Before deciding what FoxyInvoice should do, its team needs evidence that a specific group of people has a consequential problem—and that a feasible solution can support a viable business. Treat the product’s audience, workflow, features, price, and claims as hypotheses until customer research supports them. Discovery is not a kickoff exercise or a way to justify a decision already made; it is ongoing work that informs what to build and how to explain it.
Start with a customer problem, not a product pitch
Product discovery helps a team identify real customer needs, choose worthwhile problems, and refine possible solutions using evidence. Aha! describes discovery as ongoing work to identify customer needs and deliver appropriate solutions, while Atlassian frames it as research and testing that continue alongside product delivery (Aha!; Atlassian).
For FoxyInvoice, that means not assuming that its name establishes who it serves, what invoicing workflow it supports, or which features customers need. Begin with the people and situations in question. Digital.gov defines pain points as “real or perceived problems experienced by customers within a system.” That system can include a customer’s tools, handoffs, policies, and workarounds—not just a screen or feature (Digital.gov).
Use questions that reveal context and consequence:
- Who experiences the problem, and who decides whether to pay to address it?
- Where and when does it occur? How often does it happen?
- What happens if it is not resolved, and how costly or disruptive are those consequences?
- What do people do now—including manual work, existing tools, or simply tolerating the problem?
- What would make a solution valuable enough to adopt, and what might prevent adoption?
Look beyond the first feature request. A request describes one person’s proposed answer; discovery should examine the underlying need, root cause, touchpoints, and important moments. Useful evidence may already exist in support conversations, product analytics, sales notes, or other customer feedback, alongside new interviews and experiments.
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Run small tests that can change a decision
Research is useful when it can alter what the team does next. Write down an assumption, identify what evidence would weaken or strengthen it, and choose a test suited to that uncertainty. A test might be a customer interview about a recent experience, an analysis of support records, a prototype task, or a small experiment that measures an observable behavior.
- State the assumption. For example: “A particular kind of customer regularly loses time resolving a specific invoicing-related problem.” Keep this as a hypothesis, not a FoxyInvoice fact.
- Choose evidence that addresses it. Ask about recent concrete situations and current workarounds, rather than only asking whether someone likes an idea or would buy it.
- Set the decision in advance. Specify what finding would lead the team to proceed, change the concept, investigate further, or stop.
- Collect and compare evidence. Look for patterns across relevant customer accounts and existing data, as well as evidence that contradicts the idea.
- Update the choice. Record what was learned, what remains uncertain, and which next action follows.
There is no universal interview count, survey sample size, or validation threshold established by the cited guidance. The appropriate amount of evidence depends on the decision, the consequences of being wrong, and how directly the test addresses the assumption. For practical advice on conducting customer conversations without steering them toward a preferred answer, see Rob Fitzpatrick’s The Mom Test; the book can inform interviews, but it cannot validate a product by itself.
Strategyzer reports that one enterprise client found no customer interest in a planned software idea and says the client avoided $800,000 in planned development spend after changing direction. That is a provider-reported anecdote, not a general estimate of savings or independently verified causal evidence (Strategyzer).
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Separate desirability, usability, feasibility, and viability
Positive reactions to an idea do not answer every product question. Assess different risks separately so that one kind of evidence does not stand in for another:
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1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problems- Desirability: Do people have this need, and would the proposed outcome matter enough to change what they do?
- Usability: Can intended users understand and use the proposed solution to complete the task?
- Feasibility: Can the team build, operate, and support it with available technical and organizational capabilities?
- Viability: Can the product serve customers sustainably within the business’s economics and constraints?
These questions call for different evidence. A conversation may uncover a real need but cannot, by itself, prove that a solution is usable, technically feasible, or commercially sustainable. As discovery continues during delivery, new customer, market, and operational evidence may require the team to revise its assumptions.
Compare candidate problems before committing
When several possible problems compete for attention, compare them using the same factors. This is a decision aid synthesized from the cited guidance, not a validated scoring formula; a high score in one area should not conceal a serious weakness in another.
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| Factor | Questions to investigate |
|---|---|
| Need | How frequent and severe is the problem? What are the consequences of the current workaround? |
| People and buyer | Who experiences it, who influences a solution, and who would pay? |
| Access to evidence | Can the team reach relevant people and examine useful feedback or behavior? |
| Alternatives | What tools, services, manual processes, or workarounds already address it? |
| Solution potential | Could a feasible solution improve the situation in a way customers value? |
| Business potential | Could the product deliver that value sustainably at a price the market will support? |
Keep track of uncertainty as well as apparent opportunity. If the team cannot yet identify the buyer, establish the severity of the need, or explain how the proposed solution differs meaningfully from alternatives, those are research questions—not reasons to fill gaps with confident product claims.
