Growth & Strategy
Personas
SaaS & Startup
Time to ROI
Short-term (< 3 months)
Last year, a potential client approached me with an exciting opportunity: build a two-sided marketplace platform. The budget was substantial, the technical challenge was interesting, and it would have been one of my biggest projects to date.
I said no.
Here's why — and what this taught me about the real purpose of lovable MVP user feedback methods in 2025.
The client came to me excited about the no-code revolution and new AI tools like Lovable. They'd heard these tools could build anything quickly and cheaply. They weren't wrong — technically, you can build a complex platform with these tools.
But their core statement revealed the problem: "We want to see if our idea is worth pursuing."
They had no existing audience, no validated customer base, no proof of demand. Just an idea and enthusiasm. Sound familiar?
In this playbook, you'll discover:
Why your first MVP shouldn't be a product at all
The feedback collection framework that actually validates demand
How to test market fit before building anything
Real examples of what lovable feedback looks like
The simple system I use to turn feedback into product decisions
Ready to learn how to build something people actually want? Let's dive in.
Reality Check
What everyone gets wrong about MVP feedback
Walk into any startup accelerator or browse through Product Hunt, and you'll hear the same advice repeated like gospel:
"Build fast, ship early, iterate based on user feedback."
Sounds logical, right? The problem is most founders interpret this as: build something first, then ask for feedback. This backwards approach is why 90% of MVPs fail.
Here's what the industry typically recommends:
Build a minimum viable product with basic features
Launch to a small group of beta testers
Collect feedback through surveys and analytics
Iterate based on usage data and user requests
Scale once you've found product-market fit
This conventional wisdom exists because it feels productive. You're building, shipping, measuring — all the things successful companies do. The feedback loop gives you data to point to in investor meetings.
But here's where it falls short in practice: you're optimizing for the wrong metrics.
Most founders confuse "feedback" with "validation." They build something, put it in front of users, and interpret any response as useful feedback. But feedback on a solution nobody asked for is just noise.
The real question isn't "How can we improve this feature?" It's "Should this feature exist at all?"
That's why I've developed a completely different approach to MVP feedback — one that validates demand before you write a single line of code.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
When that marketplace client came to me, they had fallen into the classic trap. They wanted to test if their idea worked by building it first. But as I told them: "If you're truly testing market demand, your MVP should take one day to build — not three months."
This wasn't the first time I'd seen this mistake. Working with SaaS startups and e-commerce businesses as a consultant, I've watched founders burn through budgets building products nobody wanted. They'd come to me after months of development, confused why their "perfect" solution wasn't gaining traction.
The pattern was always the same:
Founder has a brilliant idea
Builds MVP based on assumptions
Launches to crickets
Blames execution, not validation
One SaaS client spent six months building a project management tool for creative agencies. Beautiful interface, solid functionality, great user experience. But when they launched, agencies weren't signing up. Why? Because they'd never actually talked to agency owners about their project management pain points.
Turns out, most creative agencies weren't looking for another project management tool — they were drowning in client communication issues. The real problem wasn't task organization; it was client expectations and feedback loops.
Another e-commerce client built an inventory management system for small retailers. Months of development, sophisticated features, perfect product-market fit on paper. But small retailers were already using spreadsheets and weren't motivated to change. The "problem" existed, but it wasn't painful enough to drive purchasing decisions.
These experiences taught me something crucial: the most important feedback happens before you build anything.
That's why I told the marketplace client to forget about building a platform. Instead, I recommended something that would have shocked most product advisors: manual validation first, automation later.
Here's my playbook
What I ended up doing and the results.
Here's exactly what I recommended to that marketplace client — and what I now use with every new product idea:
Phase 1: The One-Day MVP (Day 1)
Forget Lovable, forget no-code tools. Your first MVP should be a simple landing page or Notion doc explaining your value proposition. That's it.
The goal isn't to impress anyone with functionality. It's to test if people care about the problem you're solving. Include:
Clear problem statement
Proposed solution overview
Email signup for "early access"
One specific call-to-action
Phase 2: Manual Demand Validation (Week 1)
Now comes the real work. Start manual outreach to potential users on both sides of your marketplace. This isn't about selling — it's about understanding.
