Ux Strategy

UX Strategy

You are an expert in UX strategy — the discipline that connects design decisions to business outcomes and customer value. Your recommendations are grounded in Teresa Torres's Continuous Discovery Habits (Opportunity Solution Trees, outcome-driven discovery), Jim Kalbach's Jobs to Be Done Playbook (job mapping, desired outcomes, switch analysis), Jaime Levy's UX Strategy (competitive analysis, value innovation, funnel design), Jeff Gothelf and Josh Seiden's Lean UX (hypothesis-driven design, outcomes over outputs), Victor Papanek's Design for the Real World (ethical responsibility, shared value, designing for underserved populations), and Google's HEART framework for UX metrics.

UX strategy is the high-level plan to achieve business goals under conditions of uncertainty. It precedes wireframes, visual design, and development. Without it, teams build features no one needs. With it, every design decision traces back to a reason.

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Core Framework

UX strategy sits at the intersection of four concerns:

All four must be addressed. A desirable product that isn't viable fails. A viable product that isn't desirable is ignored. A product without competitive differentiation gets commoditized. A product without metrics can't improve.

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Outcomes Over Outputs

The most common strategic failure: teams measure success by features shipped instead of impact created.

Types of Outcomes

The sweet spot is product outcomes. They're specific enough for a team to influence directly, and they connect upward to business outcomes.

Setting Outcomes

Outcomes emerge from a two-way negotiation (Torres): 1. Leadership sets strategic context: "We need to improve retention" 2. Product team proposes product outcomes they believe will drive retention: "Reduce time-to-first-value for new users" 3. Both sides agree on the outcome and how to measure it

When the team is new to an outcome, set a learning goal ("Discover the key drivers of activation") rather than a performance goal ("Increase activation by 15%"). Learning goals reduce pressure and encourage exploration.

Anti-patterns

• Pursuing more than 1-2 outcomes at once per team
• Choosing outputs disguised as outcomes ("Launch the redesigned dashboard")
• Setting outcomes without connecting them to business goals
• Picking outcomes in isolation without leadership alignment

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Opportunity Mapping

The Opportunity Solution Tree (OST)

The OST (Torres) is the central strategic artifact. It maps the path from a desired outcome to testable experiments:

        [Desired Outcome]
              |
    ┌─────────┼──────────┐
    |         |          |
[Opportunity] [Opportunity] [Opportunity]
    |              |
 ┌──┴──┐      ┌───┴───┐
[Sol A] [Sol B] [Sol C] [Sol D]
   |       |      |
[Test]  [Test]  [Test]

Four layers: 1. Outcome (root) — The business/product outcome the team is pursuing 2. Opportunities — Customer needs, pain points, and desires discovered through research 3. Solutions — Ideas the team is exploring to address opportunities 4. Assumption tests — Experiments to validate which solutions will work

Writing Good Opportunity Statements

Opportunities must be:

• Written from the customer's perspective
• Describing a need, pain point, or desire — never a solution
• Grounded in actual customer stories — not team assumptions

Structuring the Tree

• Parent-child: Broad opportunities break into specific sub-opportunities. "Managing finances is stressful" → "I don't know where my money goes" + "Unexpected bills catch me off guard"
• Organize by moments in time: Top-level branches map to distinct moments in the customer journey ("When I first sign up," "When I check my balance," "When I pay a bill")
• Sibling opportunities should be distinct and comparable — if two siblings overlap significantly, merge them

Prioritizing Opportunities

Select a single leaf-node opportunity (one without children) to address. Evaluate across:

Most prioritization decisions are reversible (two-way doors). Don't over-analyze. Pick, explore, and switch if evidence suggests a different path.

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Jobs to Be Done (JTBD)

Core Concept

People don't buy products — they "hire" them to get a job done (Kalbach, Christensen). A job is the process of reaching objectives under given circumstances.

Jobs are:

• Solution-agnostic — they exist independent of any product
• Stable over time — technology changes, fundamental objectives don't
• Focused on progress — people hire solutions to make progress toward goals
• Contextual — circumstances matter as much as the objective itself

Job Structure

Job Map (8 Stages)

Jobs unfold as a process (Ulwick):

1. Define — Determine objectives and plan 2. Locate — Gather materials and information 3. Prepare — Organize and set up 4. Confirm — Ensure readiness 5. Execute — Perform the job 6. Monitor — Evaluate success 7. Modify — Iterate as necessary 8. Conclude — End and follow up

Each stage contains desired outcomes — needs formulated as: [Direction] + [Measure] + [Object] + [Clarifier]

Example: "Minimize the time it takes to find relevant job listings when searching in a new city"

Finding Underserved Needs

Plot needs on an importance-satisfaction matrix:

Opportunity score (Ulwick): Importance + (Importance - Satisfaction). Scores above 10 signal significant opportunity. Scores above 15 signal extreme opportunity.

Four Forces of Switching

When customers switch solutions, four forces are at play (Moesta):

Switching happens when Push + Pull > Anxiety + Habit. Strategy: amplify push and pull while reducing anxiety and habit.

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Competitive Analysis

Types of Competitors (Levy)

JTBD competitors are the most dangerous blind spot. Traditional competitive analysis misses them entirely.

Competitive Analysis Process

1. Identify competitors — 5-8 direct, 3-5 indirect, 2-3 JTBD competitors 2. Research each — Product, business model, UX strengths/weaknesses, positioning 3. Build a comparison matrix — Attributes as rows, competitors as columns 4. Analyze — Find gaps, patterns, table stakes, and opportunities 5. Write findings brief — Recommendations with a clear strategic point of view

Value Innovation (Levy, Kim & Mauborgne)

Value innovation is the simultaneous pursuit of differentiation and low cost — creating a leap in value for customers and the business.

Four patterns: 1. New mash-up — Combine features from different competitors into something new 2. Innovative slice — Take one aspect of a broad platform and do it radically better 3. Consolidation — Unify disparate experiences into one simple solution 4. Two-sided connection — Bring distinct user segments together for unprecedented value

Market positioning:

• Blue ocean — Uncontested space, no direct competition
• Red ocean — Crowded market, fierce competition
• Purple ocean — Somewhere in between

Value innovation targets blue ocean. If you're in a red ocean, stop competing on existing attributes and create new ones.

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Validating Strategy

Hypothesis-Driven Design (Gothelf & Seiden)

Replace "requirements" with "assumptions." Everything is a hypothesis until validated.

Hypothesis format:

We believe that [doing this] for [these people] will achieve [this outcome]. We'll know we're right when [measurable signal].

Validation process: 1. State assumptions explicitly 2. Identify the riskiest assumption (highest importance × lowest evidence) 3. Design the smallest experiment to test it 4. Define success criteria before running the test — use specific numbers ("7 out of 10 participants will..."), not percentages 5. Run the test, evaluate results, iterate

Assumption Types (Torres)

Map assumptions on a 2×2 grid: importance (y-axis) × evidence (x-axis). Upper-right quadrant (high importance, low evidence) = "leap of faith" assumptions. Test these first.

Testing Tools

Aim for 10-20 small assumption tests per week (Torres), not one large study per quarter.

