openclaw-qqlobster-skills/skills/product-manager-skills/knowledge/discovery-research.md

Discovery & Research

Compressed decision logic, frameworks, and quality gates for running product discovery end-to-end: framing problems, interviewing customers, mapping jobs and journeys, generating solutions, and validating hypotheses before committing to build.

Problem Framing

Problem Statement (Component)

Template -- write from the user's perspective:

I am:       [persona with 3-4 key characteristics]
Trying to:  [desired outcome -- measurable, not a task]
But:        [barriers preventing the outcome]
Because:    [root cause, not symptom]
Which makes me feel: [authentic emotion from research]

Final statement formula: [Persona] needs a way to [outcome] because [root cause], which currently [impact].

Quality gates:

• "I am" passes if you can picture a real person (not "busy professionals")
• "Trying to" is an outcome, not an activity
• "Because" survives 5-why interrogation
• "Makes me feel" uses verbatim customer language, not marketing copy
• Final statement fits one sentence and is measurable

Top anti-patterns:

1. Solution smuggling -- "The problem is we don't have X." Fix: reframe around user outcome.
2. Business problem disguised as user problem -- "Users want to reduce our churn." Fix: dig into why users leave from their perspective.
3. Symptom instead of root cause -- "Because the UI is confusing." Fix: keep asking "why" until you hit structural cause.

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Problem Framing Canvas (MITRE, Interactive)

Three-phase bias-check before you write a problem statement.

Phase 1 -- Look Inward:

• What is the problem? (symptoms only)
• Why haven't we solved it? (new / hard / low priority / lack of resources / authority / systemic inequity)
• How are we part of the problem? (confirmation bias / internal bias / survivorship bias / premature convergence)

Phase 2 -- Look Outward:

• Who experiences it? When, where, consequences?
• Who else has it? Who doesn't? (counter-examples reveal root cause)
• Who's been left out of the conversation?
• Who benefits from the problem existing? Who benefits from it being solved?

Phase 3 -- Reframe:

• Restate: "[Who] struggles to [what] because [root cause], leading to [consequence]. Affects [segments], overlooked because [bias]."
• HMW: "How might we [action] as we aim to [objective]?"

Quality gates:

• HMW is broad enough to permit multiple solutions, narrow enough to be actionable
• Canvas was completed cross-functionally, not solo
• "Who benefits from the status quo?" was explicitly answered

Top anti-patterns:

1. Skipping Look Inward -- groupthink persists. Fix: force explicit bias discussion.
2. Generic reframe -- "Improve user experience." Fix: include who, what, when, consequence, root cause.
3. HMW too narrow -- "How might we add a mobile app?" Fix: state the job, not the solution.

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Customer Discovery

Discovery Process (Workflow, 6 phases / 3-4 weeks)

Phase 1: Frame (Day 1-2)
  -> Problem Framing Canvas (120 min) + Problem Statement (30 min)
  -> Optional: Proto-Persona, JTBD
  -> Output: problem hypothesis, 3-5 research questions, success criteria
  -> Gate: enough context to start research? If no, gather data first (+2-3 days)

Phase 2: Plan Research (Day 3)
  -> Discovery Interview Prep (90 min)
  -> Recruit 5-10 participants, schedule across 1-2 weeks
  -> Output: interview guide (5-7 Mom Test questions), participant roster

Phase 3: Conduct Research (Week 1-2)
  -> 5-10 interviews + support ticket analysis + analytics review
  -> Note template per interview: participant, context, actions, pain points, workarounds, verbatim quotes, insights
  -> Gate: saturation? Same pains across 3+ interviews = proceed. Still learning = +3-5 interviews.

Phase 4: Synthesize (End of Week 2)
  -> Affinity mapping: sticky notes -> themed clusters with frequency counts
  -> Optional: Customer Journey Map workshop
  -> Prioritize: score each pain on frequency x intensity x strategic fit (1-5 each)
  -> Output: top 3-5 pain points, 3-5 verbatim quotes per pain, validated problem statement

Phase 5: Generate & Validate Solutions (Week 3)
  -> Opportunity Solution Tree OR Lean UX Canvas
  -> Design experiments: concierge / prototype / landing page / A/B test
  -> Run experiments (1-2 weeks each)
  -> Gate: validated? If no, pivot to next solution (+1-2 weeks)

Phase 6: Decide & Document (Week 3-4)
  -> GO (roadmap + epics + PRD) / PIVOT (next solution) / KILL (deprioritize)
  -> 30-min stakeholder readout: problem validation, solution validation, recommendation

Timeline ranges: fast track 3 weeks (5 interviews, 1 experiment) | typical 4 weeks | thorough 6-8 weeks.

