.png)
The tension between shipping fast and shipping complete sits at the heart of product development. The choice depends on what you need to learn and what the market demands. A fintech startup entering the corporate card space faces different constraints than an event platform or an automotive software team. Some need to prove technical feasibility before investing further. Others know the concept works but need competitive features to gain traction. Some can only break through by delivering something people genuinely love from day one.
This is where minimum product approaches become useful. They're not sequential stages you progress through, though sometimes they work that way. They're strategic choices about scope, quality, and purpose. A Minimum Viable Product tests whether your core idea works with minimal investment. A Minimum Marketable Product gives you enough to compete and generate revenue. A Minimum Lovable Product creates an experience users love, even with limited features.
These frameworks help you decide what to build next and, more importantly, what to cut. Understanding when to use each approach—and when to skip them entirely—can mean the difference between validating a breakthrough idea and spending six months building something nobody wants.
This guide breaks down each approach, explains when they make sense, and shows how recent products across fintech, events, and automotive have used them. You'll see what worked, what didn't, and how to apply these principles to your own product decisions.
The term "minimum product" trips people up because "minimum" sounds like an invitation to cut corners or ship something half-finished. In reality, it's about focus. A minimum product is built to achieve a specific goal and nothing more. That goal might be validating an assumption, entering a market, or creating an emotional connection with users. What changes from case to case isn't discipline or quality, but scope and the quality bar you need to clear.
This way of thinking emerged as a reaction to waterfall development. For years, teams built in isolation for months, only to discover at launch that they'd solved the wrong problem or shipped features nobody cared about. Being wrong was expensive because changing course meant throwing away large chunks of work. Lean thinking flipped that dynamic. Instead of committing upfront, teams started validating assumptions incrementally: ship something small, learn from real users, then decide what to build next.
Mercury's launch of Treasury in late 2020 illustrates this principle. They needed a product that could safely handle real cash from day one. Moving customer money into government securities and money market funds demands reliability, regulatory compliance, and trust. It took nine months and a dedicated team to build. The minimum wasn't small in effort, but it was narrow in scope. No portfolio analytics, no advanced forecasting—just the core capability done well enough to test whether startups would actually move meaningful cash into higher-yield accounts.
That's why "minimum" is best understood as a risk-management choice. You're minimizing wasted effort, not ambition. Every feature you include should directly support the question you're trying to answer right now. Everything else, no matter how attractive, increases cost without increasing learning.
With the foundation established, we can examine the three primary approaches: MVP, MMP, and MLP. Each addresses a different question. An MVP asks "does this idea actually work?" An MMP asks "can we compete in this market?" An MLP asks "will people love this enough to tell others?"
Your context determines which approach makes sense. High uncertainty about demand favors smaller bets and faster validation. Crowded or credibility-driven markets may require a more complete experience just to be taken seriously. Regulatory environments can force significant upfront investment before real user testing is even possible. Understanding these trade-offs helps you decide not only what to build, but when shipping makes sense at all.
An MVP exists to answer a specific question about whether your core idea works. You're building the minimum that will generate meaningful insight about technical feasibility or market demand, then cutting everything else.
This means accepting constraints that would feel uncomfortable later. You might handle processes manually that you'd eventually automate, work with a small group of forgiving early users, or skip features that seem important but aren't central to what you're testing. The goal is validating your riskiest assumptions as quickly and cheaply as possible.
The core pattern: identify your riskiest assumption, build the minimum that tests it, learn whether you're right.
MVPs work best when uncertainty is high and the cost of being wrong would be significant. If you're building something technically complex where feasibility is unclear, an MVP helps you avoid months spent on something that won't work. If you're entering a new market where demand is unproven, it lets you test interest before committing to a full product.
