Customer Jobs
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Evidence-aware customer-value fit workspace
Value Proposition Canvas
Map what you know about one customer segment separately from what you propose to offer-then identify which customer-value relationships still need evidence.
A complete canvas is a model of what you believe. It is not proof of customer value or product-market fit. CraftUp therefore treats fit as a hypothesis to test, not a canvas score.
One customer profile at a timeCustomer evidence ≠ solution evidenceFit links start untestedNo 0–100 FitScoreExports + local autosave + share
Framework attribution
The standard Value Proposition Canvas terms-Customer Jobs, Pains, Gains, Products & Services, Pain Relievers, and Gain Creators-are attributed to Strategyzer AG. CraftUp is an independent implementation with evidence-aware workflow additions; no Strategyzer affiliation, certification, or endorsement is claimed. Refer to Strategyzer's own resources for the original framework and current usage terms.
Original framework resource →Start with one customer profile
Segment and context
Define whose Jobs, Pains, and Gains you are mapping. Do not mix materially different users, buyers, administrators, or approvers into one profile.
Autosave uses this browser’s localStorage. Share URLs contain compressed canvas data and are not private; avoid participant PII or confidential strategy in a shared link.
What we believe / know about the customer
Customer Profile
Jobs, Pains, and Gains should describe the customer’s world independently of your proposed solution.
Pains
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Gains
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What we propose to do about it
Value Map
Products, relievers, and creators are solution hypotheses. They are not customer evidence, even when the Customer Profile is well supported.
Products & Services
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Pain Relievers
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Gain Creators
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Lines are claims to test
Fit hypotheses and link evidence
For each link, explain the mechanism and record evidence about whether the proposed value actually changes the customer outcome.
Link a Job, Pain, or Gain to the relevant Value Map item. Creating a link does not mark it as supported.
Coverage is not fit
Fit health, transparent states, no score
A canvas can map every important need and still have zero evidence that the proposed value changes a customer outcome. These diagnostics show what is missing without turning completeness into pseudo-precision.
Profile readiness
Customer Profile weak, mostly assumptions
Value-map readiness
Value Map is still an idea list
- Customer evidence gaps
- 0
- Important needs without a response
- 0
- Orphan value-map items
- 0
- Untested fit hypotheses
- 0
- Supported fit hypotheses
- 0
- Contradicted fit hypotheses
- 0
Primary reasoning output
Value Fit Hypotheses
These are deliberately written as hypotheses, not marketing claims. Customer evidence and solution evidence remain visible separately.
Add at least one fit link to generate a reasoning artifact.
10× derived asset
Value Fit Test Backlog
Prioritized qualitatively by focus, uncertainty, and contradictory evidence. There is no arbitrary risk score.
Add customer items, evidence, and fit links to derive the next learning work.
Customer first, value second, evidence throughout
How to use the canvas without manufacturing fit
1. Define one customer segment
Name the specific user, buyer, administrator, or other role whose Jobs, Pains, and Gains you are mapping. Keep materially different customer profiles separate.
2. Build the Customer Profile from evidence
Capture Jobs, Pains, and Gains as Observed, Inferred, Assumed, or Unknown. Add evidence source/context and optionally mark a few items as priority focus.
3. Build the Value Map separately
Add Products & Services, Pain Relievers, and Gain Creators as Proposed, Tested, Supported, or Weak solution hypotheses. Do not treat them as customer evidence.
4. Connect the two sides as hypotheses
Link Job → Product, Pain → Reliever, or Gain → Creator. Explain the proposed mechanism; a line starts as Untested, not proven fit.
5. Inspect gaps without a score
Review customer evidence gaps, important needs with no proposed response, orphan value-map items, untested links, supported links, contradictions, and deliberate non-fit.
6. Work the Value Fit Test Backlog
Turn the unresolved customer and solution assumptions into next-evidence cards instead of polishing marketing claims before the underlying value logic is strong enough.
The critical distinction
Strong customer evidence can coexist with zero solution evidence
Customer Profile
What we know or believe about the customer
Jobs, Pains, and Gains carry an evidence state: Observed, Inferred, Assumed, or Unknown, plus source/context.
Value Map
What the team proposes to do about it
Products, Relievers, and Creators are Proposed, Tested, Supported, or Weak. A well-supported pain does not make the proposed reliever supported.
Fit link
The relationship is a testable claim
State the mechanism, keep the link Untested until effect evidence exists, and record evidence that supports or contradicts it.
Coverage ≠ fit
A canvas can have 100% mapping coverage and 0 evidence of value
Coverage asks whether important customer needs have a proposed response. Fit asks whether evidence indicates that the proposed value actually changes the customer outcome. CraftUp reports the underlying gaps and link states directly instead of collapsing them into a percentage.
Quality checks
Keep the Customer Profile in the customer's world
Weak: solution-shaped customer truth
- Job: “Use our dashboard.”