Top anti-patterns:

1. Skipping interviews -- relying only on analytics. Fix: always 5-10 qualitative interviews.
2. Analysis paralysis -- 6 weeks synthesizing. Fix: time-box to 3-4 weeks total.
3. Discovery as one-time event -- run continuous (Teresa Torres: 1 interview/week).

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Interview Prep (Interactive, 4 adaptive questions)

Q1 -- Research Goal: problem validation | JTBD discovery | retention/churn investigation | feature prioritization

Q2 -- Target Segment: people who experience problem regularly | people who tried to solve it | people in target segment regardless of awareness | people who recently experienced it

Q3 -- Constraints: limited access (5-10, 2 weeks) | existing base (100+ customers) | cold outreach required | internal stakeholders only (proxy)

Q4 -- Methodology (context-aware on Q1-Q3):

• Mom Test (Rob Fitzpatrick — problem validation): past behavior, not hypotheticals. "Tell me about the last time..."
• JTBD interviews: what customers hire/fire. "What were you trying to get done?"
• Switch interviews: push/pull of changing solutions. "What prompted you to look?"
• Timeline/journey mapping: chronological walkthrough of full experience

Output: interview plan with opening (5 min), 5 core questions with follow-ups and anti-patterns, closing (5 min), bias checklist, success criteria, logistics.

5 biases to avoid in every interview:

1. Confirmation bias -- don't ask "Don't you think X is a problem?"
2. Leading questions -- don't ask "Would you use this?"
3. Hypothetical questions -- don't ask "If we built Y, would you pay?"
4. Pitching disguised as research -- don't explain your solution
5. Yes/no questions -- don't ask "Is invoicing hard?"

Interview success = specific stories (not generic complaints) + past behavior (not wishes) + patterns across 3+ interviews + at least one surprise.

Top anti-patterns:

1. Asking what customers want -- gets feature requests, not problems. Fix: ask about past behavior.
2. Pitching instead of listening -- don't mention your solution until last 5 min (if at all).
3. Stopping at 1-2 interviews -- small sample = confirmation bias. Fix: 5-10 minimum.

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Jobs to Be Done

JTBD Framework (Component)

Three categories of customer jobs:

Type	Question	Examples
Functional	What tasks to complete?	"Reconcile monthly expenses for tax filing"
Social	How to be perceived?	"Be seen as strategic by exec team"
Emotional	What state to achieve/avoid?	"Feel confident I'm not missing details"

Four categories of pains:

• Challenges: obstacles preventing job completion
• Costliness: excessive time, money, or effort
• Common mistakes: preventable errors
• Unresolved problems: gaps in current solutions

Four categories of gains:

• Expectations: what exceeds current solutions
• Savings: time/money/effort reductions
• Adoption factors: what triggers switching
• Life improvement: how life gets better

Quality gates for jobs:

• Verb-driven (actions, not nouns)
• Solution-agnostic ("communicate with team" not "use Slack")
• Specific ("track expenses for tax deductions" not "manage finances")

Prioritization: rank pains by intensity (acute vs. mild). Ask: "If we solved one pain, which has biggest impact?"

Top anti-patterns:

1. Confusing jobs with solutions -- "I need Slack." Fix: ask "Why?" 5 times.
2. Ignoring social/emotional jobs -- people buy on emotion, justify with logic. Fix: explicitly ask about perception and feelings.
3. Fabricating JTBD without research -- assumptions aren't insights. Fix: conduct switch interviews or contextual inquiries.

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Opportunity Mapping

Opportunity Solution Tree (Teresa Torres — Interactive, 2 phases)

Structure:

Desired Outcome (1 measurable metric)
    |
    +-- Opportunity 1 (customer problem, not solution)
    |     +-- Solution A + experiment
    |     +-- Solution B + experiment
    |     +-- Solution C + experiment
    |
    +-- Opportunity 2
    |     +-- Solutions...
    |
    +-- Opportunity 3
          +-- Solutions...