Vivenu demonstrates this principle perfectly. The company was created to address the need of ticket sellers for a user-centric ticketing platform, as event organizers were stuck with solutions that heavily depend on manual processes, causing high costs, dependencies, and frustration. The riskiest assumption wasn't whether ticketing existed as a category—Ticketmaster dominated that market. The question was whether venues and promoters would actually switch to an API-first platform that gave them direct control.
Rather than building a full-featured competitor trying to match Ticketmaster on every dimension, Vivenu's MVP tested one specific hypothesis: would the ability to customize and control ticketing workflows without account manager dependencies be valuable enough to overcome switching costs? CEO Simon Hennes explained the core pain point: "You have to send your seat map to Ticketmaster, and then the account manager comes back to you with a sitemap. This goes back and forth and takes ages. With us you have a seating chart designer basically integrated into the software which you can simply change yourself".
The validation came quickly. In March 2020, vivenu secured €1.4 million in seed funding, then in December 2020 closed a €12.6 million Series A led by Balderton Capital after selling more than 2 million tickets since the seed round. Nine months and 2 million tickets proved that venues valued self-service flexibility enough to abandon incumbent platforms—exactly the kind of signal an MVP should generate. Only after proving this core assumption did Vivenu expand features to compete more broadly.
This is when MVPs shine: testing whether your differentiation actually matters to customers before investing in comprehensive feature parity with established competitors.
An MVP doesn't compete in an established market. You're not trying to match competitive feature sets or professional polish. Users willing to try an MVP understand the trade-off: early access to something new in exchange for rougher edges.
This distinction matters because many teams mislabel their products as MVPs when they're actually building for competitive markets that demand more complete offerings. If customers have working alternatives they're already using, they won't tolerate missing features or clunky experiences. The label describes a specific strategic situation where you're validating assumptions rather than winning market share. This is why picking the right early users matters enormously for MVPs. You need people who genuinely experience the pain you're solving and can evaluate whether your solution addresses it, even in limited form.
Success metrics center on learning rather than growth. You want clear signals about whether your core concept resonates, whether users complete the primary workflow, whether the technical approach is viable, and whether people indicate willingness to pay. High user numbers matter less than understanding whether you're solving a real problem in a way that works.
An MMP shifts focus from validation to competition. You're no longer asking whether the category exists—you're trying to win customers in a market that already does. That means building a product that meets baseline expectations for the space while staying narrow enough to ship, learn, and iterate. Unlike an MVP, an MMP is judged directly against alternatives.
An MMP doesn't have to follow an MVP. In some markets, demand is obvious. The open question isn't whether customers want a solution, but whether they'll choose yours. In other cases, you've already proven the core concept works and now need to close the gaps that make your product credible next to established players.
Polestar 3 launched in mid-2024 and demonstrates textbook MMP strategy through systematic OTA updates. Since delivering the first customer Polestar 3 in June 2024, the Swedish brand has implemented nine software updates to its flagship SUV. Rather than delaying launch until every feature was perfect, Polestar shipped with core functionality working reliably, then methodically closed competitive gaps.
Then the OTA updates enhanced the Polestar 3 with features like walk-away locking and digital key functionality for selected devices, allowing smartphone users to lock, unlock, or start the car without removing their phone from their pocket.
This MMP approach lets Polestar compete with Tesla and other premium EV makers by continuously adding features customers expect without waiting years to perfect everything before launch. Each update brings the vehicle closer to competitive parity while learning from real customer usage.
The central challenge of an MMP is finding the line between "enough to compete" and "too much to ship." Customers expect certain features from any serious product in a category, but copying competitors feature-for-feature leads to scope creep and long delays. The real work is understanding which expectations are non-negotiable for your target customers and which ones are incidental.
When Luma expanded from virtual to in-person events in 2021-2022, they faced established players like Eventbrite with years of feature development. Instead of matching every feature, Luma focused on making event creation and discovery dramatically simpler. They skipped complex ticketing tiers, detailed analytics dashboards, and white-label customization in favor of beautiful event pages, easy calendar integration, and social discovery. This worked because their target customers—people hosting smaller community events—valued simplicity over comprehensive features.
