM differs across company stages (startup vs. enterprise)
Practical skills
- Identify the appropriate owner of a decision in an ambiguous cross-functional situation
- Distinguish outcome-oriented from output-oriented thinking
Key concepts
- Outcomes vs. outputs
- Value exchange
- PM as “CEO of the product” (and the limits of that analogy)
- Build-measure-learn mindset
Frameworks
- Outcome vs. output framing
- RACI (applied lightly, not as a memorised acronym test)
Example situations
- A PM is asked to just “manage the project timeline”
- A new PM must clarify their decision rights with a Head of Engineering
Not covered
- Formal project management certifications (PMP-style scheduling, critical path, Gantt mechanics)
Expected level: Application — candidates must recognise foundational principles operating inside a scenario, not recite definitions.
Domain 2 · 7.5% · 3 questions
Product Vision, Strategy & Goals
Assess the candidate's ability to connect day-to-day product decisions to a coherent vision and strategy.
Learning objectives
- Differentiate vision, strategy, and goals
- Translate strategy into actionable product direction
- Recognise when a decision is inconsistent with stated strategy
Knowledge
- Vision as long-term direction
- Strategy as the chosen path and trade-offs
- Goals/OKRs as measurable near-term targets
- Strategy as saying “no”
Practical skills
- Evaluate whether a proposed feature or roadmap item is consistent with strategy
- Identify strategic drift
- Set outcome-based goals
Key concepts
- Vision-strategy-goals hierarchy
- OKRs
- Strategic focus areas
- Opportunity cost of strategic choices
Frameworks
- OKRs
- Simple strategy frameworks (e.g., focus area / bet selection), used conceptually, not tested as trivia
Example situations
- A team is asked to build a feature that grows a metric outside the company's stated strategic focus
- A PM must reject a request that conflicts with the product vision
Not covered
- Corporate-level business strategy frameworks (e.g., Porter's Five Forces in depth) beyond what a PM needs conceptually
Expected level: Application — judge whether a real decision aligns with a given strategy.
Domain 3 · 7.5% · 3 questions
Customer Discovery & Problem Validation
Assess the ability to identify real customer problems before committing to solutions.
Learning objectives
- Distinguish a validated problem from an assumed one
- Select appropriate discovery methods
- Avoid solution-first thinking
Knowledge
- Qualitative research methods (interviews, contextual inquiry)
- Problem statements
- Jobs-to-be-done thinking
- Bias in customer feedback (e.g., vocal minority, sales-driven requests)
Practical skills
- Choose the right discovery method for a situation
- Recognise when a stated customer “want” masks a different underlying need
- Avoid confirmation bias
Key concepts
- Problem vs. solution space
- Jobs-to-be-Done
- Discovery vs. delivery
- Sample bias
Frameworks
- Jobs-to-be-Done
- Problem statement structure
- Customer interview best practice (open questions, avoiding leading questions)
Example situations
- One large customer requests a feature that conflicts with broader usage data
- A PM must decide whether to run interviews or trust an internal stakeholder's assumption
Not covered
- Formal market-research statistics/survey design methodology at an academic level
Expected level: Application in ambiguous, conflicting-signal scenarios.
Domain 4 · 2.5% · 1 question
Market & Competitive Analysis
Assess the ability to use market and competitive context to inform product decisions without over-indexing on competitors.
Learning objectives
- Use competitive information appropriately
- Avoid feature-parity traps
- Identify differentiation opportunities
Knowledge
- Competitive analysis basics
- Market sizing concepts (TAM/SAM/SOM at a conceptual level)
- Positioning and differentiation
Practical skills
- Decide whether to match a competitor's feature or pursue differentiation
- Interpret competitive pressure against internal evidence
Key concepts
- Feature parity trap
- Differentiation vs. parity
- Market timing
Frameworks
- TAM/SAM/SOM (conceptual)
- Basic competitive positioning
Example situations
- A competitor launches a feature and sales asks for immediate parity despite no internal customer demand
Not covered
- Detailed financial market-sizing calculations or formal competitive-intelligence tooling
Expected level: Application — weigh competitive pressure against customer and business evidence.