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UX Metrics

HEART Framework (Google)

Using HEART: Pick 1-2 categories most relevant to your current outcome. Don't track all five simultaneously — that's monitoring, not strategy.

North Star Metric

A single metric that captures the core value your product delivers to customers. It connects product usage to business outcomes.

Characteristics of a good North Star:

• Measures value delivered (not vanity)
• Leading indicator of revenue/retention (not lagging)
• A team can directly influence it
• Simple enough to rally a team around

Connecting Metrics to Outcomes

North Star Metric
    |
    ├── Input Metric 1 (Adoption): New users completing onboarding
    ├── Input Metric 2 (Engagement): Users reaching "aha moment"
    └── Input Metric 3 (Retention): Users active in week 2
         |
         ├── Signal: Users who complete setup within 24 hours
         └── Signal: Users who invite a teammate

Measure people, not actions. "500 users completed onboarding" is more meaningful than "1,200 onboarding actions occurred" — one active user can generate many actions.

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Strategy Process (End-to-End)

This is not linear. Discovery feeds analysis, validation feeds back to discovery, measurement informs the next cycle.

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Ethical and Responsible Strategy

Strategy that ignores social impact eventually fails — through regulation, reputation damage, or simply building products that harm the people they're meant to serve. Responsible strategy isn't a constraint on innovation; it's a lens that expands the field of opportunities. This framework draws on Victor Papanek's design responsibility principles and connects them to practical strategy decisions.

The Responsibility Check

Before committing to a strategic direction, test it against three dimensions:

Designing for Underserved Populations

The most commercially successful products are often those that solve problems for underserved populations — not because of charity, but because underserved markets represent untapped demand.

Strategic approach: 1. Identify who is excluded by current solutions — affordability, accessibility, literacy, infrastructure, cultural context 2. Understand their constraints — These constraints are design requirements, not obstacles. A product that works with low bandwidth, low literacy, or low cost is often a better product for everyone 3. Design within constraints — Solutions designed for constrained environments frequently become mainstream innovations (SMS-based banking → mobile payments; voice interfaces for accessibility → smart speakers for all) 4. Test with real users in real contexts — Not in a lab. In the environment where the product will be used

Shared Value Creation

Traditional strategy asks: "How do we capture value?" Shared value asks: "How do we create value for both the business and society with every interaction?"

Practical application: For each opportunity on your OST, ask: "Does solving this create value only for us, or does it make the user's life genuinely better?" Opportunities where both align are more durable than those where they diverge.

Ethical Assumption Testing

The strategy skill already includes "Ethical" as an assumption type. Here's how to test it rigorously:

Integrating Ethics into the Strategy Process

Ethics is not a separate phase — it's a lens applied throughout:

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Common Mistakes

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Reference Files

Load these for deeper guidance on specific topics:

• references/outcomes-and-opportunities.md — Opportunity Solution Trees, outcome types, continuous discovery habits, opportunity prioritization, and the product trio
• references/competitive-analysis.md — Competitive research process, analysis matrix, value innovation, market positioning, and competitive findings briefs
• references/jobs-to-be-done.md — JTBD framework, job mapping, desired outcomes, switch interviews, four forces, and JTBD-driven personas
• references/metrics-and-measurement.md — HEART framework, North Star metrics, funnel metrics, instrumentation, and connecting metrics to outcomes
• references/value-proposition.md — Value proposition design, validation process, hypothesis-driven design, MVP strategy, and business model alignment

Templates

• templates/strategy-brief-template.md — Complete UX strategy document for framing a product initiative
• templates/competitive-analysis-template.md — Competitive analysis matrix and findings brief
• templates/competitive-brief-template.md — Standalone competitive brief for stakeholder communication
• templates/opportunity-solution-tree-template.md — OST with guidance for each layer

Examples

• examples/strategy-walkthrough.md — End-to-end UX strategy for a fictional B2B product
• examples/competitive-analysis-walkthrough.md — Full competitive analysis of a fictional market

Competitive Analysis Walkthrough

Full competitive analysis for a fictional market — demonstrating the research process, analysis framework, and strategic output.

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Context

Product: NoteStack — a knowledge management tool for small product teams (5-20 people) Main job to be done: "Organize and retrieve team knowledge so the right information is available when decisions need to be made" Trigger: The team is preparing a UX strategy brief and needs to understand the competitive landscape before defining their value proposition.

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Step 1: Build the Competitor List

Research Sources

• Google: "team knowledge management tool," "internal wiki for small teams," "team documentation tool"
• Product Hunt: searched "knowledge base," "wiki," "documentation"
• G2: Category "Knowledge Management Software" — filtered by small business
• Customer interviews: "What did you use before NoteStack?" and "What else did you consider?"

Competitors Identified

Direct (6): Notion, Confluence, Slite, Tettra, GitBook, Nuclino

Indirect (3): Google Docs (general docs used as wiki), Slack (search replaces documentation for some teams), Loom (video replaces written docs)

JTBD (3): Shared spreadsheets (tracking decisions), Email threads (institutional knowledge locked in inboxes), Human memory / asking colleagues (the "just ask Sarah" pattern)

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Step 2: Research Each Competitor

Feature Comparison Matrix

Job Performance Ratings (1-5)

Main job: "Organize and retrieve team knowledge"

Key insight: No competitor scores above 3 on "Confirm" (verifying accuracy) or "Monitor" (keeping content current). The entire market under-serves knowledge maintenance.

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Step 3: Analyze Patterns

Table Stakes (every competitor has these)

• Rich text editor with formatting
• Page hierarchy / folder organization
• Full-text search
• Team sharing and permissions
• Web-based access

Differentiators

• Notion: Block-based flexibility — can build anything (databases, wikis, project boards). Differentiator is power, but it's also the top complaint (overwhelming)
• Tettra: AI-powered answers from your docs. Ask a question, get an answer with source citations. Differentiator is retrieval, but feature set is limited
• Slite: "Ask" feature + editorial guidance ("This doc is outdated — should it be updated?"). Differentiator is proactive maintenance

Gaps (from customer reviews and interviews)

Over-Served Areas

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Step 4: Positioning Map

Dimensions chosen based on JTBD research:

• X-axis: Ease of getting started (low setup effort → high setup effort)
• Y-axis: Knowledge stays current (knowledge decays → knowledge maintained)

Knowledge       │
maintained      │
                │                  Tettra (AI answers)
                │         Slite (stale alerts)
                │
                │                              ★ OPPORTUNITY
                │
                │  Nuclino        Notion
                │         GitBook
                │                    Confluence
Knowledge       │  Google Docs
decays          │              Slack (no structure)
                └──────────────────────────────────────
              Easy to                          Hard to
              start                            start

★ = Unoccupied position: Easy to start AND knowledge stays current

The opportunity: No one occupies the "easy to start + knowledge stays maintained" quadrant. Tettra and Slite are moving toward maintenance but require moderate setup effort. Notion and Confluence are powerful but knowledge decays without dedicated wiki gardeners.

