What if the product idea you’re excited about… just doesn’t matter to your customers?
It’s more common than it seems.
According to CB Insights, 42% of startups fail because there’s no market need. That makes it the most frequent reason startups don’t succeed.
Often, idea validation is rushed or based on limited data. Some teams jump straight into development and then struggle to bring the product to market. They can’t explain the value proposition, or find people who actually need this product or service.
The frameworks and research methods in this guide will help you validate:
- Products (new or existing)
- Value proposition
- Features
- Pricing models
- App ideas
- Startup ideas
- Product concepts
- Service and business ideas
- New product lines
- Product & service assumptions
This is a practical guide to validate product-market fit before writing code or hiring a team. The approach is based on real projects from Craft Innovations’ work in fintech – including cases in banking, payments, loyalty programs, and digital services.
What Is Product-Market Fit?
You can always feel when product-market fit isn’t there.
And you can also feel it when it is there.
That’s how Marc Andreessen described it back in 2007.
You can always feel when product-market fit is not happening. The customers aren’t quite getting value out of the product, word of mouth isn’t spreading, usage isn’t growing that fast, press reviews are kind of ‘blah,’ the sales cycle takes too long, and lots of deals never close.
And you can always feel product-market fit when it is happening. The customers are buying the product just as fast as you can make it – or usage is growing just as fast as you can add more servers.
But feelings alone aren’t enough ❗
At Craft Innovations, we look at product-market fit as something measurable:
Product-market fit is when your target customers choose your product at the price you offer, because they see it as the best option to solve their need – and the gross profit from sales covers both your CAPEX and OPEX.
Thus, you achieve product-market fit when:
- Gross profit from sales covers capital expenses and operational expenses.
- The market size is large enough to make the product viable.
- Customer acquisition cost (CAC) is at least 3 times < the lifetime value (LTV).
This is the balance we’re looking for. Instead of jumping into MVP development, we validate a product idea with a following flow:
- Need validation and market estimation
- Prototype design and business model
- Concept validation and feature prioritization
- Only then – MVP, user feedback, go-to-market, and iteration
Product-Market Fit Pyramid: Product Validation Framework
Having a “great idea” doesn’t mean you can find product-market fit.
The Product-Market Fit Pyramid is one of the best product validation techniques — a framework that breaks product validation into 4 clear layers. It moves from strategic questions at the top to tactical execution at the bottom to validate product ideas based on actual user needs.
If you’re wondering where to start: always start from the top. Validate the need first. Execution matters, but only if you’re solving the right problem.
This idea validation framework works for new products and individual features alike so you don’t test everything at once.
1. Target Market & Customers
- Does the problem exist in people’s lives?
- Is it something they experience often – and care enough to solve?
This is where validation starts. Without a real problem, there’s no need to build anything.
2. Value Proposition
- What can we offer as a better way to solve the problem?
- Why would users choose your product over current alternatives?
This step is about testing your solution – not the whole product, just the idea behind it.
3. Feature Level
- What needs to be built for users to feel the benefit?
- Will our features work as expected for the user?
Here, you validate what to build – and what not to.
4. User Experience
- Is the product intuitive?
- Does it reduce friction?
- Will users keep coming back?
Even great features won’t matter if people can’t use them easily. This level helps test whether people will keep using the product long enough to cover acquisition costs and grow LTV.
1. Problem Validation in Target Market
We break down the problem validation process into 4 parts:
- Problem assessment
- Problem discovery
- Discovery results analysis
- Common discovery mistakes
1.1 Problem – Assessment
Before jumping into solutions, it helps to assess whether the problem is frequent, painful, and widespread enough to justify building something new.
We use four core metrics to validate the problem:
| Metric | Benchmark |
|---|---|
| % of target users reporting the problem | At least 40% |
| Frequency of problem occurrence | Appears weekly or more often |
| Level of “pain” | At least 7/10 |
| % using workarounds/manual solutions | Over 45% |
How many people face the problem?
Start with volume. If at least 40% of your target users say they experience this issue in their lives, that’s already a strong sign. You’re not building for the edge cases – you’re addressing something real for a sizeable group.
How often does it happen?
Frequency matters. If a problem only shows up once a year, users might just work around it and move on. But if it happens weekly – or more often – it becomes part of their routine. That’s when they’re more likely to pay for a solution.