- Pain: “Doesn't have our automation.”
- Gain: “Wants AI recommendations.”
These describe a solution or feature wish, not independent customer evidence.
Stronger: context and outcome first
- Job: understand which requests are blocked before weekly planning.
- Pain: describe the specific obstacle, consequence, or risk in context.
- Gain: describe a desired customer outcome, not the feature that might create it.
Only use specifics you can support. Otherwise keep the item Assumed or Unknown.
Artifact boundaries
Use the VPC for customer-value reasoning, not every discovery or strategy job
| Owner | Distinct job | Route |
|---|---|---|
| Customer Interviews | Gather real behavior, context, workarounds, and evidence. | Open → |
| Problem Statement | Frame one supported obstacle and consequence clearly. | Open → |
| JTBD | Go deeper on situation, motivation, desired progress, and alternatives. | Open → |
| Value Proposition Canvas | Map one customer profile to proposed value mechanisms and decide what fit evidence is missing. | Open → |
| Lean Canvas | Expand into broader business-model assumptions such as channels, revenue, costs, and advantage. | Open → |
| Product Strategy | Choose where to focus, why, what not to do, and how to allocate product bets. | Open → |
| Positioning / messaging | Communicate differentiated value after the underlying evidence is strong enough for that claim. | Open → |
Route by what is still uncertain
Choose the next tool from the evidence state, not from a generic tool wall
Customer Profile is mostly assumptions
Do customer discovery before claiming fit.
Build an interview guide →One problem is still fuzzy
Frame the obstacle, context, workaround, impact, and evidence.
Frame the problem →A job needs deeper progress context
Use JTBD to explore situation, motivation, and desired progress.
Deepen the job →Customer need is supported but the Value Map is untested
Design evidence for whether the proposed mechanism changes the outcome.
Plan validation →Several opportunities compete
Structure opportunity/solution options before deciding what to invest in.
Map opportunities →You need a build/investment decision
Bring strategy, effort, evidence, opportunity cost, and risk into prioritization.
Prioritize →You need the broader business model
Move beyond customer-value fit into the other business assumptions.
Open Lean Canvas →Practical guidance
Evidence-aware VPC tips
- Define one meaningful customer segment and context before adding value-map ideas. Separate materially different users, buyers, administrators, or approvers into different canvases when their jobs differ.
- Write the Customer Profile from customer evidence or clearly labeled assumptions. Do not reverse-engineer jobs, pains, or gains from features you already want to build.
- Use Observed for direct evidence, Inferred for your interpretation, Assumed for an unsupported belief, and Unknown when you genuinely do not know yet.
- Priority focus is optional and means 'pay attention here', not 'the framework requires exactly three'. Add a rationale so teammates can challenge why an item matters.
- A Pain Reliever or Gain Creator is a proposed mechanism. Even with strong customer evidence, the mechanism remains untested until solution evidence exists.
- Treat every line between the Customer Profile and Value Map as a fit hypothesis. Record the proposed mechanism and the evidence that supports or contradicts it.
- Mark lower-priority needs as Not targeting when they are deliberately outside the proposition. A focused value proposition does not need to cover every customer need.
- Use the Value Fit Test Backlog to decide what to learn next. Test important weak assumptions before polishing copy or expanding the feature list.
- Keep participant PII and confidential strategy out of share URLs. Shared canvas data is encoded into the URL, not protected as a private workspace.
Anti-patterns
Common Value Proposition Canvas mistakes
Customer jobs or gains name your dashboard, AI feature, app, or button.
Why: The Customer Profile was reverse-engineered from the solution.
Fix: Rewrite the item in the customer's world: progress, obstacle, consequence, or desired outcome. If you only have a guess, keep it Assumed.
Everything is linked, so the team says the canvas proves fit.
Why: Coverage has been confused with evidence of effect.
Fix: Treat links as hypotheses. Add mechanism and solution evidence, then use the transparent supported/untested/contradicted counts rather than a fit score.
One quote or data point becomes 'validated'.
Why: Evidence strength and epistemic state are collapsed into a binary label.
Fix: Record what was observed, distinguish inference from observation, and keep the evidence source/context visible. Avoid universal truth claims.
The Value Map is a feature backlog with no customer rationale.
Why: Solution ideas were added without tracing them to a selected customer need.
Fix: Review orphan value-map items. Link them only when a real customer rationale exists; otherwise defer or remove them instead of inventing a matching pain.
Every pain and gain is treated as mandatory scope.
Why: The canvas rewards maximum coverage instead of strategic focus.
Fix: Use priority focus and Not targeting. Important uncovered needs may be opportunities, but they can also be intentional non-fit.
The same canvas mixes end users, buyers, admins, and approvers with different jobs.
Why: A market or account was treated as one customer profile.