My interview framework:
Problem exploration: "Tell me about the last time you struggled with [problem area]"
Current solutions: "How do you handle this today?"
Pain intensity: "What's the cost of not solving this?"
Solution validation: "If this existed, would you use it?"
Willingness to pay: "What would this be worth to you?"
Phase 3: Manual Marketplace Testing (Week 2-4)
If interviews validate demand, start manually matching supply and demand via email or WhatsApp. Yes, it's messy. Yes, it doesn't scale. That's exactly the point.
This manual process reveals:
Real user workflows and preferences
Actual pricing sensitivity
Hidden friction points
Feature priorities based on behavior, not opinions
Phase 4: Feedback Collection Framework
Throughout this process, I use a simple framework to capture meaningful feedback:
The LOVE Framework:
Language: How do users describe the problem in their own words?
Obstacles: What prevents them from solving this today?
Value: What outcomes do they expect from a solution?
Emotion: How do they feel when the problem occurs?
Only after proving demand through manual processes should you consider building automation. And when you do build, you're not guessing about features — you're automating workflows you've already validated.
This approach flips the traditional MVP model: your MVP should be your marketing and sales process, not your product.
Validation First
Manual testing proves demand before you build anything — saving months of development time
Problem Interviews
Real conversations reveal the language users actually use to describe their pain points
Manual Workflows
Handling transactions manually shows you the true user journey and friction points
Emotion Mapping
Understanding how users feel about problems helps you build solutions they'll actually love
When I shared this approach with the marketplace client, they initially resisted. "But we want to test our idea quickly," they said. "Building a platform with Lovable would only take a few weeks."
I asked them: "What's quicker — spending three weeks building something nobody wants, or spending three days proving people do want it?"
They decided to try my approach. Within two weeks, they had conducted 30 problem interviews across both sides of their proposed marketplace. The results were eye-opening:
The problem was real — but smaller than expected
Current solutions were "good enough" for most users
The value proposition needed refinement based on actual user language
A simpler solution emerged from the interviews
Most importantly, they discovered their original marketplace idea would have served a real need for only about 15% of their target market. The other 85% had a different, related problem that would require a completely different solution.
By week three, they had manually facilitated five transactions using just email and spreadsheets. These manual transactions taught them more about user behavior than months of analytics data ever could.
Six months later, they built a much simpler tool based on these learnings. It wasn't the sexy marketplace they originally envisioned, but it solved a validated problem for a proven market. The result? Paying customers from day one.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
After working with dozens of startups on MVP validation, here are the most important lessons I've learned:
Speed to feedback beats speed to features. Getting meaningful user insights in one week is more valuable than launching a feature-complete product in one month.
Manual processes reveal hidden assumptions. When you handle transactions manually, you discover workflow steps you never considered.
User language is your best copy. The words users use to describe problems become your marketing message.
Emotion drives adoption more than features. Users buy solutions to feelings, not features. Understand the emotional cost of the problem.
Perfect timing beats perfect execution. A simple solution at the right time outperforms a sophisticated solution users don't need yet.
Paying customers validate better than surveys. Someone willing to pay for a manual process will definitely pay for an automated one.
Distribution comes before development. If you can't manually reach your target market, automation won't help.
The biggest mistake I see founders make is treating validation as a checkbox to complete before the "real work" of building begins. But validation is the real work. Everything else is just implementation.
Remember: in the age of AI and no-code tools, the constraint isn't building — it's knowing what to build and for whom. Master the feedback collection process, and you'll never build the wrong thing again.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS startups implementing lovable MVP feedback methods:
Start with problem interviews before writing any code
Use manual onboarding processes to understand user workflows
Test pricing sensitivity through manual sales conversations
Validate feature priorities based on user behavior, not requests
For your Ecommerce store
For ecommerce businesses implementing lovable MVP feedback methods:
Test product demand through pre-orders before inventory investment
Use manual customer service to understand shopping friction points
Validate pricing through direct customer conversations
Test market fit through manual fulfillment processes first