ux-strategy

name	UX Strategy
description	Connect design decisions to business outcomes through competitive analysis, opportunity mapping, Jobs to Be Done, outcome-driven discovery, value proposition design, and UX metrics. Shape product direction with strategic frameworks grounded in evidence.

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:

Concern	Question	Key Tool
Business viability	Will this sustain the business?	Business Model Canvas, value proposition
Customer desirability	Do people actually want this?	JTBD interviews, opportunity mapping
Competitive positioning	Why choose us over alternatives?	Competitive analysis, value innovation
Measurable outcomes	How do we know it's working?	HEART framework, North Star metric

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

Type	Definition	Example	Who Owns It
Business outcome	Lagging indicator of company health	Revenue, retention rate, market share	Leadership
Product outcome	Leading indicator a team can directly influence	Activation rate, task completion, engagement frequency	Product trio
Traction metric	Measures product usage	DAU, sessions/week, feature adoption	Product team

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

Bad (solution in disguise)	Good (opportunity)
"We need a dashboard"	"I can't see how my project is tracking"
"Users want notifications"	"I miss important updates because I don't check the app daily"
"Add a search filter"	"I waste time scrolling through results that don't match what I need"

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:

Dimension	Question
Opportunity sizing	How many customers face this? How often?
Market factors	How does this relate to competitive dynamics?
Company factors	Does this align with strategy, strengths, resources?
Customer severity	How painful is this? What workarounds exist?

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

Element	Description	Example
Main job	The overall functional objective	"Prepare a meal for my family"
Related jobs	Adjacent objectives significantly different from the main job	"Clean up after cooking"
Emotional jobs	How people want to feel	"Feel confident I'm feeding them well"
Social jobs	How people want to be perceived	"Be seen as a good host"

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:

Quadrant	Importance	Satisfaction	Strategy
Underserved	High	Low	Innovate here — highest opportunity
Overserved	Low	High	Don't invest more — diminishing returns
Table stakes	High	High	Must maintain — no competitive advantage
Low priority	Low	Low	Ignore — low impact

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):

Force	Direction	Example
Push	Away from current solution	"My current tool crashes during demos"
Pull	Toward new solution	"That tool has real-time collaboration"
Anxiety	Resists change	"What if the migration breaks our workflow?"
Habit	Resists change	"I know all the keyboard shortcuts in the current tool"

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)

Type	Description	Example
Direct	Same value proposition to same customers	Figma vs. Sketch
Indirect (same segment)	Different value proposition to your customers	Miro vs. Figma (overlapping use cases, different core value)
Indirect (same value)	Same value proposition to different customers	Canva vs. Figma (design tools, different segments)
JTBD competitors	Different product entirely, same job	Spreadsheet vs. project management tool (both hired to "track project progress")

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)

Type	Question
Desirability	Will customers want this? Will they choose it over alternatives?
Viability	Does this work for the business? Can we sustain it?
Feasibility	Can we build this? Do we have the capability?
Usability	Can customers figure out how to use this?
Ethical	Could this cause harm? Are there unintended consequences?

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

Tool	Best For	Speed	Cost
Story-based interviews	Desirability, understanding current behavior	1 week	Low
Smoke test / landing page	Desirability at scale	1-2 weeks	Low-Medium
Wizard of Oz	Feasibility of automation (simulate with humans)	1-2 weeks	Medium
Concierge test	Desirability of value proposition (deliver manually)	2-4 weeks	Medium
One-question survey	Specific assumptions at scale	Days	Low
Data mining	Behavioral patterns in existing product	Days	Low
Prototype test	Usability, concept validation	1-2 weeks	Medium
A/B test	Solution comparison at scale	2-4 weeks	Medium-High

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)