Fix: Choose one meaningful segment/role context per canvas and create separate profiles when customer jobs materially differ.
Marketing copy is treated as the primary output before fit mechanisms are tested.
Why: Canvas completion is being converted into claim certainty.
Fix: Use the Value Fit Hypotheses and Test Backlog first. Move into positioning or messaging only when the underlying customer and solution evidence is strong enough for that decision.
Decision questions
Value Proposition Canvas FAQ
What is the difference between the Customer Profile and the Value Map?
The Customer Profile describes the selected customer's world: Jobs, Pains, and Gains. The Value Map describes what your team proposes to offer through Products & Services, Pain Relievers, and Gain Creators. CraftUp keeps their evidence semantics separate because strong evidence that a customer pain exists does not prove that your proposed reliever changes that pain.
Does completing a Value Proposition Canvas validate product-market fit?
No. A completed canvas records a model of customer needs and proposed value. Links show what you believe may fit; they do not prove willingness, adoption, differentiation, retention, or product-market fit. CraftUp therefore does not calculate a numerical FitScore. It shows evidence gaps, uncovered important needs, orphan value-map items, and supported, untested, or contradicted fit hypotheses.
What do Observed, Inferred, Assumed, and Unknown mean?
Observed means the item is supported directly by the current evidence you record. Inferred means it is your interpretation of evidence rather than the observation itself. Assumed means the team believes it but has not yet supported it. Unknown is useful when the question is still open. None of these labels means the statement is universally true for every customer.
What do Proposed, Tested, Supported, and Weak mean on the Value Map?
Those labels describe the current state of a solution hypothesis, not customer truth. Proposed means the mechanism has not been tested. Tested means you have exercised it and should record what happened. Supported means current evidence increases confidence that the mechanism affects the intended outcome. Weak means current evidence does not support it well enough for the present decision.
What does a fit link mean?
A fit link is a hypothesis connecting one customer item to one value-map item: for example, a Pain to a Pain Reliever. Add the proposed mechanism so teammates can see how the effect is supposed to happen. Then record link-level evidence and mark it Untested, Supported, or Contradicted. A line on the canvas by itself is not causal evidence.
Do I need exactly three Jobs, Pains, and Gains?
No. CraftUp keeps an optional 'priority focus' marker for up to three items in each Customer Profile section because focus is useful, but three is not a correctness rule. A strong canvas can contain only a few meaningful customer needs. Add a priority rationale and leave lower-value items unselected or mark deliberate non-fit rather than filling boxes for completeness.
How should I use the Value Fit Test Backlog?
The backlog is derived from the most consequential uncertainty visible in the canvas: priority customer items with weak evidence, untested or contradicted fit links, and value-map ideas with no customer rationale. Each card states the hypothesis, what is currently known, the biggest uncertainty, useful next evidence, a possible method, and what result would weaken the hypothesis. It is guidance, not a universal research recipe.
How do autosave, exports, and share links handle my data?
The tool autosaves canvas state in your browser's localStorage and exports files locally through the browser. A share link encodes the canvas state into the URL so another browser can reconstruct it; anyone with that link can read the included data. Avoid participant PII or confidential product information in shared URLs. Tool analytics record action metadata such as mode and export format, not canvas text.
Is CraftUp affiliated with Strategyzer?
No affiliation or endorsement is claimed. The standard Value Proposition Canvas terminology is attributed to Strategyzer AG. CraftUp is an independent evidence-aware implementation that adds evidence states, fit-hypothesis records, transparent diagnostics, and a test backlog. For the original framework material and current usage terms, refer to Strategyzer's own published resources.
Direct workflow handoffs
Customer assumptions dominate
User Interview Script Generator →One obstacle needs clear framing
Problem Statement Generator →A job needs deeper situation/progress context
JTBD Statement Generator →Several opportunities or solution paths need structure
Opportunity Solution Tree →You must decide what to invest in next
Product Prioritization →You need the broader business-model assumptions
Lean Canvas →Go deeper
Privacy, persistence, and sharing
Autosave stores the current canvas in this browser's localStorage. Exports are created from the current browser state. Share URLs contain a compressed copy of the canvas in the URL so another browser can reconstruct it; anyone with the URL can read that content. Avoid participant PII or confidential product strategy in shared links. The VPC analytics events in this implementation record action metadata such as mode and export format, not canvas text.
Freshness
Last updated: 2026-09-16
- Replaced the numerical FitScore and binary Assumption/Validated model with separate customer-evidence, value-map test, and fit-link evidence states.
- Added explicit customer segment/context, link mechanisms and evidence, intentional non-fit, profile/value readiness, transparent gap diagnostics, and a Value Fit Test Backlog.
- Replaced automatic marketing hero copy with Value Fit Hypotheses, rewrote examples as clearly synthetic teaching cases, and added safe v1 share/local-storage migration.