Set a price using value, demand, and cost
A defensible price must make sense to customers and to the business. McKinsey’s pricing guidance describes two important boundaries: customer value informs a price ceiling, while the cost of delivering the product and the return the business requires inform a price floor. Demand across different prices matters too. A price customers say they would accept is not enough if it cannot support the business; a cost-based price is not enough if customers do not perceive corresponding value (McKinsey).
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Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteResearch the benefits customers receive, including outcomes the team may not anticipate. McKinsey’s example of a valve supplier illustrates why: open questions about customers’ maintenance economics produced a different willingness-to-pay result than beginning with a comparison to another valve. It is an illustrative case, not a universal effect size or a price benchmark.
For a new product, work through these questions:
- Estimate customer value. What measurable or perceived benefit does the solution provide, and to whom? Treat the value ceiling as an evidence-based estimate, not a price customers are guaranteed to pay.
- Estimate demand at alternative prices. Investigate how demand may change across price points rather than relying on one stated willingness-to-pay answer or assuming that the cheapest option will win.
- Calculate the cost floor. Include the full relevant unit costs and allocated costs of delivery, plus the minimum return the business requires.
- Check market and business fit. Assess whether likely demand at a defensible price can support those costs and the intended return.
- Revise when the boundaries do not meet. If the market will not support the cost-informed floor, reconsider the product, delivery model, or business model rather than relying on an unsupported forecast.
Competitor prices can inform the context customers use to compare offers, but they are not a complete pricing strategy. Nor is cost-plus pricing or a single survey response sufficient on its own. Pricing research should test the assumptions that connect value, demand, costs, and the return the business needs.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Position the product around an evidenced difference
Positioning, value proposition, and messaging are related but distinct. Atlassian describes positioning as the product’s place in the market and the perception the team aims to create relative to alternatives. The value proposition names the customer benefits; messaging communicates those benefits to a particular audience through a particular channel (Atlassian).
Before writing public copy for FoxyInvoice, establish what evidence supports each element:
Best Value
- If you want to build a better future, you must believe in secrets.
- The great secret of our time is that there are still uncharted frontiers to explore and new inventions to create. In Zero to One, legendary entrepreneur and investor Peter Thiel shows how we can find singular ways to create those new things.
- Audience: Which specific customers does the offer serve?
- Problem: Which consequential need or situation does it address?
- Alternatives: What do those customers use or do instead?
- Outcome: What meaningful result can the product credibly help them achieve?
- Difference: What is distinct about that result or approach, and what supports the claim?
A working positioning statement can make the strategy explicit: “For [defined audience] who [face a specific problem], FoxyInvoice helps [achieve an evidenced outcome], unlike [relevant alternatives] because [supported difference].” Keep it internal until the bracketed claims have evidence; it is a structure for thinking, not proof of product-market fit.
Translate product capabilities into customer outcomes only when the connection is supported. Avoid claims of uniqueness unless the team has checked the alternatives customers actually consider. Salesforce’s go-to-market guidance likewise emphasizes research into customers and competitors and connecting customer problems to solutions (Salesforce).
Keep a decision record as the product changes
Discovery remains useful after an initial build: customer needs, market conditions, and product evidence can change. Keep a shared record of assumptions, evidence, decisions, and open questions so that product, design, engineering, and commercial teams can see why priorities or positioning change. Atlassian’s Jira Product Discovery is one optional example of a shared workspace for capturing ideas and evidence alongside delivery status; a tool can organize discovery, but it cannot supply the customer evidence (Atlassian).
Quick Recap
- Can the team name the customer and situation behind the problem?
- Has it investigated frequency, severity, consequences, and current alternatives?
- Can it explain what evidence would change the decision and what the evidence currently shows?
- Have desirability, usability, feasibility, and viability been considered as separate questions?
- Does the pricing rationale account for customer value, demand, full delivery costs, and required return?
- Does the positioning describe a specific audience, problem, alternative, and evidenced outcome?
- Are FoxyInvoice’s segment, workflow, features, price, and public claims still marked as hypotheses wherever evidence is missing?
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