Domain 5 · 5% · 2 questions
Product Discovery & Hypothesis Validation
Assess the ability to run structured discovery to reduce risk before building.
Learning objectives
- Frame assumptions as testable hypotheses
- Select the right validation technique for desirability, viability, and feasibility risk
Knowledge
- Continuous discovery
- Types of product risk (value, usability, feasibility, business viability)
- Assumption mapping
Practical skills
- Identify the riskiest assumption in a proposal
- Choose a lightweight validation method before full build
Key concepts
- Four risks (value/usability/feasibility/viability)
- Assumption testing
- Discovery cadence
Frameworks
- Opportunity Solution Tree (conceptual)
- Assumption/risk mapping
Example situations
- A team is confident a solution will work but has not tested willingness to pay
- Engineering questions technical feasibility before commercial validation is complete
Not covered
- Specific proprietary discovery tooling or vendor products
Expected level: Application — select the correct next discovery action given a scenario.
Domain 6 · 5% · 2 questions
Product Value & Outcomes
Assess understanding of how to define and maximise value for users and the business.
Learning objectives
- Differentiate user value from business value
- Define outcome-based success criteria
- Recognise vanity metrics
Knowledge
- Value exchange between user and business
- Leading vs. lagging indicators
- Outcome vs. output goal-setting
Practical skills
- Reframe an output-based request as an outcome
- Identify when a “successful” launch has not created real value
Key concepts
- Value maximisation
- Outcome over output
- Vanity vs. actionable metrics
Frameworks
- Outcome-based goal-setting
- Value proposition thinking
Example situations
- A feature ships and usage is high, but retention does not improve
- A PM must decide whether “shipped” equals “successful”
Not covered
- Formal financial valuation or corporate-finance value modelling
Expected level: Application in trade-off scenarios between user and business value.
Domain 7 · 7.5% · 3 questions
Product Prioritisation & Decision-Making
Assess the ability to make defensible prioritisation calls under competing pressures and incomplete information.
Learning objectives
- Apply prioritisation frameworks appropriately
- Justify trade-offs
- Resist purely political or HiPPO-driven prioritisation
Knowledge
- Common prioritisation frameworks and their appropriate contexts
- Cost of delay
- Opportunity cost
- Saying no
Practical skills
- Choose and defend a prioritisation decision given conflicting stakeholder input and partial data
- Recognise when more validation is needed before prioritising
Key concepts
- RICE
- Value vs. effort
- Cost of delay
- HiPPO bias
- Opportunity cost
Frameworks
- RICE
- Value vs. Effort
- MoSCoW (used critically, including its limitations)
- Cost of Delay
Example situations
- CEO-requested feature vs. data-supported feature with limited engineering capacity
- Two validated opportunities competing for the same sprint
Not covered
- Advanced operations-research optimisation mathematics
Expected level: Application — this is a core, heavily tested domain.
Domain 8 · 2.5% · 1 question
Product Roadmaps & Planning
Assess the ability to build and communicate roadmaps that reflect strategy and uncertainty honestly.
Learning objectives
- Distinguish a roadmap from a fixed delivery schedule
- Communicate roadmap uncertainty to stakeholders
Knowledge
- Outcome-based/theme-based roadmaps vs. feature-date roadmaps
- Roadmap horizons (now/next/later)
- The risks of date-driven roadmaps
Practical skills
- Respond to stakeholder demands for fixed dates
- Structure a roadmap around outcomes rather than features
Key concepts
- Now-Next-Later
- Theme-based roadmapping
- Roadmap as a communication tool, not a contract
Frameworks
- Now/Next/Later
- Theme-based roadmap
Example situations
- Sales wants a hard delivery date on an unvalidated feature
Not covered
- Detailed Gantt-chart or critical-path scheduling
Expected level: Application in stakeholder-pressure scenarios.
Domain 9 · 5% · 2 questions
Product Backlog Management
Assess the ability to maintain a healthy, value-ordered, transparent backlog.