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Step 5: Value Innovation

Four Actions

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Step 6: Strategic Recommendation

Positioning Statement

For small product teams who can't keep their team knowledge current, NoteStack is a knowledge management tool that automatically surfaces and prevents stale information. Unlike Notion and Confluence, which require a dedicated wiki gardener, NoteStack keeps knowledge healthy without manual maintenance effort.

Market Type

Purple ocean. The knowledge management market is crowded (red) but the "knowledge maintenance" sub-problem is uncontested (blue). We're entering an existing market with a differentiated angle.

Strategic Bets

1. Knowledge health over knowledge creation. The market competes on creation (editors, templates, formatting). We compete on maintenance (freshness, accuracy, confidence) 2. Proactive over reactive. Don't wait for users to notice stale docs. Surface problems automatically and prompt action 3. Simple capture over powerful editing. Make it trivially easy to get knowledge into the system. Rich formatting is secondary to having the right information captured at all

Risks

Next Steps

1. Validate the "knowledge maintenance" positioning with a smoke test landing page (1 week) 2. Conduct 5 switch interviews with users who recently moved from Confluence/Notion — understand the forces (2 weeks) 3. Map the full job ("Organize and retrieve team knowledge") with desired outcomes from interviews (3 weeks) 4. Prioritize underserved outcomes using the importance-satisfaction framework (4 weeks) 5. Begin solution ideation for the top 3 underserved outcomes (5 weeks)

Strategy Walkthrough

End-to-end UX strategy for a fictional B2B product — from framing through measurement.

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Context

Product: TaskFlow — a mid-stage project management SaaS for small agencies (10-50 people) Situation: TaskFlow has 2,000 paying customers but trial-to-paid conversion has stalled at 4%. Leadership wants to reach 8%. The product trio is tasked with improving conversion. Team: PM (Dana), Designer (Marcus), Engineer (Priya)

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Phase 1: Frame

Setting the Outcome

Business outcome (from leadership): Increase monthly recurring revenue (MRR) Product outcome (proposed by trio): Increase trial-to-paid conversion from 4% to 8%

The trio pushed back on "increase MRR" as a product outcome — it's a lagging business metric the trio can't directly influence. Trial-to-paid conversion is a leading indicator they can design for.

Outcome type: Performance goal (they have 6 months of baseline data showing consistent 4%).

Constraints

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Phase 2: Discover

Customer Interviews

The trio committed to two interviews per week for 4 weeks. They targeted three segments:

• Users who converted (signed up, paid) — what worked?
• Users who churned during trial — what failed?
• Users who are still in trial — what are they evaluating?

Recruiting: In-product intercept on day 5 of trial ("Would you chat with our product team for 20 minutes? $25 gift card").

Interview Approach

Story-based interviewing (Torres). Key questions:

• "Tell me about the last time you were evaluating a new tool for your team."
• "Walk me through what happened from when you first signed up for TaskFlow."
• "Tell me about a moment when you almost gave up on the trial."

Key Findings (after 8 interviews)

From churned trial users: 1. "I signed up but couldn't figure out how to set up a project the way my team actually works" — 5/8 mentioned this 2. "I imported my data from [competitor] but it came in wrong and I couldn't fix it" — 3/8 3. "I couldn't get my team to try it because they'd have to learn a whole new system" — 4/8 4. "I realized I'd need to set up everything myself and I don't have time for that" — 6/8

From converted users: 1. "I got lucky — a colleague showed me how they set it up and I copied their approach" — 3/4 2. "The templates got me 80% there, but I had to customize a lot" — 2/4 3. "Once my team saw the dashboard, they got it immediately" — 3/4

From active trial users: 1. "I'm still trying to figure out if this can replace what we have. I haven't set up a real project yet" — 2/3 2. "I keep comparing it to [competitor] and I can't tell if it's better yet" — 2/3

Experience Map

The trio individually mapped the trial experience, then merged:

Sign up → Land on empty dashboard → Try to create a project →
Get stuck on project structure → Look for help → Find templates →
Templates don't match my workflow → Try to customize → Get confused →
Give up OR persist → Eventually set up one project → Invite team →
Team ignores invite OR team tries it → Dashboard starts showing value →
Convert OR churn

Critical insight: The gap between "sign up" and "first project that works for my team" is where most users drop off. The product delivers value once configured, but configuration is the bottleneck.

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Phase 3: Opportunity Mapping

Opportunity Solution Tree

Outcome: Increase trial-to-paid conversion (4% → 8%)
│
├── When I first sign up
│   ├── I land on an empty screen and don't know where to start
│   └── I can't tell what the product can do for me
│
├── When I try to set up my first project
│   ├── The project structure doesn't match how my team works ← TARGET
│   ├── I have to configure everything from scratch — too much effort
│   ├── Templates exist but none match my agency type
│   └── I imported data from my old tool but it mapped incorrectly
│
├── When I try to get my team to adopt
│   ├── My team has to learn a whole new system
│   ├── I can't show my team the value until everything is set up
│   └── Team invitations don't explain why they should care
│
└── When I'm evaluating whether to pay
    ├── I haven't used it enough to know if it's better than what I have
    └── I can't tell what I'd lose on the free tier

Prioritized Opportunity

Selected: "The project structure doesn't match how my team works"

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Phase 4: Competitive Analysis

Quick Competitive Scan

Gap identified: No competitor asks "What kind of work does your team do?" and then configures the project structure automatically. Everyone either provides templates (user picks and customizes) or blank canvases (user builds from scratch).

Value Innovation

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Phase 5: Ideation and Validation

Three Solutions

Solution A — Guided Setup Interview: A 5-question conversational flow during onboarding: "What does your agency do?" → "How many active projects?" → "How does work flow through your team?" → Auto-generates a configured project with realistic sample data.

Solution B — Live Template Preview: Instead of template thumbnails, show a fully populated preview of each template. User can click through and see what their project would look like with real data before committing.

Solution C — Copy a Colleague: If a team member invites them, the new user starts with a copy of the inviter's project structure. Reduces setup to zero for team members.

Assumption Testing

Solution A — Guided Setup Interview:

Solution B — Live Template Preview:

Solution C — Copy a Colleague:

Decision

Solution A validated across all three assumptions. Solutions B and C had critical failures. The trio commits to building Solution A — the Guided Setup Interview.

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Phase 6: Measure

Metrics

Instrumentation

Events tracked:

• onboarding_started — User begins guided setup
• onboarding_question_answered (with question number) — Progress through flow
• onboarding_completed — All 5 questions answered
• onboarding_abandoned (with last question) — Where users drop off
• project_auto_generated — System creates the project
• project_first_edit — User modifies the generated project (signal of engagement)
• team_invite_sent — User invites team members

Cohort comparison: Users who go through guided setup vs. users who skip to manual setup (escape hatch preserved for power users).

Results (8 weeks post-launch)

Analysis: Conversion improved significantly (4% → 6.5%) but didn't reach the 8% target. The funnel data reveals: onboarding and project creation improved beyond targets, but the drop-off now occurs between "project created" and "team adoption." The bottleneck has shifted.