Phase 1 -- Generate tree:

1. Extract desired outcome (revenue growth / retention / acquisition / efficiency)
2. Generate 3 opportunities per outcome (customer problems with evidence)
3. Generate 3 solutions per opportunity (with hypothesis + experiment for each)

Phase 2 -- Select POC:

• Score each solution: Feasibility (1-5) + Impact (1-5) + Market Fit (1-5)
• Feasibility: 1 = months, 5 = days. Impact: 1 = minimal, 5 = major. Market Fit: 1 = customers don't care, 5 = actively request.
• Pick highest total score as POC. Define experiment type: A/B test, prototype + usability, or concierge.

Hypothesis template: "If we [solution], then [metric] will [change] from [X] to [Y] because [rationale]."

Top anti-patterns:

1. Opportunities disguised as solutions -- "We need a mobile app." Fix: reframe as customer problem: "Mobile users can't access product on the go."
2. Skipping divergence -- "We know the solution." Fix: generate 3+ per opportunity. Force divergence before convergence.
3. No experiments -- picking solution and going to roadmap. Fix: every solution must map to an experiment.
4. Vague outcomes -- "Improve UX." Fix: make measurable: "Reduce drop-off from 60% to 40%."

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Customer Journey

Journey Map (Component)

Horizontal axis (stages): Awareness -> Consideration -> Decision -> Service -> Loyalty

Vertical axis (per stage):

• Customer Actions (observable, specific)
• Touchpoints (digital + physical + human)
• Customer Experience (emotions with customer quotes)
• KPIs (measurable, stage-appropriate)
• Business Goals (outcome-focused, stage-aligned)
• Teams Involved (cross-functional with specific roles)

Quality gates:

• Emotions are specific ("relieved setup took 30 min, not 3 hours") not generic ("happy")
• Touchpoints include offline (conferences, calls), not just digital
• Map reflects what customers actually do, not what you want them to do
• KPIs and goals present for every stage

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Journey Mapping Workshop (Interactive, 5 questions)

Q1 -- Actor: select persona (primary / secondary / high-churn / newly discovered) Q2 -- Scenario + Goal: first-time use / core workflow / problem resolution / upgrade-expansion Q3 -- Journey Phases: generate 4-6 phases based on scenario (e.g., Discover -> Evaluate -> Try -> Activate -> Use -> Expand) Q4 -- Per-phase mapping: 3-5 actions, thoughts, emotions, and pain points per phase Q5 -- Opportunities: rank 5-7 pain points by impact (HIGH/MEDIUM/LOW) with evidence

Output: full journey map + prioritized opportunity list.

Top anti-patterns:

1. Mapping internal process, not customer experience -- "Lead generated -> Qualified -> Demo." Fix: map from customer POV.
2. No emotions -- actions only. Fix: add customer quotes and emotional states.
3. Too many personas in one map -- loses focus. Fix: one map per persona.

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Lean Validation

Lean UX Canvas (v2, Interactive, 8 boxes)

Fill order:

Box	Question	Content Type
1. Business Problem	What changed that created a problem?	Context + trigger
2. Business Outcomes	What behavior change = success?	Metrics (not emotions)
3. Users	Which persona first?	Specific segment
4. User Outcomes & Benefits	Why would users seek this?	Goals, emotions, empathy (not metrics)
5. Solutions	What might solve it?	3+ candidate features/initiatives
6. Hypotheses	Testable if/then statements	"We believe [outcome] if [user] attains [benefit] with [solution]"
7. Learn First	What's the riskiest assumption?	Value > usability > feasibility > viability risk
8. Least Work	Smallest experiment to test it?	Must complete in <2 weeks

Box 2 vs Box 4 distinction: Box 2 = behavior change metrics. Box 4 = human motivation and empathy.

Top anti-patterns:

1. Starting with solutions -- Box 1 says "build X." Fix: ask "What changed? Why is this a problem now?"
2. Confusing Box 2 and Box 4 -- metrics in the empathy box. Fix: Box 2 = numbers, Box 4 = feelings.
3. Only one solution in Box 5 -- no exploration. Fix: force 3+ candidates.
4. Skipping experiments -- "just build it." Fix: design smallest test first.

