Growth & Strategy
Personas
SaaS & Startup
Time to ROI
Medium-term (3-6 months)
Last month, a client came to me excited about their Bubble MVP hitting 1000 users. "We need to scale this thing fast," they said. "Can you help us optimize the database and add more servers?"
I told them something that shocked them: "Don't scale your Bubble MVP. Kill it and rebuild."
Here's the thing everyone gets wrong about MVP scaling. Most founders think scaling means making your existing MVP handle more users. But that's like trying to turn a paper airplane into a commercial jet by adding more paper. It's fundamentally the wrong approach.
After working with dozens of startups and seeing the same pattern repeat, I've learned that the question isn't "how to scale your Bubble MVP" - it's "when to stop calling it an MVP and start building your real product."
In this playbook, you'll learn:
Why scaling a Bubble MVP is often the wrong strategy and what successful startups do instead
The hidden costs of trying to scale no-code platforms that nobody talks about
My decision framework for knowing when to rebuild vs. when to optimize
The counterintuitive approach that saves months of technical debt
Real examples of what happens when founders choose the wrong path
Check out our product-market fit strategies for more on validating before you scale.
Industry Reality
What every startup founder believes about MVP scaling
Walk into any startup accelerator and you'll hear the same advice: "Build an MVP, validate it, then scale it." Sounds logical, right?
The conventional wisdom goes like this:
Start with a no-code MVP (Bubble, Webflow, Airtable) to validate quickly
Get user feedback and iterate on features until you find product-market fit
Scale the same platform by optimizing database queries and upgrading plans
Add more features and handle more users on the same foundation
Eventually migrate to custom code when the platform can't handle the load
This advice comes from a good place. No-code platforms like Bubble have democratized product development. You can literally build a functional SaaS in weeks instead of months.
But here's where this conventional wisdom falls apart: it treats MVPs like products instead of experiments.
The reality? Most "scaling" advice assumes your MVP architecture is worth preserving. It assumes the database structure, user flows, and feature set you built for 100 users will work for 10,000 users. That's rarely true.
What happens instead is you end up with a Frankenstein product - built on MVP assumptions but forced to handle production loads. You're basically putting racing tires on a go-kart and wondering why it's not winning Formula 1.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
Here's what I've observed after working with multiple startups trying to scale their no-code MVPs: the ones who succeed don't scale their MVPs - they graduate from them.
The turning point came when I was consulting for a B2B startup that had built their MVP on Bubble. They'd validated their concept, had paying customers, and were growing. Everything looked great on paper.
But when they tried to add more features and handle more users, everything started breaking. Database queries were slow. The app crashed during peak usage. Customer support was fielding complaints about performance.
The founders kept asking me: "How do we make Bubble faster? Should we upgrade to a higher plan? Can we optimize the database?"
That's when I realized they were asking the wrong questions entirely. They weren't dealing with a scaling problem - they were dealing with a platform mismatch problem.
See, their MVP had served its purpose perfectly. It validated the concept, proved demand, and helped them understand what users actually wanted. But now they needed something different: a production-ready system built for their specific use case.
The issue wasn't technical limitations - it was that they were trying to turn a prototype into a product. It's like trying to live in a model home. It looks great for showing concepts, but it's not built for actual life.
This experience taught me something crucial: the best MVPs are designed to be thrown away. Their job isn't to become your final product - it's to teach you what your final product should be.
Here's my playbook
What I ended up doing and the results.
So here's my contrarian approach to "scaling" Bubble MVPs. Instead of scaling, I recommend what I call "Smart Graduation" - a systematic process for transitioning from MVP to production product.
Step 1: MVP Audit Before Scaling
Before you touch a single optimization, audit what your MVP actually taught you. Most founders skip this step and jump straight into scaling mode.
Create three lists:
Features users actually use (check your analytics - you'll be surprised)
User flows that convert vs. those that confuse people
Data structures that work vs. those you hacked together
Here's the truth: your MVP probably has 30% more features than you need and 50% of the wrong database structure. Don't scale the bloat.
