What Is a Minimum Viable Product (MVP)? 7 Strategies to Build MVPs That Get Funded

An MVP isn't a polished product. It's a learning experiment designed to prove whether anyone actually wants what founders are building. Founders who understand this save months of development time and improve their odds of raising capital. This guide covers what makes MVPs work, common types founders build, how to build your first one and what early-stage investors look for in MVP-stage companies.

What Is a Minimum Viable Product (MVP)?

A minimum viable product (MVP) represents the simplest working version of a product that can generate real customer feedback. Frank Robinson coined the term in 2001, which Eric Ries later popularized in The Lean Startup. Ries defined an MVP as "that version of a new product which allows a team to collect the maximum amount of validated learning about customers with the least effort."

Ries emphasized that the goal of an MVP "is to begin the process of learning, not end it." An MVP isn't version 1.0 of a final product. It's an experiment designed to answer whether real users will actually pay for or consistently use a solution.

MVP vs. Proof of Concept vs. Prototype

MVPs, proofs of concept and prototypes are often lumped together, but they solve different problems. Here is what each one actually does:

• MVP: Delivers a working product with core features to actual customers, testing whether anyone wants the solution.
• Proof of concept: Validates whether a core technical idea is buildable. Only use this when the technical approach is genuinely novel.
• Prototype: Tests user experience and design decisions before development, focusing on interaction patterns rather than market demand.

Most founders should skip the proof of concept and prototype stages when they use established technology, and instead should build a lean MVP to test market demand.

Why Founders Need MVPs Before Raising Capital

Most startups fail because they build something nobody needs. MVPs let you test that assumption before investing months of work:

• Validate demand before building: Dropbox founder Drew Houston created a demo video showing how Dropbox would work. The video generated 75,000+ pre-launch signups overnight, validating market need before investing months in complex synchronization technology.
• Measure what actually drives behavior: Track specific actions like daily active usage, feature adoption rates or time-to-first-value rather than vanity metrics like total signups. Focus your MVP iteration on the specific actions that correlate with long-term retention.
• Prove understanding to investors: Seed-stage investors back companies during MVP development. What they require is evidence that founders understand the problem deeply and can learn quickly from real users.

These three validation points explain why investors fund MVPs rather than ideas.

Best Practices That Make MVPs Work

The most effective MVPs solve one core problem exceptionally well rather than addressing multiple problems adequately. Spotify's initial MVP focused exclusively on solving music streaming latency. Founder Daniel Ek spent months ensuring users could click play and hear music instantly, ignoring features like playlists, social sharing or discovery algorithms. That singular focus on latency proved people would use streaming services.

The "viable" in minimum viable product often gets overlooked. An MVP must actually retain and satisfy early users, not just barely function. Early adopters tolerate missing features but not broken core functionality. When the core experience disappoints, it is hard to rebuild that initial trust.

We've seen four patterns that consistently separate effective MVPs from failed experiments:

• Talk to users directly: Observe how users actually use your product rather than relying on analytics alone. Airbnb's founders personally photographed hosts' apartments in their first year, learning what made listings convert through direct observation and host conversations.
• Do the work yourself: The founders who understand their business best actually ran it manually first. Tony from DoorDash hand-delivered meals during the company's first nine weeks, learning how restaurants actually operate before automating anything. That hands-on knowledge is why CRV backed them so early — and Tony still does daily drives to watch the service in action.
• Use existing tools before custom development: Groupon started as a WordPress blog with no custom technology. Founder Andrew Mason posted daily deals manually, proving the business model worked before investing in infrastructure.
• Design for instrumentation from day one: Build systems that can measure user behavior once traction begins. Add simple feedback prompts like "Was this helpful?" inside the product rather than waiting for enough volume to make analytics meaningful.

Collecting quick feedback is critical at the MVP stage. Founders who optimize for polish over learning velocity typically build products nobody wants.

Common Types of MVPs Founders Build

Different MVP approaches work for different business models. Choosing the right type for your specific hypothesis saves time and capital while generating clear signals about the demand for your solution.

Landing Page MVP

Landing page MVPs test market demand by describing a product concept and measuring visitor interest through email signups before building anything. Buffer founder Joel Gascoigne validated demand for his social media scheduling tool through a simple landing page focused entirely on validated learning.

This approach works best when testing whether anyone wants your category of solution rather than a specific implementation.

Concierge MVP

Concierge MVPs involve manually delivering a service to early users before building automation. Food on the Table tested meal planning by having founder Manuel Rosso manually create customized meal plans for each customer.

Customers knowingly paid for the manual service, which validated the hypothesis that people would pay for personalized meal planning. The manual approach revealed which features actually worked rather than which seemed important in theory.

Wizard of Oz MVP

Wizard of Oz MVPs make users believe they're using an automated system while humans power it behind the scenes. Zappos founder Nick Swinmurn tested whether people would buy shoes online by creating a website displaying shoe photos, then physically purchasing and shipping shoes when orders came in.