Next cycle: The trio returns to the OST and pivots to the "When I try to get my team to adopt" branch — specifically "I can't show my team the value until everything is set up." The guided setup solved the individual setup problem, but team adoption remains the next opportunity.

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Key Takeaways

1. The outcome negotiation prevented wasted effort — "Increase MRR" would have led the trio in a dozen directions. "Increase trial-to-paid conversion" focused the work 2. Interviews revealed the real problem — The team assumed trial churn was a pricing issue. It was a setup friction issue 3. Three solutions prevented premature commitment — Solution B and C seemed promising but failed critical assumptions 4. Small, fast tests saved months — The prototype test for Solution A took 3 days. Building the wrong solution would have taken 6 weeks 5. Measurement revealed the next opportunity — Hitting the target on intermediate metrics but not the final one showed exactly where the funnel still leaks 6. Discovery is continuous — The team didn't "finish" strategy. They completed one cycle and started the next

Competitive Analysis

How to research, analyze, and position against competitors. Grounded in Jaime Levy's UX Strategy, Jim Kalbach's Jobs to Be Done, and established competitive strategy frameworks.

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Why Competitive Analysis Matters

• Learn what has worked and what hasn't — without repeating others' mistakes
• Identify gaps and opportunities the market hasn't addressed
• Understand table-stakes features (what customers expect from everyone)
• Inform value proposition and positioning
• Provide evidence for strategic decisions rather than gut feelings

When to do it: Before ideation, before major pivots, and quarterly as maintenance.

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Types of Competitors

Traditional View

JTBD View (Kalbach)

Traditional competitive analysis misses the most dangerous competitors: solutions from entirely different categories that get the same job done.

To find JTBD competitors: In customer interviews, ask "Before you used [product], how did you get this done?" The answers reveal the real competitive landscape.

How Many to Analyze

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Research Process (Levy)

Step 1: Build the Competitor List

Sources:

• Google search for your product category
• App stores (search category and keywords)
• G2, Capterra, Product Hunt (market reviews)
• Customer interviews ("What did you use before?" "What else did you consider?")
• Industry reports and analyst coverage
• Crunchbase for funded startups in your space

Step 2: Research Each Competitor

For each competitor, gather:

Business information:

• Founded when, by whom
• Funding (rounds, amounts, investors)
• Revenue model (subscription, freemium, marketplace, advertising)
• Estimated user base / monthly traffic
• Recent news, pivots, acquisitions

Product information:

• Core features and key experience
• Pricing and plans
• Platform coverage (web, mobile, desktop)
• Integration ecosystem
• Content types and personalization

UX evaluation:

• Onboarding experience (sign up and try it yourself)
• Core workflow — how many steps to complete the main job?
• Information architecture and navigation
• Visual design quality and consistency
• Accessibility (quick check: keyboard, contrast, screen reader)
• Performance (load time, responsiveness)

Customer perception:

• App store ratings and review themes
• G2/Capterra reviews — what do customers praise and complain about?
• Social media sentiment
• Support forums — what issues come up repeatedly?

Step 3: Build the Comparison Matrix

A matrix with competitors as columns and attributes as rows. Attributes should cover:

Color-code cells: green (strong), yellow (adequate), red (weak), gray (not available).

Step 4: Analyze Patterns

Look for:

Table stakes — Features every competitor has. These are baseline expectations. You must have them, but they won't differentiate you.

Differentiators — Features only 1-2 competitors have that receive positive customer reception. These are opportunities to adopt or outperform.

Gaps — Customer needs (from reviews and interviews) that no competitor addresses well. These are your highest-value innovation opportunities.

Over-served areas — Features that are heavily invested in across the market but that customers rate as low-importance. Competitors are wasting effort here — you can skip or simplify.

Step 5: Write the Findings Brief

Structure: 1. Introduction — Scope, methodology, competitors analyzed 2. Market landscape — Overall positioning map (can be a 2×2 using the two most differentiating dimensions) 3. Direct competitor analysis — Key findings for each 4. Indirect and JTBD analysis — Non-obvious threats and opportunities 5. Gaps and opportunities — What the market isn't doing well 6. Recommendations — Your strategic point of view. Take a stand.

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Value Innovation

The Concept (Kim & Mauborgne, via Levy)

Value innovation is the simultaneous pursuit of differentiation (offering something new) and low cost (reducing or eliminating features the market over-invests in). The goal: make the competition irrelevant by creating new market space.

Four Actions Framework

For each major feature/attribute in the competitive matrix, ask:

Value Innovation Patterns (Levy)

Strategy Canvas

A visual tool showing how you compare to competitors across key attributes:

High │         ★                    ★
     │    ★              ★
     │              ★         ★
     │         ●    ●              ●
     │    ●              ●
Low  │                         ●
     └──────────────────────────────
       Attr1  Attr2  Attr3  Attr4  Attr5

★ = Your product    ● = Market average

Your value curve should cross the market average — high on some attributes, low on others. If your curve mirrors the market, you have no differentiation. If it's consistently higher, your costs are likely unsustainable.

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Market Positioning

Positioning Map

Plot competitors on two dimensions that matter most to customers. Choose dimensions from your JTBD research — the attributes customers actually use to evaluate solutions.

Common dimension pairs:

• Ease of use vs. Power/flexibility
• Price vs. Feature comprehensiveness
• Self-serve vs. High-touch support
• Speed of setup vs. Depth of customization

Look for empty quadrants — market positions no one occupies. These may be opportunities or may be empty for good reason (validate before pursuing).

Positioning Statement

Template:

For [target customer segment] who [key need/job to be done], [product name] is a [category] that [key differentiator]. Unlike [primary competitor], we [primary advantage].

This should be one sentence. If it takes a paragraph, the positioning isn't clear enough.

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Ongoing Competitive Intelligence

Competitive analysis isn't a one-time exercise. Maintain awareness through:

Signals to Watch

• Competitor raises a large funding round → likely expanding into your space
• Competitor acquires a company in an adjacent space → entering new job territory
• Competitor's reviews suddenly improve in an area where you differentiate → your advantage is eroding
• New entrant appears with a novel approach → potential disruptor
• Competitor deprecates a feature your customers rely on → migration opportunity

Jobs to Be Done

The JTBD framework for understanding markets from the customer's perspective. Grounded in Jim Kalbach's Jobs to Be Done Playbook, Clayton Christensen's theory of disruptive innovation, and Tony Ulwick's Outcome-Driven Innovation.

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Core Principles

Five principles unite the various JTBD approaches (Kalbach):

1. Customer-centricity — People employ products to get their job done, not to interact with your organization 2. Stability — Jobs are stable over time even as technology changes. "Get from point A to point B" hasn't changed in centuries; the solutions have 3. Progress — People seek solutions that enable them to get more of their job done, quicker and easier 4. Predictability — Making the job the unit of analysis makes innovation more predictable 5. Universality — JTBD applies across all organizational functions — product, sales, marketing, support, strategy

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The Five Elements

1. Job Performer (Who)

The person executing the job. Distinguish from adjacent roles:

Always research the job performer, not proxies.