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PoL Probe (Component) -- Proof of Life

A disposable, hypothesis-driven validation artifact. Not an MVP. Planned for deletion.

5 required characteristics: Lightweight (hours/days) + Disposable (deletion date set) + Narrow Scope (one hypothesis) + Brutally Honest (surfaces harsh truth) + Tiny & Focused (reconnaissance, not product).

Template fields: hypothesis, risk being eliminated, probe type, target users, success criteria (pass/fail/learn thresholds), tools, timeline, disposal plan, owner, status.

5 Probe Flavors:

Flavor	Core Question	Timeline	When to Use
Feasibility Check	Can we build this?	1-2 days	Technical unknowns, API deps, data integrity
Task-Focused Test	Can users complete this job?	2-5 days	Critical UI moments, navigation, drop-off zones
Narrative Prototype	Does this earn buy-in?	1-3 days	Complex flow explanation, stakeholder alignment
Synthetic Data Simulation	Can we model without production risk?	2-4 days	Edge cases, unknown-unknowns, load testing
Vibe-Coded Probe	Will this survive real user contact?	2-3 days	Workflow/UX validation needing real interaction

Golden Rule: Use the cheapest prototype that tells the harshest truth.

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PoL Probe Advisor (Interactive, decision logic)

Selection flow: hypothesis -> risk type -> core question -> recommended probe.

Decision matrix:

• Technical feasibility unknown -> Feasibility Check (spike-and-delete, API sniff tests)
• Critical UI friction -> Task-Focused Test (Optimal Workshop, UsabilityHub, Maze)
• Need stakeholder alignment -> Narrative Prototype (Loom walkthrough, slideware storyboard)
• Edge case exploration -> Synthetic Data Simulation (Monte Carlo, synthetic users, LangFlow)
• Need real user interaction -> Vibe-Coded Probe (ChatGPT Canvas + Replit + Airtable Frankensoft)

Refinement questions when hypothesis is too broad:

1. What's the smallest thing you could test first?
2. What would failure look like?
3. Is this testing user behavior, technical feasibility, or stakeholder alignment? Pick one.

Top anti-patterns:

1. Choosing based on tooling comfort -- "I know Figma, so I'll prototype." Fix: match method to hypothesis, not skillset.
2. Defaulting to code -- "Let's just build it." Fix: ask what's cheapest path to harsh truth.
3. Confusing vibe-coded probes with MVPs -- scope creep, refusal to dispose. Fix: set disposal date before building.
4. Testing multiple things at once -- ambiguous results. Fix: one probe, one hypothesis.
5. No success criteria -- "we'll know it when we see it." Fix: define pass/fail/learn before building.

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Quality Gates

Consolidated Anti-Patterns Across All 11 Skills

Problem framing failures:

• Solution smuggling in problem statements
• Business metrics framed as user problems
• Generic personas ("busy professionals")
• Skipping bias examination (Look Inward)

Research failures:

• Leading / hypothetical / yes-no questions
• Pitching disguised as research
• Stopping at 1-2 interviews (need 5-10 minimum)
• Not recording insights immediately post-interview
• Never reaching saturation (same patterns in 3+ interviews)

Synthesis failures:

• Analysis paralysis (6+ weeks, no decisions)
• Opportunities disguised as solutions in OST
• Vague outcomes that can't be measured
• Journey maps reflecting internal wishful thinking, not customer reality
• Generic emotions ("happy") instead of specific states

Validation failures:

• Prototype theater (impressive demos that teach nothing)
• Choosing validation method by tooling comfort, not hypothesis
• Testing multiple variables in one experiment
• No pre-defined failure criteria
• Treating disposable probes as production code
• Discovery as one-time event instead of continuous practice

Universal Quality Checks

Every discovery artifact should pass these:

1. Falsifiable: can you describe what failure looks like?
2. Evidence-backed: grounded in customer research, not assumptions?
3. Specific: can you picture the person, the problem, the metric?
4. Actionable: does it inform a concrete next step?
5. Time-boxed: is there a deadline that prevents indefinite exploration?