Zappos later sold to Amazon for $1.2 billion, but the initial validation happened through entirely manual fulfillment.

Piecemeal MVP

Piecemeal MVPs combine existing tools to deliver an offering without building new technology. Groupon founder Andrew Mason tested daily deals using WordPress, explaining "We took a WordPress Blog and we skinned it to say Groupon and then every day we would do a new post."

No custom technology was built initially. The constraint forced focus on whether the business model worked before investing in infrastructure.

Single-Feature MVP

Single-feature MVPs keep narrow focus on one key feature at launch. Uber tested one core hypothesis that people would use smartphones to request rides, starting with a premium black car service in San Francisco.

Uber’s initial version had just one feature: requesting a ride via the iOS app. No fare splitting, multiple stops or driver ratings existed yet.

Different MVP types work for different hypotheses. But how do you actually build one?

How to Build Your First MVP: 7 Strategies

These seven strategies help founders validate demand, iterate faster and reach product-market fit without wasting months on features nobody wants.

Strategy 1: Talk to Users First

Schedule 10 to 20 conversations with people who experience the problem you're solving. Don't ask if they'd use your solution. Ask them to describe the last time they tried to solve this problem and what happened. The "Mom Test" principle applies: when someone says "I would totally use that," ask "When was the last time you needed this?" and "Would you pay for this today? How much?" If they can't recall a recent instance or won't commit to paying, the pain isn't severe enough.

Tools like Claude Code and other AI assistants can now compress the technical MVP build significantly. But speed doesn't replace validation: you still need to discover your moat, prove people will pay and build distribution channels.

Strategy 2: Define Your Specific Segment

Get specific about who you're building for. Target "B2B finance managers at 20- to 100-employee startups using QuickBooks" rather than "small businesses." Specificity makes it easier to find early users and determine whether feedback represents signal or noise.

Buffer's Joel Gascoigne started with "social media managers who schedule Twitter posts for brands." When 120 people signed up over seven weeks through his landing page MVP, he knew demand existed.

Strategy 3: Choose Your MVP Type

Match your MVP type to what needs validation. Landing pages test demand before you build, concierge MVPs test workflows before you automate and single-feature MVPs prove one hypothesis before you add more.

Zappos started by photographing shoes at local stores and fulfilling orders manually. This Wizard of Oz MVP approach validated that people would buy shoes online before investing in inventory or infrastructure.

Strategy 4: Set Success Metrics Before Launch

Define two to three metrics that signal whether your MVP works before you build. Track user retention, feature adoption or time-to-first-value rather than total signups.

If you launch without defining what "working" means, you'll rationalize mediocre engagement as "early users need time to understand the product" instead of recognizing a failed hypothesis.

Choose metrics that measure actual behavior, not user interest. Life Folder tracked how many friends each user invited and celebrated when the average hit over two invites per user. But almost nobody accepted the invitations. The metric that actually mattered was conversion rate, which remained near zero. Tracking invites sent instead of invites accepted masked the problem for months.

Strategy 5: Use No-Code Tools When Possible

Webflow, Bubble, Airtable and Zapier let you validate demand without writing code. Reserve custom development for features that differentiate you.

Teal built their career growth platform entirely with Bubble, Webflow, Airtable, Zapier and HubSpot. The no-code approach helped them validate their product model and raise $5 million in funding before writing any custom code.

Strategy 6: Prioritize With MoSCoW

Categorize every potential feature into Must Have, Should Have, Could Have or Won't Have (MoSCoW). Your MVP should contain only the must-haves. If you can't articulate how a feature helps acquire or retain customers, you don't need to build it right now.

Instagram's founders cut location check-ins, messaging and social feeds. They shipped with one feature: posting photos with filters.

Strategy 7: Launch Small and Iterate

Launch to 10 to 50 early adopters who will give honest feedback rather than thousands of anonymous users. Set up tracking before launch using Mixpanel or Amplitude and add simple feedback prompts throughout the product like "Was this helpful?" or "What's missing?" Watch how early users describe the product, which features they ask about and where they get stuck to identify iteration priorities.

Most founders spend months building features nobody wants. These strategies flip that pattern: you'll know if your idea works within weeks instead of wasting time on the wrong solution.

How Early MVPs Became Billion-Dollar Companies

Several of the most successful technology companies started with MVPs that looked nothing like their current products. These examples reveal patterns about what early validation actually requires.

Airbnb

In October 2007, Brian Chesky and Joe Gebbia purchased airbeds and created a basic website offering conference attendees a place to sleep for $80 per night. The first three customers generated $240 in revenue, validating that strangers would pay to stay in someone's home.

This single data point answered the fundamental question about whether the business model could work. For Airbnb, the journey from MVP to traction took two years of failures before New Year's Eve 2009 brought 1,400 guests, marking the shift to sustained growth.