2. Jobs (What)

Writing main job statements:

• Solution-agnostic: "Listen to music" not "Use Spotify"
• Verb + object: "Prepare a meal" not "Cooking"
• Right level of abstraction: Not too broad ("Live a good life") or too narrow ("Slice an onion")

3. Process (How) — The Job Map

Jobs unfold as a process. Ulwick's 8-stage universal job map:

Job map rules:

• Write steps beginning with verbs
• Avoid referencing specific technologies or solutions
• Focus on what the job performer does, not what the product does
• Map the job, not the customer journey (jobs are solution-independent; journeys are solution-specific)

4. Needs (Why) — Desired Outcomes

Needs are formulated as desired outcome statements with four elements:

[Direction] + [Measure] + [Object] + [Clarifier]

Full example: "Minimize the time it takes to find relevant results when searching in an unfamiliar category"

Rules for desired outcomes:

• One need per statement
• Solution-agnostic (never reference a product or feature)
• Measurable (contains a unit of measure)
• Controllable (the team can design for this)
• Unambiguous (anyone reading it draws the same conclusion)

5. Circumstances (When/Where)

Contextual factors that frame job execution:

Circumstances often matter more than demographics. Two people with identical demographics may hire completely different solutions because their circumstances differ.

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Finding Underserved Needs

The Importance-Satisfaction Framework (Ulwick)

Survey job performers on each desired outcome:

Opportunity Score

Opportunity = Importance + (Importance - Satisfaction)

Opportunity Landscape

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Switch Interviews (Moesta & Spiek)

The Switch Timeline

Work backward from the moment of purchase/adoption:

[First Thought] → [Passively Looking] → [Actively Looking] → [Deciding] → [Consuming] → [Satisfaction]

The Four Forces

Strategic implications:

• To accelerate adoption: Amplify push (make current pain visible) and pull (make new value tangible)
• To reduce churn: Reduce anxiety (offer migration support, trials, guarantees) and increase habit (make your product part of the daily workflow)

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JTBD-Driven Personas

Traditional demographic personas ("Sarah, 34, marketing manager, lives in Austin") don't explain behavior. JTBD personas segment by goals and circumstances instead.

Building JTBD Personas

1. Identify behavior variables from interviews: How urgently do they need to complete the job? How frequently? How much expertise do they have? What constraints do they face? 2. Map participants to variables: Plot interviewees on each dimension 3. Find clusters: Groups that share similar goals, circumstances, and behaviors 4. Describe personas by goals: Each persona is defined by what they're trying to accomplish and the circumstances that shape how they do it

Example:

These personas explain why different users need different things — demographics can't do that.

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JTBD for Competitive Analysis

JTBD reveals competition that feature-comparison misses:

Step 1: Determine All Alternatives

Ask: "How do people currently get this job done?" Include:

• Dedicated tools (direct competitors)
• General-purpose tools used for this job (spreadsheets, docs, email)
• Manual processes (pen and paper, whiteboard, sticky notes)
• Workarounds (combining multiple tools)
• Hiring someone (outsourcing the job to a person)
• Not doing it at all (accepting the status quo)

Step 2: Compare on Job Performance

Rate each alternative on how well it performs each stage of the job map (1-5 scale):

This reveals where your product excels AND where "inferior" alternatives outperform you (spreadsheets might be more flexible for modification).

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Applying JTBD Across the Organization

Metrics and Measurement

How to define, track, and act on UX metrics that connect design decisions to business outcomes. Grounded in Google's HEART framework, Teresa Torres's outcome measurement, and Jaime Levy's funnel design.

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HEART Framework (Google)

Five categories of user-centered metrics. Don't track all five — select 1-2 most relevant to your current outcome.

Categories

Goals-Signals-Metrics (GSM) Process

For each HEART category you choose:

1. Goal — What outcome does the team want? (Qualitative) "New users should quickly understand the product's value"

2. Signal — What user behavior would indicate success or failure? (Observable) "Users complete the onboarding tutorial" / "Users reach the 'aha moment' feature"

3. Metric — How to measure the signal at scale? (Quantitative) "Percentage of new users who complete onboarding within 24 hours of signup"

Example: HEART for a SaaS Product

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North Star Metric

What It Is

A single metric that captures the core value your product delivers to customers. It serves as the focal point for the entire product team.

Characteristics

A good North Star:

• [ ] Measures value delivered to customers (not revenue — revenue is a lagging effect of value)
• [ ] Is a leading indicator of long-term business success
• [ ] Can be directly influenced by product decisions
• [ ] Is simple enough to rally a team around
• [ ] Increases when customers get more value (not gameable without delivering value)

Examples by Product Type

Input Metrics

The North Star breaks down into input metrics that the team can directly influence:

North Star: Weekly active teams using core feature
    |
    ├── Activation: % of new teams completing setup within 48 hours
    ├── Engagement: Average core-feature sessions per team per week
    ├── Adoption: % of team members who have used core feature (breadth)
    └── Retention: % of teams active this week who were active last week

Each input metric can have its own sub-metrics (signals) that connect to specific product changes.

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Funnel Metrics (Levy)

The Funnel Matrix

Track users through stages from discovery to advocacy:

AARRR (Pirate Metrics)

Where Strategy Focuses

Strategy work primarily concerns activation and retention — these are where product decisions have the most leverage. Acquisition and revenue are important but more influenced by marketing and pricing than by UX strategy.

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Connecting Metrics to Outcomes

The Metrics Tree

Business Outcome: Increase annual recurring revenue (ARR)
    |
    ├── Product Outcome: Increase enterprise trial-to-paid conversion
    │   |
    │   ├── Input: % of trial teams that complete setup
    │   ├── Input: % of trial teams that reach "aha moment"
    │   └── Input: % of trial teams that add 3+ users
    │
    └── Product Outcome: Reduce enterprise churn
        |
        ├── Input: % of accounts using core feature weekly
        ├── Input: NPS score for enterprise segment
        └── Input: Support ticket volume per account

Each input metric connects to a specific product lever the team can pull. This creates traceability from a design change to a business outcome.

Measuring Impact (Torres)

When a solution ships, close the loop:

1. Instrument the product for the metrics defined during strategy 2. Measure people, not actions: "500 users completed onboarding" > "1,200 onboarding actions occurred" 3. Measure impact on the desired outcome, not just feature usage: Did the feature actually move the needle? 4. Feed learnings back into discovery: Partial success reveals new opportunities. Failure points back to the opportunity map

Anti-patterns

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Instrumentation Checklist

Before shipping a feature, ensure these are in place:

• [ ] Outcome metric defined and baseline measured
• [ ] Success criteria stated as specific numbers ("7 out of 10 new users will complete setup within 24 hours")
• [ ] Events instrumented for key interactions (not every click — just the signals that matter)
• [ ] Cohort tracking enabled (compare behavior of users who got the feature vs. those who didn't)
• [ ] Time window defined for evaluation ("We'll measure for 4 weeks before drawing conclusions")
• [ ] Segment definitions clear (new vs. existing users, free vs. paid, enterprise vs. SMB)
• [ ] Dashboard or report created and shared with the team

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Benchmarks

Use these as starting points — actual targets depend on product, market, and maturity:

These benchmarks are reference points, not goals. Your goals should come from your outcome and baseline measurements.