Still, not all problems need to be frequent to be important. Some issues, like rent payments or taxes, show up once or twice a month – but they carry serious financial or emotional weight. These are still valid targets.
How painful is it?
Next, measure intensity. Use a simple 1-to-10 scale, where 1 means “barely noticeable” and 10 is “extremely painful.” If the average score lands above 7, that’s another signal you’re onto something important.
Are people using workarounds?
When users are building workarounds, it usually means current solutions aren’t cutting it. Some might be using complex Excel files. Others combine multiple tools like Zapier, Notion, or Google Forms to create custom flows. If more than 45% of users are doing this, there’s likely space for a better, purpose-built product.
***
These 4 indicators – breadth, frequency, pain level, and workaround behavior – help validate product ideas before moving forward. If a problem checks most of these boxes, it’s a strong candidate for product development.
1.2. Problem – Discovery
To understand the problem, talk to real people – not just personas. Here are 5 common research methods we use:
- In-depth interviews
- Quantitative surveys
- Ethnographic research
- On-site or in-context studies
- “Moccasins” discovery (experience the problem firsthand)
Talk to people
In-depth interviews are still one of the most reliable ways to uncover real user pain points. One-on-one conversations help reveal behaviors, habits, and unmet needs that users might not even realize they have. To back this up with data, you can run quantitative surveys – for example, to measure how often a problem appears or how many people are affected by it.
Observe behavior
Talking to people gives you stories. Watching them gives you context. Ethnographic research – observing people as they use tools or perform tasks – shows what they actually do (not just what they say). This is especially useful when you’re trying to uncover manual workarounds and fragmented tool use.
Walk in their shoes
In some cases, it helps to go one step further and experience the problem yourself. We call this the “moccasin” approach – trying to complete the same task your target users struggle with, using their current tools and methods. This hands-on experience often highlights friction points that interviews and surveys can miss.
***
Together, these methods form a strong foundation for validating product ideas. They help you reveal unmet needs, workarounds, and moments of friction in real-life context.
1.3. Problem – Discovery Results Analysis
What should you get out of this discovery work?
A good problem validation process will give you:
A prioritized list of needs
Focus on recency and painfulness. What problems came up most often, and which ones felt the most urgent to users? These should rise to the top.
Specific user struggles with current solutions
Where exactly are people getting stuck? What do they try to do – and where does it fall apart? This helps clarify the weak points in existing tools or workflows.
Success metrics that matter to users
How do users define a successful outcome? For some, it’s saving time. For others, it might be reducing stress, staying compliant, or simply getting through a task without frustration. Understanding these metrics helps shape your future value proposition.
The cost of success
How much time, money, or effort are users spending just to get the job done with their current setup? This cost – emotional or financial – is key input for pricing later on.
Barriers to change
Even if your product is better, switching isn’t always easy. Users might be locked into existing platforms, workflows, or contracts. Migration could take hours or cost thousands. Identifying these blockers early helps you plan how to reduce friction and support adoption later.
This kind of structured output helps you move from vague user feedback to specific, validated product ideas. It’s also what allows you to estimate market value, forecast adoption, and build features that solve real problems – not just hypothetical ones. And ultimately, it gives you the clarity you need to find product-market fit with confidence.
1.4. Problem – Common discovery mistakes
Even with the best intentions, it’s easy to collect misleading data – or worse, none at all. Here are the most common mistakes we see when teams try to validate product ideas through discovery research.
Talking to the wrong people
You need feedback from your real users – not just anyone. If the people you’re interviewing don’t match your target personas, the insights you get won’t reflect the actual market. This is especially important when selecting participants for in-depth interviews or observation sessions.
Relying on friends and family
They mean well. But they’re also more likely to support your idea, avoid criticism, or not challenge your assumptions. That’s not validation – that’s comfort. Get outside your circle and talk to people who don’t owe you encouragement.
Pitching instead of listening
In early interviews, your job isn’t to sell – it’s to understand. When you start pitching your solution too early, users can’t clearly picture what you mean. Without a working prototype, it’s nearly impossible for them to give honest feedback. Focus on listening, not convincing.