Rivian shows the same principle in automotive. When they delivered their first R1T trucks in 2021, the vehicles were complete enough to drive and charge, but the software lacked features Tesla owners considered standard. Instead of delaying delivery to match Tesla's entire feature set, Rivian shipped with core functionality working reliably, then added capabilities through over-the-air updates. Throughout 2023 and 2024, they've introduced scheduled drive conditioning, improved regenerative braking, automatic wipers, launch mode, and refined drive modes based on customer feedback.
Success metrics for an MMP center on market traction: customer acquisition, retention rates that suggest product-market fit, and revenue if that's part of your model.
The most common failures come from misreading market expectations. Build too little and customers dismiss the product as incomplete or unserious. Build too much and you delay entry while burning resources trying to match incumbents on every dimension. An MMP gets you into the competitive arena—staying there depends on continued iteration driven by customer behavior and competitive pressure.
An MLP shifts focus from competing to captivating. It centers on a narrow, well-crafted experience that drives advocacy, repeat use, and word-of-mouth. Instead of covering every use case, the approach aims to create a memorable experience that people notice and remember.
Like the MMP, an MLP doesn't necessarily follow an MVP. Sometimes you enter a crowded market where functional parity is table stakes, and the only way to break through is making something people love from day one. Other times you've built your MMP and now need differentiation as competition intensifies.
When Partiful launched in 2020, event planning tools already existed—Evite, Eventbrite, Facebook Events. The market was established, but Partiful's founders saw an opening: none of these tools worked the way Gen Z actually shares events. Partiful stripped away complexity in favor of what made events feel social again. Creating an event takes seconds. Invitations look like social posts with animated GIFs and playful themes instead of formal cards. Guests RSVP via text message without creating accounts or downloading apps. The entire flow is effortless and fun instead of transactional.
By late 2023, Partiful reached millions of monthly active users despite launching into a market dominated by established players. Google named it App of the Year for 2024, citing design that made event planning enjoyable. Users consistently mention how much more likely guests are to respond compared to traditional invitations.
Ramp took a similar approach in fintech, where expense management tools had existed for years. Every corporate card offered receipt capture and expense tracking by 2023, but most felt like they were built by accountants for accountants. Ramp focused on making the daily experience noticeably smoother. Automated receipt matching happens in seconds. The mobile app anticipates what you need without requiring menu navigation. Policy violations get flagged instantly with clear explanations instead of cryptic error codes. These aren't revolutionary features—they're thoughtful execution of basics that competitors treated as solved problems. CFOs choose Ramp for the savings analytics, but employees actually use it because it doesn't feel like work.
The challenge with MLPs is resisting the urge to compete on feature count. When you're building for enthusiasm, adding more doesn't automatically create more love—complexity often kills the magic. The key is identifying what will create emotional resonance with your specific audience, then executing those elements beautifully while staying disciplined about scope.
Success metrics for an MLP center on enthusiasm over satisfaction. You want high NPS scores indicating users actively recommend your product, not just tolerate it. Word-of-mouth growth becomes a leading indicator. Social media mentions and unsolicited testimonials matter more than paid acquisition efficiency. You're measuring whether people love what you've built enough to become advocates.
The most common mistake is confusing delight with decoration. Adding animations, playful copy, or visual polish doesn't automatically create love if the underlying experience remains frustrating or confusing. Real connection comes from making core workflows feel effortless, anticipating user needs, and creating moments of unexpected satisfaction. It's about removing friction and adding personality in ways that resonate emotionally, not about surface-level aesthetics. An MLP succeeds when users feel the product understands them, not just when it looks appealing.
Choosing between MVP, MMP, and MLP isn't about preference—it's about matching your approach to your context. The wrong choice wastes resources by building too much too soon or shipping something the market won't take seriously.