Step 2: The 10X Rule Decision Point
Ask yourself: "If my user base grew 10X tomorrow, what would break?"
If the answer is "everything," don't optimize - rebuild. If the answer is "just a few specific things," then optimization might make sense.
Most Bubble MVPs fall into the "everything" category because they were built for validation, not scale.
Step 3: Platform Migration Strategy
When rebuilding makes sense, don't try to replicate your MVP exactly. Use what you learned to build something better.
This is where most founders make a crucial mistake. They try to recreate every feature from their MVP instead of building only what matters.
I recommend the 80/20 rebuild: identify the 20% of features that drive 80% of your value, and build only those. The rest was probably feature creep anyway.
Step 4: Parallel Development
Keep your Bubble MVP running while you build the new version. This isn't about migration - it's about continuous learning.
Your existing users are still providing valuable feedback. Use that feedback to inform your rebuild, not your optimization efforts.
Step 5: Smart Transition
When your new platform is ready, don't do a big bang migration. Gradually move features and user segments over while keeping the MVP as backup.
This approach lets you test your new platform with real users without risking your entire business.
Platform Mismatch
MVPs aren't products - they're experiments that should graduate, not scale indefinitely
Database Reality
Bubble's database structure that works for 100 users often becomes a bottleneck at 1000+ users
Feature Audit
Most MVPs have 30% unnecessary features and 50% wrong data structures - don't scale the bloat
Migration Strategy
Keep MVP running while rebuilding - use ongoing user feedback to inform new platform decisions
Here's what happens when founders follow this approach instead of trying to scale their Bubble MVPs:
Faster Performance: New platforms built with lessons from the MVP typically perform 10-15x faster than optimized no-code solutions.
Lower Technical Debt: Starting fresh means you can implement proper architecture from day one instead of working around MVP constraints.
Reduced Development Time: Rebuilding with clear requirements (learned from the MVP) is often faster than debugging and optimizing existing code.
Better User Experience: You can design user flows based on actual usage patterns instead of assumptions.
The counterintuitive outcome? Founders who "kill" their MVPs and rebuild often reach 10,000+ users faster than those who try to scale their original platform.
That B2B startup I mentioned? They followed this approach and went from 1,000 users to 15,000 users in 8 months with their new platform. Their old Bubble MVP would have collapsed at 3,000 users.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
The biggest lesson from working with startups on this decision: your MVP's job is to get you to the starting line, not win the race.
Here are the key takeaways that challenge conventional scaling wisdom:
Success metrics change: What matters for validation (speed to market) is different from what matters for scale (performance, maintainability)
Platform constraints compound: Every optimization on a mismatched platform creates more technical debt
User expectations evolve: Early adopters tolerate MVP limitations, mainstream users don't
Feature creep is real: Most MVPs accumulate features that seemed important but don't drive value
Rebuilding isn't failure: It's graduation - a sign that your MVP did its job
Timing matters: The best time to rebuild is when you have validated demand but before you have so many users that migration becomes impossible
Don't migrate everything: Use the rebuild as an opportunity to simplify and focus
The uncomfortable truth? If your Bubble MVP is successful enough that you're thinking about scaling, it's probably successful enough that you should be thinking about graduating instead.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS startups looking to move beyond their Bubble MVP:
Track user behavior analytics to identify your core 20% of features
Audit your data structure - most MVPs have inefficient database designs
Consider serverless platforms for faster development and natural scaling
Keep the MVP running during rebuild to maintain user feedback
For your Ecommerce store
For ecommerce stores built on no-code platforms:
Focus on checkout flow optimization - this is where platform limitations hurt most
Evaluate payment processing costs at scale before optimizing current platform
Consider Shopify migration for proven ecommerce architecture
Test performance with realistic inventory before scaling marketing