Category	Measures	Example Metrics
Happiness	Satisfaction, perceived ease, NPS	Task satisfaction score, CSAT, SUS
Engagement	Depth and frequency of use	Sessions/week, features used, time in core workflow
Adoption	New users, feature uptake	Signups, first-time feature usage, onboarding completion
Retention	Users who come back	Day-7 retention, monthly active %, churn rate
Task success	Efficiency and effectiveness	Completion rate, time-on-task, error rate

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

Product Type	North Star Example
Marketplace	Transactions completed per week
SaaS tool	Weekly active teams using core feature
Content platform	Quality content consumed per user per week
Communication app	Messages sent per user per day

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)

Phase	Activities	Key Output
1. Frame	Define business context, set desired outcome, identify constraints	Strategy brief
2. Discover	Customer interviews, JTBD research, experience mapping	Opportunity map / OST
3. Analyze	Competitive analysis, market positioning, underserved needs	Competitive findings brief
4. Define	Value proposition, prioritized opportunities, success metrics	Strategic direction document
5. Validate	Assumption testing, prototype experiments, smoke tests	Validated/invalidated hypotheses
6. Measure	Instrument product, track outcomes, close feedback loop	Metrics dashboard, learning log

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:

Dimension	Question	Red Flag
Harm	Could this cause harm to users, non-users, or communities — even unintentionally?	Dark patterns, addictive loops, data exploitation, exclusion of vulnerable populations
Access	Who benefits and who is excluded? Are we designing for the people who need this most, or only the most profitable segment?	Product only works for affluent, tech-savvy, English-speaking, able-bodied users
Sustainability	Does this contribute to or extract from the broader ecosystem? What happens at scale?	Winner-take-all dynamics, environmental cost, depletion of shared resources

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?"

Traditional Value	Shared Value
Maximize profit per customer	Create value that grows the total market
Extract attention and data	Provide genuine utility that earns trust
Compete for existing demand	Expand access to create new demand
Optimize for engagement metrics	Optimize for user outcomes

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:

Test	How to Run It	What It Reveals
Pre-mortem	Ask: "It's one year from now, and this product has caused harm. What happened?" Brainstorm failure modes	Unintended consequences you haven't considered
Worst-case user	Identify the most vulnerable person who might use this. Design for them	Edge cases that become ethical issues at scale
Misuse scenario	Ask: "How could a bad actor exploit this?" Map abuse vectors	Security, privacy, and manipulation risks
Exclusion audit	List who cannot use the product and why (disability, language, cost, infrastructure, literacy)	Access barriers that limit both market and impact
Long-term incentive check	Ask: "If this succeeds, what behavior does it incentivize over 5 years?"	Whether success creates healthy or extractive dynamics

Integrating Ethics into the Strategy Process

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

Strategy Phase	Ethical Integration
Frame	Include "Who could be harmed?" alongside "Who benefits?" in the strategy brief
Discover	Interview underserved and excluded users, not just primary personas
Analyze	In competitive analysis, note where competitors exploit users — this is a differentiation opportunity
Define	Add at least one ethical assumption to the leap-of-faith list
Validate	Run at least one test with a vulnerable or underserved user group
Measure	Track harm indicators alongside success metrics (support complaints, accessibility scores, exclusion rates)

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Common Mistakes

Mistake	Why It Fails	Instead
Skipping competitive analysis	Build something the market already has, or miss a critical differentiator	Research 10-15 competitors before ideating
Defining strategy as a feature list	Features are outputs. Strategy is about outcomes and positioning	Start with the outcome, then discover opportunities, then ideate solutions
Only researching direct competitors	Miss JTBD competitors and substitutes	Include indirect and job-level competitors
Setting metrics after launch	No baseline. Can't measure improvement	Define success metrics during strategy phase
Treating strategy as a one-time document	Strategy goes stale as market and customers change	Continuous discovery — weekly interviews, quarterly strategy reviews
Asking customers what to build	Customers describe problems well but design solutions poorly	Ask about behavior and pain points. Design solutions yourself
Optimizing a metric without understanding the job	Metric gaming — improving numbers without improving customer experience	Tie every metric to a job outcome

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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