Start by assessing your uncertainty. If you're unsure whether your core concept works technically or whether customers actually want it, you need an MVP. A fintech startup uncertain whether small businesses will switch from their existing accounting software shouldn't build a full-featured product before testing that assumption. An MVP that validates the core workflow with a small group reveals whether the concept resonates before months of development.
Market maturity changes the equation. Entering an established market where competitors have set baseline expectations often requires starting with an MMP. Users in mature markets have reference points—they know what "complete enough" looks like. A new expense management tool launching in 2024 can't ship with just receipt capture and expect customers to wait for basic reporting. Those capabilities aren't innovations; they're table stakes.
Sometimes differentiation strategy matters more than validation. If you're entering a crowded market where functional parity won't win customers, an MLP approach might make sense from day one. This works when experience becomes the competitive advantage because features are already commoditized. Partiful didn't need to validate whether people wanted event planning tools—those existed. They needed to prove that making the experience delightful could overcome entrenched competitors.
Resource constraints and regulatory environment shape what's realistic. MVPs require the least investment—you're building narrowly and accepting rough edges. MMPs demand more because you need production-quality features matching competitive baselines. MLPs often require the most investment in design and refinement because experience is the product.
Meanwhile, banking products need licenses before processing transactions, medical devices require certification before patient use, and automotive software needs safety validation before deployment. In regulated industries, the "minimum" gets defined by compliance requirements rather than strategic choice.
Real decisions rarely fit cleanly into one category. A fintech product might need MMP-level compliance for core banking features while taking an MVP approach to experimental features like spending insights. An automotive team adding features to vehicles already in customers' hands doesn't need an MVP—they need an MMP or MLP depending on whether they're reaching competitive parity or creating differentiation.
The traditional path—MVP validates, MMP competes, MLP differentiates—makes sense when pioneering a new category or facing high uncertainty. But it's not mandatory. You might skip MVP entirely if the market is proven. You might jump straight to MLP if you're entering a commoditized market where experience is the only remaining differentiator. You might build an MMP, learn it's not enough to stand out, then shift toward MLP thinking for your next iteration.
Your market context influences timing and quality expectations. Consumer apps targeting younger audiences often need more polish from launch because that demographic expects Instagram-quality experiences. Enterprise B2B tools need credibility markers—security certifications, integration capabilities, professional support—before buyers will consider them seriously. Developer tools can succeed with rough MVPs if the core functionality solves a real problem, because technical users tolerate rough edges more than general consumers.
The framework won't help you find the "right" answer. It's about understanding the trade-offs and choosing deliberately based on your riskiest assumptions, market expectations, differentiation strategy, available resources, and regulatory constraints.
Once you've chosen your approach, execution requires different disciplines for each. The principles guiding an MVP differ from those guiding an MMP or MLP, though some fundamentals remain constant.
The hardest part of any minimum product is deciding what stays and what gets cut. Start by writing down the core problem you're solving in a single paragraph. If you can't articulate it that concisely, you're not focused enough.
For an MVP, ask: does this feature help validate our riskiest assumption? If not, cut it. When Column built their banking infrastructure, they focused on account opening and basic transaction processing—the minimum needed to validate whether fintechs would actually integrate with their platform. Wire transfers, check deposits, and treasury management came after they'd proven the core premise.
For an MMP, ask whether a feature meets baseline market expectations or provides meaningful differentiation. When Luma expanded to in-person events, they needed features Eventbrite users would expect—event pages, RSVP tracking, basic ticketing—but skipped complex multi-tier pricing and detailed analytics because their target users valued simplicity over comprehensive reporting.
For an MLP, the filter changes: does this feature contribute to the experience we want people to love? Partiful could have added complex invitation customization with dozens of options, but that would have undermined the simplicity that made the app delightful. They kept customization curated and playful instead of comprehensive.
Set a launch date and work backward, prioritizing ruthlessly. The common trap is convincing yourself that "just one more feature" is essential. It rarely is.