Outcomes and Opportunities

How to set meaningful outcomes, map the opportunity space, and run continuous discovery. Grounded in Teresa Torres's Continuous Discovery Habits and Jeff Gothelf & Josh Seiden's Lean UX.

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The Product Trio

The ideal discovery unit is the product trio (Torres): a product manager, a designer, and a software engineer making decisions collaboratively.

The trio should make product decisions together, not in sequential handoffs. All three participate in interviews, ideation, and assumption testing.

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Setting Outcomes

The Negotiation

Outcomes should emerge from a two-way conversation between leadership and the product team:

1. Leadership provides strategic context: "Our Q3 priority is improving retention for enterprise accounts" 2. Team proposes product outcomes: "We believe reducing time-to-first-value for enterprise onboarding will improve retention" 3. Negotiate and commit: Both sides agree on the specific outcome and how to measure it

Outcome Quality Checklist

A good product outcome:

• [ ] Is a leading indicator of a business outcome (not lagging)
• [ ] Can be directly influenced by the product team's work
• [ ] Is measurable with data the team can access
• [ ] Is scoped enough for one team to own
• [ ] Connects clearly to a business outcome leadership cares about
• [ ] Is stated as a change in behavior, not a feature ("Users complete onboarding within 24 hours" not "Build onboarding wizard")

Learning Goals vs. Performance Goals

Learning goals are not weaker than performance goals. They're the appropriate first step when a team lacks sufficient understanding to set meaningful targets.

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The Opportunity Solution Tree (OST)

Building the Tree

Layer 1 — Outcome (root): State the desired product outcome at the top. One tree per outcome. If the team has two outcomes, build two trees.

Layer 2 — Opportunities: Customer needs, pain points, and desires discovered through weekly interviews. Structure as a hierarchy:

• Top-level branches: Distinct moments in the customer journey
• Child opportunities: Specific needs within each moment
• Leaf nodes: Specific enough to address directly

Example:

Outcome: Reduce time-to-first-value for enterprise users
├── When I first sign up
│   ├── I don't know where to start
│   ├── The setup requires information I don't have readily available
│   └── I can't tell if the setup is working correctly
├── When I try to use a core feature for the first time
│   ├── I can't find the feature I was promised in the sales demo
│   ├── The feature works differently than I expected
│   └── I need to configure settings before I can do anything useful
└── When I try to get my team to adopt
    ├── I can't explain the value to my team without a lot of effort
    ├── Each team member has to repeat the same setup process
    └── There's no way to share what I've already configured

Layer 3 — Solutions: For the prioritized leaf-node opportunity, generate 15-20 ideas individually (Torres), then share as a trio. Select 3 diverse solutions for further exploration — not 1 (too narrow), not 10 (too scattered).

Layer 4 — Assumption tests: For each solution, identify assumptions across all five types (desirability, viability, feasibility, usability, ethical). Map them on importance × evidence. Test "leap of faith" assumptions first.

Maintaining the Tree

The OST is a living artifact, not a one-time deliverable:

• Update after every customer interview
• Add new opportunities as they emerge
• Archive opportunities that turn out to be less important than expected
• Move between branches as evidence accumulates

Anti-patterns

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Continuous Interviewing

Why Weekly

Traditional research is project-based — commission a study, wait weeks, get a report. By the time insights arrive, context has changed. Weekly interviewing makes customer understanding a habit, not an event.

Minimum cadence: One customer interview per week, conducted by the product trio (not delegated to a separate research team).

Story-Based Interviewing

The core technique: ask customers to share specific stories about past behavior, not opinions, preferences, or hypothetical futures.

Why stories work:

• People confabulate reasons for their behavior (the "left brain interpreter" phenomenon). Asking "Why did you...?" triggers rationalization, not truth
• Stories about specific instances reveal actual behavior, workarounds, and pain points
• Stories provide context that abstract questions miss

Key practices:

Interview Snapshots

After each interview, create a one-page summary:

Participant: [Name/ID]
Date: [Date]
Context: [Role, how they use the product, relevant circumstances]

Key stories:
1. [Story summary — what happened, what they did, how it went]
2. [Story summary]

Opportunities identified:
- [Need/pain point/desire, in customer's language]
- [Need/pain point/desire]

Notable quotes:
- "[Direct quote]"
- "[Direct quote]"

Surprises:
- [Anything that challenged the team's assumptions]

Automated Recruiting

Set up a continuous pipeline rather than scrambling before each session:

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Ideation

Generate Alone, Share Together

Group brainstorming has well-documented problems (Torres): social loafing, group conformity, production blocking, downward norm setting. The fix:

1. Each trio member generates ideas individually — aim for 15-20 each 2. Share all ideas with the group 3. Build on each other's ideas to create new combinations 4. Dot-vote to select roughly 3 diverse solutions for further exploration

Getting Unstuck

When ideas dry up:

• Incubation — Take a break. Let the subconscious work
• Analogous products — How do other industries solve similar problems?
• Extreme users — What would a power user need? A complete novice?
• Wild ideas — Deliberately suggest impractical ideas to break mental constraints
• Reverse the problem — "How would we make this problem worse?" Then invert

Why Three Solutions

Exploring three solutions (not one, not ten) forces compare and contrast, which produces better evaluation than a "whether or not" decision about a single idea. Three is enough for diversity while remaining manageable for assumption testing.

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Co-Evolution of Problem and Solution

An important insight from Torres: the problem space and solution space evolve together. Learning about opportunities suggests solutions. Exploring solutions reveals new opportunities.

This means:

• Don't finish mapping all opportunities before ideating solutions
• Don't finalize solutions before exploring more opportunities
• The tree grows in all directions simultaneously
• This is expected behavior, not a process failure

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Showing Your Work

Why It Matters

Product trios don't operate in isolation. They need buy-in from leadership, sales, marketing, engineering managers. Making discovery visible builds trust and prevents stakeholder surprises.

How to Show the OST

1. Walk through the reasoning — Don't present conclusions. Show the outcome, opportunities discovered, solutions explored, and evidence gathered 2. When stakeholders disagree — Don't argue about who's right. Frame the disagreement as different assumptions and design tests to resolve them 3. Slow down — The trio has weeks of context that stakeholders lack. Take time to build shared understanding

Anti-patterns in Stakeholder Communication

Value Proposition Design

How to define, validate, and communicate the strategic promise your product makes to customers. Grounded in Jaime Levy's UX Strategy, Alexander Osterwalder's Value Proposition Canvas, Jeff Gothelf's Lean UX, and JTBD principles.

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What Is a Value Proposition?

A value proposition is the promise of value your product delivers to a specific customer segment. It answers: Why should someone choose this over every alternative — including doing nothing?

A strong value proposition has three properties: 1. Specific — Names the customer segment and their core need 2. Differentiated — States why this is better than alternatives 3. Credible — Can be substantiated with evidence

Value Proposition Statement

Template (Levy):

It's [type of product] for [customer segment] that [key differentiator].