Learning objectives
- Order a backlog by value and risk
- Keep the backlog appropriately refined
- Manage backlog health over time
Knowledge
- Backlog ordering principles
- Refinement cadence
- Backlog transparency
- Avoiding backlog bloat
Practical skills
- Decide how to re-order a backlog when new information arrives
- Identify signs of an unhealthy backlog
Key concepts
- DEEP backlog attributes (Detailed appropriately, Estimated, Emergent, Prioritised)
- Continuous refinement
Frameworks
- DEEP
- Backlog refinement practices
Example situations
- New data arrives mid-sprint that changes item priority
- A backlog has grown stale and items are no longer relevant
Not covered
- Specific backlog-tooling software features (e.g., a particular vendor's UI)
Expected level: Application — real backlog-management dilemmas.
Domain 10 · 5% · 2 questions
Requirements, User Stories & Acceptance Criteria
Assess the ability to translate validated problems into clear, testable requirements.
Learning objectives
- Write/evaluate user stories that express user value
- Define acceptance criteria that make “done” unambiguous
Knowledge
- User story structure and purpose
- INVEST criteria
- Acceptance criteria vs. implementation detail
- Splitting large stories
Practical skills
- Identify a poorly written story or missing acceptance criteria
- Split an oversized story appropriately
Key concepts
- INVEST
- Given-When-Then style acceptance criteria
- Story vs. task
Example situations
- A story is too large to complete in a sprint
- Acceptance criteria are missing, causing rework after delivery
Not covered
- Formal software requirements specification (SRS) documentation standards
Expected level: Application — evaluate/correct a flawed artifact in a scenario.
Domain 11 · 5% · 2 questions
Agile Product Delivery
Assess understanding of how product work flows through iterative delivery, and the PM's role in that flow.
Learning objectives
- Explain iterative/incremental delivery
- Identify the PM's responsibilities during delivery (not just planning)
Knowledge
- Agile values and principles (conceptual, not trivia)
- Iteration/increment
- Definition of done
- The difference between Scrum and Kanban at a conceptual level
Practical skills
- Respond appropriately to mid-sprint scope pressure
- Protect delivery focus while remaining responsive to change
Key concepts
- Iterative delivery
- Definition of done
- Flow vs. timeboxed delivery
Frameworks
- Agile principles (conceptual)
- Definition of Done
Example situations
- A stakeholder asks to add scope mid-sprint
- A team's “done” definition is inconsistent, causing quality issues downstream
Not covered
- Engineering-specific practices (CI/CD pipeline configuration, branching strategy mechanics)
Expected level: Application — protecting delivery integrity under pressure.
Domain 12 · 7.5% · 3 questions
Scrum & Product Owner Responsibilities
Assess the candidate's understanding of the Product Owner accountability within Scrum, used as a reference point for professional rigor — not the whole certification.
Learning objectives
- Explain Product Owner accountabilities
- Distinguish PO from Scrum Master and Development Team accountabilities
- Apply Scrum events purposefully
Knowledge
- Product Owner accountability for backlog value
- Scrum events and their purpose (Sprint Planning, Daily Scrum, Review, Retrospective)
- Sprint Goal
- Self-managing teams
Practical skills
- Identify who should make a given decision within a Scrum team
- Respond to a Scrum event being misused
- Protect the Sprint Goal
Key concepts
- Product Owner accountability
- Sprint Goal
- Empiricism (transparency, inspection, adaptation)
Frameworks
- Scrum accountabilities and events (conceptual understanding, applied to scenarios — not terminology recall)
Example situations
- A Scrum Master is asked to make a prioritisation call that belongs to the PO
- A Sprint Review is being used only as a demo with no stakeholder feedback loop
Not covered
- Verbatim recall of the Scrum Guide
- Other Agile framework certifications (SAFe, LeSS) in depth
Expected level: Application — the exam tests judgement within Scrum situations, not memorised Scrum Guide text.
Domain 13 · 7.5% · 3 questions
Product Analytics & Metrics
Assess the ability to select, interpret, and act on product data.