MVPs optimize for speed of learning, which sometimes means accepting technical shortcuts you'll fix later. Manual processes can substitute for automation. When Mercury first launched treasury, some compliance checks were handled manually while they built automated systems, letting them serve customers and learn what mattered before investing in full automation.
MMPs require production quality from the start because you're competing for customers who have alternatives. Technical debt accumulates, but you can't ship obvious bugs or performance issues. Brex couldn't launch bill pay with slow processing times or unclear error messages—those basics needed to work smoothly even in the initial release.
MLPs demand higher quality because the experience is the product. Small details matter more when you're creating delight. The extra time spent on polish, transitions, and overall feel is what separates an MLP from an MMP.
Feedback loops differ by stage. For MVPs, you want direct conversation with users to understand not just what they're doing but why—five in-depth interviews often teach you more than fifty survey responses. For MMPs, you need both qualitative feedback on usability and quantitative data on behavior: completion rates, friction points, competitive comparisons. For MLPs, pay attention to emotional language. Do users say they "like" your product or that they "love" it? What specific moments do they mention?
For MVPs, the key questions are: Did we validate our core assumptions? Can we build this sustainably? Will customers pay? Growth numbers matter less than clear answers to these fundamentals. Fifty users with forty-five indicating they'd pay is more valuable than five hundred users with unclear purchase intent.
For MMPs, metrics shift toward market traction: acquisition rate, activation for key features, retention after the first week and month, and revenue growth. You're measuring whether you can win and keep customers.
For MLPs, NPS becomes central alongside retention. Products people love typically score above 50, indicating active promoters instead of passive satisfaction. Track word-of-mouth growth separately from paid acquisition—if growth is primarily paid, you might not have created the emotional connection you're targeting. Social mentions, unsolicited testimonials, and user discovery stories all signal whether you've achieved delight.
Match your metrics to what you're actually trying to achieve. Optimizing for growth during MVP development leads to premature scaling. Focusing only on NPS during MMP development distracts from competitive positioning work.
Product development rarely goes according to plan. Understanding common pitfalls helps you avoid them or recognize when you're heading toward one.
Resource constraints look different across industries. Fintech startups face infrastructure costs that can't be minimized below certain thresholds. Column needed to acquire an actual bank charter—Northern California National Bank—and replace its legacy systems before processing a single transaction. This wasn't optional scope; it was the price of entry. Their "minimum" referred to features built on top of that infrastructure, not the infrastructure itself.
Automotive companies face similar dynamics. Rivian couldn't ship vehicles with "minimum viable" crash safety or battery management. Those systems needed to meet strict standards regardless of product stage. The strategic choice was what software features to include at launch versus what could come through over-the-air updates later.
The mistake many teams make is treating all constraints as equally binding. A bootstrapped fintech startup might delay advanced analytics but can't delay compliance infrastructure. Recognizing which constraints you can work around versus which you must accommodate shapes realistic timelines and scope.
Regulated industries present unique challenges because compliance requirements define the minimum instead of customer needs. When Mercury launched treasury, they needed every transaction to comply with securities regulations, banking laws, and anti-money laundering requirements. Building the minimum compliant product took nine months with a dedicated team—no shortcuts existed around regulatory approval.
Geographic variation intensifies this challenge. A payments company launching in Europe needs PSD2 and GDPR compliance from day one, while US expansion faces different requirements around payment processing and consumer protection. The strategic response is building compliance as infrastructure instead of treating each requirement as a separate feature. This front-loaded investment pays off as you expand, but it does mean your initial minimum carries more weight than in unregulated industries.
The most expensive mistake is building comprehensively for a problem you haven't validated. Humane's AI Pin demonstrates this at scale. The company raised over $230 million and spent years developing a $699 wearable device intended to replace smartphones through a screenless, voice-controlled AI assistant that projected information onto your hand.