Template (Geoffrey Moore):

For [target customer] who [key need/job], [product name] is a [category] that [key benefit]. Unlike [primary alternative], we [primary differentiation].

Examples:

Value Proposition Quality Check

• [ ] Can you state it in one sentence?
• [ ] Does it name a specific customer segment (not "everyone")?
• [ ] Does it reference a real need (validated through research, not assumed)?
• [ ] Does it state a clear differentiator from the primary alternative?
• [ ] Would a customer recognize the need as their own?
• [ ] Is the differentiator something you can actually deliver?

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The Value Proposition Canvas (Osterwalder)

A visual tool for aligning your offering with customer needs.

Customer Profile (Right Side)

Solution Profile (Left Side)

Fit

Value proposition fit occurs when:

• Pain relievers address the most important pains (not all pains — the critical ones)
• Gain creators deliver the most desired gains
• Products & services get the main job done

Lack of fit signals:

• Pain relievers address pains customers don't have
• Gain creators deliver gains customers don't value
• The product does something well that nobody asked for
• Customer interviews reveal needs your offering doesn't address

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Validating the Value Proposition

The Validation Hierarchy

Validate in order of risk and cost:

Don't skip levels. A landing page test costs days; a failed MVP costs months.

Problem Interviews (Levy)

Validate that the problem exists and matters before designing anything.

Structure: 1. Screening questions (5 min) — Qualify that this person is your target segment 2. Current behavior (10 min) — "How do you currently [get this job done]?" "What's the hardest part?" 3. Pain exploration (10 min) — "Tell me about the last time [pain point] happened. What did you do?" 4. Solution pitch (5 min) — Describe your proposed value proposition. "Would this help? How?" 5. Commitment test (2 min) — "Would you sign up for early access?" "Would you pay for this?"

Key rules:

• Ask about past behavior, not hypothetical futures
• Listen for workarounds — they signal genuine pain
• The "money-shot question" (Levy): pitch your hypothetical solution and watch the reaction. Enthusiasm = signal. Politeness = noise

Lean Validation Loop (Gothelf & Seiden)

Hypothesis → Experiment → Evidence → Iterate
    ↑                                    |
    └────────────────────────────────────┘

Hypothesis format:

We believe that [doing this] for [these people] will achieve [this outcome].

We'll know we're right when [specific, measurable signal].

Rules:

• Define success criteria before running the experiment
• Use specific numbers: "7 out of 10 participants will sign up" — not "70%"
• Time-box experiments: 1-2 weeks maximum for early validation
• One hypothesis per experiment. Don't test multiple things at once

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Proto-Personas (Gothelf & Seiden)

When you can't do full JTBD research yet, create proto-personas to align the team on assumptions.

Four components: 1. Name and snapshot — A name and rough sketch (humanizes the discussion) 2. Behavioral demographics — Not age/gender but: tech savviness, frequency of need, budget, decision authority 3. Behaviors — How they currently get the job done, what tools they use, what workarounds they employ 4. Needs and goals — What they're trying to achieve (stated as jobs, not features)

Important: Proto-personas are assumptions, not research. Label them as such. Validate and update through actual customer interviews.

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Business Model Alignment

Business Model Canvas (Osterwalder)

The value proposition sits within a broader business model. UX strategy must account for all nine building blocks:

Revenue Model Impact on UX

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MVP Strategy (Gothelf & Seiden)

Types of MVPs

MVP Principles

1. Gauge effort to degree of proof needed — Don't build more than necessary to test the current riskiest assumption 2. Ugly is fine — Design fidelity should match the stage. At the MVP stage, a sketch or wireframe will do 3. Observe behavior, not opinions — Watch what people do with the MVP. "Would you use this?" is unreliable. "Here it is — try it" is reliable 4. Time-box it — An MVP that takes 3 months to build isn't minimum. If it takes more than 2-4 weeks, scope is too large 5. Define what you'll learn — Before building, state: "This MVP will tell us whether [assumption]. We'll know if [specific signal]"

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Two-Sided Markets

Products that serve two distinct user groups (Levy) require validating the value proposition for both sides:

Key insight: You must solve the chicken-and-egg problem. Usually: start with one side (often supply) and use concierge or manual methods to serve the other until both sides reach critical mass.

The UX must address both sides, but it doesn't have to be equal. Start with the side that's harder to attract.

Competitive Analysis: [Market/Product Area]

Date: [Date] Analyst(s): [Names] Scope: [What job or product category is being analyzed]

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1. Competitor Inventory

Direct Competitors

Indirect Competitors

JTBD Competitors

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2. Feature Comparison Matrix

Color-code: Green = strong, Yellow = adequate, Red = weak, Gray = N/A

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3. Job Performance Comparison

Rate each competitor on how well they perform each stage of the main job (1-5 scale):

Main job: [Statement]

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4. Positioning Map

Dimensions

• X-axis: [Most differentiating attribute — e.g., "Ease of use"]
• Y-axis: [Second most differentiating attribute — e.g., "Feature depth"]

Map

High [Y] │
          │    [Comp 1]
          │                    [Comp 3]
          │         ★ TARGET
          │
          │  [Comp 2]
          │              [Comp 4]
Low  [Y]  │
          └────────────────────────────
         Low [X]              High [X]

★ = Desired position for our product

Empty Quadrants

[Are there unoccupied positions? Why might they be empty — opportunity or dead zone?]

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5. Analysis

Table Stakes

[Features/attributes every competitor has. Customers expect these as baseline.]

1. [Attribute] 2. [Attribute] 3. [Attribute]

Differentiators

[Features/attributes only 1-2 competitors have that receive positive reception.]

1. [Competitor] — [Differentiator] — [Customer reception] 2. [Competitor] — [Differentiator] — [Customer reception]

Gaps

[Customer needs no competitor addresses well. Sourced from reviews, interviews, support data.]

1. [Gap] — Evidence: [Source] 2. [Gap] — Evidence: [Source] 3. [Gap] — Evidence: [Source]

Over-Served Areas

[Attributes heavily invested in across the market but rated low-importance by customers.]

1. [Attribute] — [Why it's over-served]

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6. Value Innovation Opportunity

Four Actions

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7. Competitive Findings Brief

Market Landscape Summary

[2-3 sentences: what is the overall state of competition? Blue/red/purple ocean?]

Key Findings

1. [Finding with strategic implication] 2. [Finding with strategic implication] 3. [Finding with strategic implication]

Threats to Monitor

Strategic Recommendation

[Take a clear stand. What should we do based on this analysis? 2-3 sentences.]

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8. Appendix

Individual Competitor Profiles

[Competitor 1 Name]

• Overview: [2-3 sentences]
• Target segment: [Who they serve]
• Key experience: [What makes them notable]
• Strengths: [Bulleted list]
• Weaknesses: [Bulleted list]
• Recent moves: [Launches, pivots, funding, acquisitions]

[Repeat for each competitor]

Sources

• [Source 1]
• [Source 2]
• [Source 3]

Competitive Brief: [Product/Market Area]

A standalone deliverable for stakeholders who need competitive intelligence to make decisions — without reading the full analysis. This brief answers: where do we stand, what threatens us, and where should we go?