Not talking to enough people
One or two interviews won’t give you patterns. Our benchmark is around 8 to 12 interviews per persona or segment to reach insight saturation – that’s when over 80% of insights start to repeat. This helps avoid making decisions based on outliers.
Make sure you also account for segment diversity – geography, industry, tech stack, level of experience – they all affect how people experience the same problem.
Not quantifying the problem
Qualitative data is powerful, but it’s not enough on its own. If you skip quantification, you can’t estimate the size or cost of the problem. That leaves you with guesswork when it comes to pricing, feature prioritization, or business viability.
Done right, discovery helps you validate product ideas before writing code. Done poorly, it can send you in the wrong direction fast.
2. Value Proposition Testing and Validating
Let’s say you’ve already confirmed there’s a real need in the market. The next step is to check whether the solution you’re offering is actually what customers want. This is where value proposition validation comes in.
You’re not testing a full product here – you’re testing whether people want what you’re promising.
There are a few key metrics that help validate product ideas at this stage:
| Metric | Benchmark |
|---|---|
| % of users who say they’d use the product | Over 50% in surveys or landing page traffic |
| CTR or concept test conversion | 20–30% CTR or sign-up on prototype/test pages |
| Early access/demo requests | Over 25% of target audience |
| Engagement (with prototype/demo/video) | Comparable to direct competitors or your best-performing product |
These signals tell you whether your idea connects – not in theory, but in practice.
2.1 Prototype Early – Even Rough Is Fine
To get real user feedback, you need something tangible. A sketch, a mockup, or even a few clickable screens. It doesn’t have to be final – it just needs to help users understand the logic and potential value of what you’re offering.
Today, there’s no excuse to delay. AI tools like Lovable, Readdy, and Builder make it easy to create mid- to high-fidelity prototypes that look and feel like real products – without writing a line of code.
You can use:
- Sketches or drawings for basic flows
- Clickable prototypes in tools like Figma
- Interactive demo pages or test sites
The earlier you share these prototypes, the sooner you’ll understand which parts of the idea users actually care about.
2.2 Test Purchase Intent with Ads and Landing Pages
Another way to validate your value proposition is to simulate real buying behavior. You don’t need a product – just a page and a clear call to action.
Use landing pages, pre-order forms, or demo booking pages with clear CTAs like:
- Pre-order / Join waitlist
- Book a demo
- Get a quote
- Sign up / Download
- Buy now
- Message us
Pair this with targeted ads or social media posts to drive traffic and measure interest. Track metrics like:
- Engagement
- Cost per action
- Number of leads
- Conversion rate
- Customer acquisition cost (CAC)
This helps you understand whether people are just curious – or ready to act.
***
The goal of this stage is simple: validate product-market fit signals as early as possible. If you can show that people want what you’re offering – and are willing to take action – you’re ready to move forward.
3. Feature and Monetisation Validation
Let’s say you’ve already validated the need and value proposition. Now it’s time to go one level deeper: which features should make it into the MVP, and what are people actually willing to pay for?
This chapter covers frameworks, benchmarks, and research methods used in product testing and validation — helping you prioritize features and define pricing before building anything.
There are three key metrics that help you validate monetisation potential at this stage:
| Metric | Benchmark |
|---|---|
| % willing to pay target price | > 25% of users say yes to realistic pricing |
| % accepting a paid pilot or pre-order | Up to 15% from outreach or beta waitlist |
| Expected monthly revenue per user (ARPU) | Enough to cover CAC by 2–3x within 6–12 months |
These numbers are particularly useful for B2B and fintech SaaS models, where revenue per customer plays a huge role in business model viability.
3.1 Concept Testing
When you have multiple product concepts or features to consider, concept testing is a simple way to compare them side by side.
You show users several options – different features, combinations, or even competitor offers – and track their responses across:
- Attention
- Interest
- Purchase intent
- Price perception
- Needs fit
- Likeability
You can also include competitors in the mix – to benchmark your positioning and better understand what stands out to customers.
3.2 Kano Model
To understand how users feel about specific features, use the Kano model. This method helps you identify which features:
- Are expected by default
- Delight users when present
- Don’t make a difference
- Or actually hurt the experience
You simply ask: “How would you feel if [your product] had [this feature]?”