Amazon

Jeff Bezos launched Amazon in 1995, selling only books online, a single-category MVP that validated whether people would purchase products through the internet. Amazon sold $12,000 worth of books in its first week.

This approach let Bezos prove the e-commerce model before expanding into additional categories. Rather than building "the everything store" from day one, the books-only MVP minimized risk while testing the core hypothesis that consumers would trust online purchasing.

Dropbox

Drew Houston created a demo video showing how Dropbox would work rather than building complex synchronization technology first. This approach validated market demand before investing in expensive infrastructure.

The video drove 75,000 signups overnight from a Hacker News post. Houston recognized that proving demand mattered more than proving technical capability. Dropbox grew from three million users in November 2009 to 50 million in October 2011 through multiple growth tactics including referral programs.

Uber

The first Uber ride was requested in San Francisco as a premium black car service. The initial product had one core feature with no fare splitting, multiple stops or driver ratings.

This single-feature validation proved people would use smartphones to request rides before the company invested in expanding features.

These success stories share common patterns, but they also reveal what happens when founders ignore MVP principles. Recognizing mistakes before making them saves months.

Mistakes That Undermine MVP Effectiveness

Most MVPs fail for one of four predictable reasons. Here are the mistakes many first-time founders make:

• Building too many features: When five features launch simultaneously, isolating which features drive engagement becomes impossible. If your MVP takes longer than six to eight weeks to build, you're overengineering it.
• Confusing MVP with beta: An MVP validates an idea quickly as a learning tool. A beta version assumes that the idea works and further polishes the product. Building a “Minimum Marketable Product” when validation is still needed wastes months and significant capital on features that miss the actual problem.
• Shipping broken core functionality: Early adopters tolerate missing features but not broken core functionality. Users can't give meaningful feedback on a solution that doesn't solve their problem at all. Stripe's MVP didn't have every payment method, but the one method it supported worked flawlessly for developers.
• Skipping user feedback loops: Eric Ries emphasized the goal is collecting maximum validated learning with minimum effort. Founders launch the MVP but don't follow through. They skip the weekly user calls and ignore usage data, missing the insights that would tell them what to build next.Without feedback loops, you're building in the dark.

All four mistakes share the same root problem: prioritizing building over learning. Avoiding these mistakes improves your odds, but what actually gets investors to say yes?

What We Look for in MVP-Stage Companies

When evaluating startups at the MVP stage, we focus on learning velocity and visible iteration rather than product completeness. We’ve seen these four patterns emerge from 55 years of early-stage investing:

• Speed to market: Founders who take six months to build their first MVP typically take just as long to iterate on subsequent versions. We look for MVPs shipped in weeks.
• Evidence of real interest: A waitlist with 200 engaged signups who respond to weekly emails outweighs 2,000 signups who never open messages. Pilot participants and retention data that shows people return weekly separate actual demand from interest.
• Visible iteration loops: Founders who find product-market fit fastest iterate in weekly sprints. They talk to users, ship changes, measure what happens, then do it again. The signal is whether they can explain what the last three iterations taught them and what hypothesis they're testing next.
• Path to scale: We invest in teams building toward product-market fit. We backed Mercury six weeks after launch when they showed strong retention among their users. By Series A, the questions shift to evidence: expanding user base without expanding marketing spend proportionally, strong retention cohorts and a clear path to $1M+ ARR.

The exact path will evolve as you learn more about your market, but the trajectory from current MVP learnings to a repeatable, scalable model should be visible.

Why Constraint Makes Better Products

Building an effective MVP means embracing constraint as a feature rather than a limitation. The founders who succeed treat their first product as a learning experiment with minimal scope and focus on collecting early feedback.

As a founder, an MVP should make you slightly uncomfortable with how minimal it is. This discomfort usually signals that your approach is working. Products that feel complete and polished at the MVP stage typically haven't stripped away enough to generate clear learnings.

If you're raising seed or Series A, reach out to CRV today. We invest in technical founders who demonstrate rapid learning velocity from real user feedback.

Frequently Asked Questions About MVPs

What does MVP stand for in startups?

MVP stands for Minimum Viable Product. Eric Ries defined it as "that version of a new product which allows a team to collect the maximum amount of validated learning about customers with the least effort."

How long should it take to build an MVP?

Most software MVPs should take two to four weeks for simple products, while standard web applications typically take six to eight weeks. If you're spending significantly more time, you're likely building too many features rather than validating a single core hypothesis.

What's the difference between an MVP and a prototype?

A prototype tests user experience and interaction patterns before development, while an MVP tests market demand with a working product. Prototypes answer "does this design work?" while MVPs answer "do people want this?"

Do I need an MVP to get VC funding?

Not always. Seed-stage startups often raise capital to build MVPs, so what you need is evidence of customer validation through waitlist signups or founder-market fit. Series A funding requires proven product-market fit with quantifiable traction.

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