Date: [Date] Author(s): [Names] Audience: [Who this brief is for — product leadership, exec team, board, etc.] Scope: [Product category, job, or market segment analyzed]

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Executive Summary

[3-5 sentences. State the competitive situation plainly. What is the market doing? Where do we sit? What is the single most important thing the reader should know?]

---

Our Position Today

What we do well

• [Strength 1 — what customers consistently praise]
• [Strength 2]
• [Strength 3]

Where we lag

• [Weakness 1 — where competitors outperform us]
• [Weakness 2]
• [Weakness 3]

Positioning statement

For [target segment] who [need/job], [product] is a [category] that [key differentiator]. Unlike [primary competitor], we [primary advantage].

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Competitive Landscape

Market shape

[Is this a crowded market with many similar players, or a few dominant ones with distinct positions? Is the market growing, consolidating, or fragmenting?]

Key competitors

Positioning map

High [Y-axis label] │
                     │    [Comp A]
                     │                    [Comp C]
                     │         ★ US
                     │
                     │  [Comp B]
                     │              [Comp D]
Low                  │
                     └────────────────────────────
                    Low [X-axis label]     High

Empty quadrants: [Are unoccupied positions opportunities or dead zones? Why?]

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What Customers Are Telling Us

Table stakes

Customers expect these from everyone. Missing any of them is disqualifying.

1. [Feature/attribute every competitor has] 2. [Feature/attribute] 3. [Feature/attribute]

Unmet needs

No competitor handles these well. Evidence from reviews, interviews, or support data.

1. [Need] — Source: [where you found this] 2. [Need] — Source: [where you found this] 3. [Need] — Source: [where you found this]

Switching triggers

What makes customers leave one product for another in this market?

1. [Trigger — e.g., "pricing change," "missing integration," "team outgrows the tool"] 2. [Trigger]

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Threats

Signals to watch

• [Signal 1 — what would tell us a threat is materializing, e.g., "Competitor X launches a free tier"]
• [Signal 2]
• [Signal 3]

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Opportunities

Where we can win

Value innovation moves

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Recommendation

[2-4 sentences. Take a clear stand. Based on the competitive landscape, what should we do? This is not a list of options — it's a point of view.]

Immediate actions (next 30 days)

1. [Action] 2. [Action]

Strategic moves (next quarter)

1. [Action] 2. [Action]

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Appendix

Methodology

[Brief description: how many competitors analyzed, what sources were used, when the research was conducted]

Full analysis

[Link or reference to the complete competitive analysis document, if one exists]

Review schedule

• Next update: [Date — typically quarterly]
• Trigger for ad-hoc update: [Events that would warrant an immediate refresh — e.g., major competitor launch, funding round, acquisition]

Opportunity Solution Tree: [Product/Team Name]

Desired Outcome: [Product outcome the team is pursuing] Team: [Product trio members] Last updated: [Date]

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Layer 1: Desired Outcome

Outcome: [Specific, measurable product outcome]

Connected business outcome: [The business goal this product outcome drives]

How we'll measure it: [Metric, current baseline, target]

Outcome type: [ ] Performance goal (we have baseline data) / [ ] Learning goal (we're still exploring)

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Layer 2: Opportunity Space

Map customer needs, pain points, and desires discovered through interviews. Organize by moments in the customer journey.

Branch A: [Moment/Theme — e.g., "When I first try the product"]

Branch B: [Moment/Theme — e.g., "When I use the core feature"]

Branch C: [Moment/Theme — e.g., "When I try to get my team to adopt"]

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Opportunity Quality Checklist

For each opportunity, verify:

• [ ] Written from the customer's perspective (not the team's)
• [ ] Describes a need, pain, or desire (not a solution)
• [ ] Grounded in actual customer stories (not assumptions)
• [ ] Specific enough to design a solution for
• [ ] Not a feeling ("I'm frustrated") — what specifically causes it?

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Layer 2.5: Prioritization

Selected Target Opportunity

Opportunity: [The leaf-node opportunity the team will address]

Prioritization rationale:

What we're NOT pursuing right now (and why):

• [Opportunity X] — [Reason: lower severity, fewer affected customers, etc.]
• [Opportunity Y] — [Reason]

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Layer 3: Solution Space

For the selected opportunity, generate diverse solutions. Each trio member generates 15-20 ideas individually, then share and dot-vote to select 3.

Solutions Under Exploration

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Layer 4: Assumption Tests

For each solution, identify and test the riskiest assumptions.

Solution S1: [Name]

Solution S2: [Name]

Solution S3: [Name]

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Decision Log

Record key decisions and pivots as the tree evolves.

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Interview Log

Track weekly interviews that feed the tree.

UX Strategy Brief: [Product/Initiative Name]

Date: [Date] Author(s): [Names and roles] Status: [Draft / In Review / Approved]

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1. Strategic Context

Business Objective

[What business outcome is this initiative expected to drive? Be specific.]

Product Outcome

[What measurable change in user behavior will this initiative produce? This is the outcome the product team owns.]

Constraints

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2. Customer Understanding

Target Segment

[Describe in 10 words or fewer. Who specifically are we designing for?]

Main Job to Be Done

[Verb + object. Solution-agnostic. What is this customer trying to accomplish?]

Key Circumstances

[When, where, and under what conditions does this job arise?]

Current Behavior

[How do customers currently get this job done? What tools, workarounds, and processes do they use?]

Top Pain Points (from research)

Proto-Personas (if full research not yet available)

Persona 1: [Name]

• Behaviors: [How they currently work]
• Needs/goals: [What they're trying to accomplish]
• Key circumstance: [What makes their situation distinct]

Persona 2: [Name]

• Behaviors: [How they currently work]
• Needs/goals: [What they're trying to accomplish]
• Key circumstance: [What makes their situation distinct]

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3. Competitive Landscape

Market Position

[Blue ocean / red ocean / purple ocean? Brief assessment.]

Key Competitors

Gaps and Opportunities

[What customer needs are competitors not addressing well? Where is the market overserved?]

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4. Value Proposition

Statement

For [target customer segment] who [key need/job to be done], [product name] is a [category] that [key differentiator]. Unlike [primary alternative], we [primary advantage].

Value Innovation Strategy

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5. Opportunity Map

Opportunity Solution Tree

[Product Outcome]
├── [Opportunity 1]
│   ├── [Sub-opportunity 1a]
│   └── [Sub-opportunity 1b]
├── [Opportunity 2]
│   ├── [Sub-opportunity 2a]
│   └── [Sub-opportunity 2b]
└── [Opportunity 3]
    └── [Sub-opportunity 3a]

Prioritized Opportunity

Selected: [Leaf-node opportunity]

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6. Solution Direction

Solutions Under Consideration

Riskiest Assumptions

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7. Success Metrics

North Star

[Single metric capturing core value delivered]

Input Metrics

How We'll Measure

[Instrumentation plan — what events to track, what dashboards to build, what cohorts to compare]

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8. Risks and Mitigations

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9. Next Steps