And let users choose from:
- I love it
- I expect it
- I wouldn’t care
- I can tolerate it
- I wouldn’t be happy
3.3 Feature Prioritisation Matrix
After running a Kano survey, features can be grouped into four categories:
- Must-Haves: Expected by default (e.g., “clear sound” in video calls)
- Performance Features: The better they’re done, the better the experience (e.g., fast loading, HD video)
- Attractive: Optional but create a “wow effect” (e.g., emoji reactions, webinars for 1000+ people)
- Indifferent: Don’t affect user satisfaction – often safe to deprioritize
This helps you avoid overbuilding and focus your MVP on what actually matters.
3.4 Conjoint / Brand Conjoint Analysis
When you want to simulate real-world decision-making, conjoint analysis lets you test how customers value combinations of product features.
Each participant compares multiple versions of your product – each with different attributes (like monthly fee, cashback, transfer fees). From this, you learn which features have the biggest impact on decision-making.
With conjoint analysis you’ll get:
- Feature mix prioritisation
- Price perception
- Simulated market share projections
3.5 Van Westendorp’s Price Sensitivity Meter
This method helps define a psychological price range.
What price would make this product feel…
- Too expensive to consider?
- Starting to feel expensive?
- Great value for money?
- Too cheap to trust the quality?
Customers provide a dollar value for each, and from this you get the optimal pricing window. The intersection point – where people feel it’s not too cheap, not too expensive – is your optimal price.
Below you can see Van Westendorp’s Price Sensitivity Meter from one of Craft Innovations’ projects.
3.6 Gabor Granger Pricing Method
If you already have a price range in mind but want to find the exact price point with the best potential, use Gabor Granger.
Ask users whether they’d buy the product at a given price (e.g., $50). If they say yes, offer a higher price. If they say no, go lower. Repeat until you zero in on their tipping point.
With enough responses, this gives you a demand curve – showing how price elasticity works for your target segment.
***
Feature-level and monetisation validation isn’t about building. It’s about prioritizing what to build and defining a pricing strategy that aligns with customer expectations – and business sustainability.
4. Usability
By now you’ve validated the need, confirmed interest, prioritized features, and tested price points – product testing and validation are finally behind. But one big question remains – can users actually use it?
Usability is a crucial part of product testing and validation. Even if your concept is great and priced right, poor UX can push users to drop off fast – especially in competitive markets. So before launch, it’s critical to validate how easily people can experience the value of your product.
At Craft Innovations, we use a core indicator called the Single Usability Metric (SUM). This composite score blends:
- Time to complete key actions
- Task success rate
- Customer Effort Score (CES)
- Error rate
- Retention of concept
If the SUM score is above 70, the product is typically market-ready – though there may still be UX improvements to make. But if it’s below 70, it’s a red flag. You’ll want to dig into why users are struggling before release.
Here are the full usability benchmarks we follow:
| Metric | Benchmark |
|---|---|
| Single Usability Metric | > 70/100 (SUM: time, success rate, CES, error rate) |
| Task Success Rate | > 85% of users can complete a core task |
| Error Rate | < 10% during core task execution |
| Retention of Concept | 80% of users can clearly describe the product value after testing |
The last one – retention of concept – is often overlooked. After a test, we ask users to explain the product’s benefit in their own words. If at least 80% can describe the core value correctly, it’s a good sign that the experience is clear, memorable, and aligned with intent.
You don’t need a polished product to start usability testing. Here are the main approaches we use:
- Moderated usability tests – guided sessions, often paired with eye-tracking if the interface is complex
- Unmoderated tests – tools like Maze or Useberry are great for simple task validation
- Heatmaps and session replays – useful to detect friction, confusion, or rage clicks
- Follow-up surveys – help capture concept clarity and perceived ease of use
These tools let you gather real feedback on real interactions – and avoid usability issues before launch.
Download the PMF Playbook
We hope you found this article useful and got answers to questions like “What is product validation?”, “How to validate a startup idea”, “How to validate a product idea”.
Looking to dig deeper?
Follow the link to download our free Product-Market Fit Playbook – a hands-on guide packed with more idea validation frameworks, benchmarks, and examples.
(Or scan the QR code below to download).
📞 Still not sure where to begin? If you need a fresh look at how to validate business ideas – or want full-cycle support with validation – get in touch with our team.
Sometimes, all it takes is a call to get things moving.
Happy Product Validation!