Learning objectives
- Choose appropriate metrics for a given goal
- Distinguish correlation from causation
- Avoid vanity metrics and metric gaming
Knowledge
- Leading vs. lagging indicators
- North Star metric concept
- Funnel/retention/engagement metrics
- Common analytics pitfalls (Simpson's paradox conceptually, survivorship bias, correlation vs. causation)
Practical skills
- Interpret conflicting data to make a defensible decision
- Identify when more data is needed before deciding
- Spot a misleading metric
Key concepts
- North Star metric
- Leading/lagging indicators
- Cohort vs. aggregate analysis
- Statistical caution (without requiring formal statistics)
Frameworks
- North Star Metric framework
- AARRR-style funnel thinking (conceptual)
Example situations
- Engagement is up but retention is flat
- Two metrics point in opposite directions and a decision is needed with a deadline
Not covered
- Statistical modelling, SQL, or data-engineering skills
Expected level: Application — interpreting real, sometimes conflicting, data.
Domain 14 · 5% · 2 questions
Experimentation & MVPs
Assess the ability to design lightweight validation before full investment.
Learning objectives
- Design an appropriate MVP or experiment for a given risk
- Interpret experiment results correctly
Knowledge
- MVP as a learning tool, not a lesser product
- A/B testing basics
- Fake-door and concierge tests
- Statistical significance at a conceptual level
Practical skills
- Choose the right-sized experiment for the risk and stage
- Avoid shipping a full solution when a smaller test would answer the question
- Interpret an inconclusive test result appropriately
Key concepts
- MVP vs. MMP (Minimum Marketable Product)
- Experiment design
- Risk-appropriate validation
Frameworks
- Build-Measure-Learn
- A/B testing (conceptual)
- Fake-door tests
Example situations
- A team wants to build a full feature to “see if customers like it” when a landing-page test would answer the question faster
Not covered
- Statistical test calculations (p-values, sample-size formulas)
Expected level: Application — matching validation method to risk and stage.
Domain 15 · 7.5% · 3 questions
Stakeholder Management
Assess the ability to manage competing stakeholder interests while protecting product integrity.
Learning objectives
- Identify stakeholder motivations
- Manage conflicting stakeholder demands
- Communicate trade-offs transparently
Knowledge
- Stakeholder mapping (influence/interest)
- Negotiation and expectation-setting
- Escalation vs. autonomous decision-making
- Saying no constructively
Practical skills
- Respond to an executive overriding a data-backed decision
- Align two stakeholders with conflicting requests using shared goals/evidence
Key concepts
- Stakeholder mapping
- Transparent trade-off communication
- Influence without authority
Frameworks
- Stakeholder influence/interest mapping
Example situations
- Two department heads want conflicting features prioritised
- An executive demands a decision be reversed without new evidence
Not covered
- Formal organisational-behaviour theory or HR conflict-resolution certification content
Expected level: Application — high-pressure, political scenarios.
Domain 16 · 5% · 2 questions
Product Launch & Go-to-Market
Assess the ability to plan and execute a product or feature launch that achieves real adoption.
Learning objectives
- Coordinate cross-functional launch readiness
- Select an appropriate launch strategy for risk and maturity
- Define post-launch success criteria before launch
Knowledge
- Launch tiers (e.g., soft launch, phased rollout, full launch)
- GTM coordination (marketing, sales enablement, support readiness)
- Post-launch monitoring
Practical skills
- Choose a phased rollout vs. full launch given risk
- Identify a missing readiness dependency (e.g., support not trained) before go-live
Key concepts
- Phased/staged rollout
- Launch readiness checklist thinking
- Post-launch success metrics defined pre-launch
Frameworks
- Phased rollout / staged launch approach
Example situations
- Support has not been trained ahead of a scheduled launch
- A high-risk feature is proposed for a full 100% rollout
Not covered
- Marketing campaign design, paid-media strategy, or brand positioning in depth
Expected level: Application — readiness and risk judgement, not marketing-copywriting skill.
Domain 17 · 2.5% · 1 question
Product Lifecycle Management
Assess the ability to manage a product or feature across its lifecycle, including decline and sunset.