When the product launched in April 2024, fundamental flaws emerged. The AI assistant gave incorrect answers and couldn't complete simple tasks like setting timers. Battery life lasted only two to four hours. The laser projection was barely visible outdoors. Voice recognition struggled in noise. Reviews were devastating—influential tech reviewer Marques Brownlee called it "the worst product I've ever reviewed." By early 2025, Humane sold its assets to HP for $116 million, less than half what they'd raised.
The strategic error was skipping validation stages entirely. Humane operated like an established company launching a refined product instead of a startup testing a novel concept. According to reports, management culture discouraged criticism—employees raising concerns about battery life and performance were dismissed or ignored. The founders preferred positivity over realistic assessment, demonstrating devices cooled on ice packs to make them last through demos. When an engineer questioned readiness, she was fired for "talking negatively about Humane."
An MVP testing whether people would prefer voice interaction over screens could have revealed fundamental issues with the approach. Instead, Humane invested everything in a complete vision the market rejected.
Finding the right pace requires understanding your market dynamics. In fintech, where trust and reliability are paramount, shipping too early can be fatal. A payment processing error or security vulnerability destroys confidence that takes years to rebuild. Brex and Ramp both ensured their core card processing worked reliably before launch because they knew customers wouldn't give them a second chance.
Events and consumer apps face different pressures. Partiful succeeded partly by timing their launch when Gen Z was looking for alternatives to Facebook Events. Had they spent another year polishing, competitors might have filled that gap.
The key is distinguishing between markets where first-mover advantage matters versus markets where being better matters more. In emerging categories, getting there first with something functional often beats arriving later with polish. In established categories with high switching costs, you need to be demonstrably better to convince people to change.
Scaling before achieving product-market fit wastes resources and creates organizational complexity that makes iteration harder. Some fintech startups expand to new customer segments or geographic markets before solidifying their core offering, spreading engineering resources thin and making excellence harder to achieve.
Warning signs include growing the team faster than revenue, expanding to new markets before the existing market works, and adding features to attract new customer types before fully serving current customers.
The antidote is disciplined focus: define success metrics for your current stage and don't progress until you've hit them. Each stage builds the foundation for the next, but skipping ahead creates instability.
Don't think of MVP, MMP, and MLP as stages you must progress through—they're strategic tools for different situations. The right choice depends on what you're trying to learn, how mature your market is, what resources you have, and how you plan to differentiate.
Start by understanding your context. High uncertainty about whether your concept works calls for an MVP to validate assumptions before committing resources. Entering an established market where customers have clear expectations likely requires an MMP that meets baseline standards while finding areas to excel. Competing in a crowded space where functional parity isn't enough might demand an MLP that wins through experience from day one.
Match your execution to your goals. MVPs focus on validation—does the core concept work, will people pay, can you build it sustainably. MMPs focus on market traction—can you acquire and retain customers competitively. MLPs focus on enthusiasm—do people love it enough to become advocates.
The companies that succeed stay flexible. Column validated their banking infrastructure concept, then expanded features. Luma proved virtual events worked, then moved to in-person. Partiful launched with delight as the strategy and let word-of-mouth drive growth. None followed a predetermined playbook—they matched their approach to what they needed to learn at each stage.
Your journey won't be linear. You might skip validation if the market is proven, shift from MMP to MLP thinking when competition intensifies, or discover your MVP reveals a different opportunity and pivot entirely. What matters is being honest about what you're trying to achieve and building accordingly.
Don't dress up an MMP as an MVP to feel scrappy. Don't convince yourself you need an MLP when an MMP would get you learning faster. Don't skip validation because you're excited about the vision.
The difference between validating a breakthrough idea and spending months building something nobody wants often comes down to asking the right questions at the right time. Choose your approach based on strategy, build the minimum that achieves your goals, and let what you learn guide what comes next.
Think of us as your tech guide, providing support and solutions that evolve with your product.
.png)