Learning objectives
- Recognise lifecycle stage from evidence
- Make appropriate investment/harvest/sunset decisions
Knowledge
- Lifecycle stages (introduction, growth, maturity, decline)
- Sunset/deprecation best practice
- Investment decisions by stage
Practical skills
- Decide whether to keep investing in a declining feature or sunset it
- Manage a deprecation communication responsibly
Key concepts
- Product lifecycle stages
- Sunk cost fallacy
- Responsible deprecation
Frameworks
- Product lifecycle model (conceptual)
Example situations
- A legacy feature has declining usage but a vocal minority resists its removal
Not covered
- Formal portfolio-management financial modelling
Expected level: Application — evidence-based lifecycle decisions.
Domain 18 · 2.5% · 1 question
Product Risk & Trade-offs
Assess the ability to identify, weigh, and communicate product risk and trade-offs.
Learning objectives
- Identify the dominant risk type in a scenario (value, usability, feasibility, viability, or business/compliance risk)
- Make and justify a trade-off decision
Knowledge
- Categories of product risk
- Trade-off communication
- Irreversible vs. reversible decisions
Practical skills
- Decide how much validation is proportional to a decision's reversibility and cost
- Communicate a risk trade-off transparently to stakeholders
Key concepts
- Reversible (“two-way door”) vs. irreversible (“one-way door”) decisions
- Risk-proportionate diligence
Frameworks
- One-way/two-way door decision framing
Example situations
- A team must decide how much testing is proportionate before an easily-reversible UI change vs. a costly infrastructure change
Not covered
- Formal enterprise risk-management (ERM) certification content
Expected level: Application in ambiguous, high-stakes scenarios.
Domain 19 · 2.5% · 1 question
Cross-functional Product Leadership
Assess the ability to lead and align a cross-functional team without formal authority.
Learning objectives
- Influence engineering, design, and business functions toward a shared goal
- Resolve cross-functional disagreement constructively
Knowledge
- Influence without authority
- Shared goal-setting across functions
- Facilitating disagreement toward a decision
Practical skills
- Resolve a design-engineering disagreement that is blocking progress
- Align a cross-functional team behind a decision they initially disagreed with
Key concepts
- Influence without authority
- Shared outcomes as an alignment tool
Frameworks
- None formal — assessed through judgement in scenarios
Example situations
- Design and engineering disagree on an approach and are at an impasse ahead of a deadline
Not covered
- Formal people-management (hiring, performance reviews, compensation)
Expected level: Application — leadership judgement, not people-management mechanics.
Domain 20 · 2.5% · 1 question
Ethics & Responsible Product Management
Assess the candidate's ability to recognise and respond to ethical risk in product decisions.
Learning objectives
- Identify dark patterns and manipulative design
- Recognise data-privacy and accessibility considerations in product decisions
Knowledge
- Dark patterns
- Informed consent in data use
- Accessibility as a baseline responsibility
- Responsible handling of sensitive user data
Practical skills
- Reject or redesign a feature that relies on manipulative design or unclear consent
- Weigh short-term metric gains against user trust
Key concepts
- Dark patterns
- Privacy-by-design
- Accessibility
- Long-term trust vs. short-term metric gains
Frameworks
- None formal — assessed through applied judgement
Example situations
- A growth tactic increases sign-ups but relies on a confusing cancellation flow
- A feature would collect more data than necessary for its stated purpose
Not covered
- Legal/regulatory certification (e.g., formal GDPR/CCPA compliance qualification)
Expected level: Application — recognising ethical risk embedded in an otherwise normal business scenario.
Competency map
- Strategic Thinking
- Domains 1, 2, 4, 17
- Customer & Market Insight
- Domains 3, 4, 5
- Value & Decision-Making
- Domains 6, 7, 18
- Planning & Execution
- Domains 8, 9, 10, 11, 12
- Evidence & Learning
- Domains 13, 14
- People & Influence
- Domains 15, 19
- Go-to-Market & Lifecycle
- Domains 16, 17
- Professional Responsibility
- Domains 20
