Growth & Strategy
Personas
SaaS & Startup
Time to ROI
Short-term (< 3 months)
A few months ago, I was on a call with a potential client who had just raised their seed round. They were excited about launching their SaaS beta testing cohort to "validate their product." Sounds reasonable, right? But as we dug deeper into their approach, I realized they were about to make the same mistake I see repeatedly in the startup world.
They had built 80% of their product already. Their beta wasn't about learning—it was about finding people to confirm what they'd already decided to build. This is backwards, and it's why most beta programs fail to deliver meaningful insights.
The uncomfortable truth? Your beta cohort shouldn't be testing your product. It should be testing whether the problem you think you're solving actually exists and matters enough for people to pay for a solution.
Here's what you'll discover in this playbook:
Why building 80% before beta testing guarantees wasted resources
The difference between feature validation and problem validation
How to structure a beta cohort that actually de-risks your business
My framework for turning beta users into paying customers
When to kill a product idea based on beta feedback
This approach saved one of my clients from building a $200K feature nobody wanted, and helped another pivot to a $1M ARR solution that emerged from beta insights.
Industry Reality
What every startup accelerator tells you about beta testing
Walk into any startup accelerator or read any "lean startup" guide, and you'll hear the same advice about launching SaaS beta testing cohorts:
Build your MVP, then find beta testers to validate it. The typical process looks like this:
Build 70-80% of your planned features
Recruit 20-50 beta users from your network
Let them use the product for 30-90 days
Collect feedback on what's missing or broken
Iterate based on feature requests
Launch publicly with "validated" product-market fit
This conventional wisdom exists because it feels safe. You have something tangible to show. Beta users can click through actual screens and give concrete feedback about user interface improvements.
But here's the problem: you're validating solutions, not problems. By the time you've built 80% of your product, you're psychologically committed to that specific solution. Your beta feedback becomes about tweaking features, not questioning whether you're solving the right problem in the first place.
The result? You end up with a very polished product that perfectly solves a problem nobody wants to pay to solve. I've seen this pattern dozens of times—beautiful SaaS products with great UX that can't find paying customers because they never validated the underlying problem severity.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
I experienced this backwards approach firsthand when I was advising a B2B SaaS startup last year. They approached me after spending six months building what they called their "MVP"—a project management tool specifically designed for creative agencies.
The founders had worked at agencies and were confident they understood the pain points. Their product had beautiful Kanban boards, time tracking, client collaboration features, and integrations with popular design tools. It looked impressive in demos.
When they launched their beta cohort with 30 creative agency owners from their network, the feedback was predictably positive. Beta users said things like "this looks great" and "I can see how this would be useful." They provided detailed feedback about UI improvements and requested additional features.
But here's what wasn't happening: nobody was actually using the product regularly. The founders interpreted this as a user experience problem and spent another three months refining the interface based on beta feedback.
When I dug deeper into their beta data, the truth became clear. The average beta user logged in 2.3 times during the 90-day period. Most sessions lasted less than 5 minutes. This wasn't a feature problem—it was a problem severity problem.
The agencies already had systems that worked "well enough." They were using a combination of Slack, Google Sheets, and maybe Monday.com or Asana. Was their current workflow perfect? No. But was it painful enough to justify switching to a new tool and training their team? Absolutely not.
The startup had built a solution to a problem that was real but not urgent. Their beta cohort confirmed the solution was well-designed, but they never tested whether the problem was severe enough to drive purchasing behavior.
Here's my playbook
What I ended up doing and the results.
After seeing this pattern repeat across multiple projects, I developed what I call "problem-first beta testing." Instead of building 80% of your product before testing, you start with the problem and use the beta cohort to validate problem severity before building solutions.
Phase 1: Problem Discovery (Week 1-2)
Your first "beta" isn't actually testing a product—it's testing problem hypotheses. I recruit 15-20 people who fit your ideal customer profile and put them through what I call a "problem interview sprint."
The key is asking about their current workflow, not their opinion about your solution. Questions like: "Walk me through exactly how you handle [specific situation] today" and "What's the most frustrating part of that process?"
Here's the crucial part: you're looking for evidence that people are already spending time, money, or effort trying to solve this problem. If they've built homegrown solutions, hired additional staff, or are paying for multiple tools to address the issue, that's a strong signal.
Phase 2: Solution Validation (Week 3-6)
Only after confirming problem severity do you build a minimum viable solution. But here's where my approach differs from conventional beta testing: you don't build features—you build workflows.
For that creative agency tool, instead of building beautiful Kanban boards, we would have started with a simple system that solved their most painful workflow bottleneck. Maybe that's client approval tracking, or resource allocation conflicts, or deadline management.
The beta test becomes: can you replace one specific part of their existing workflow with something measurably better? If they don't adopt this one simple improvement, they won't adopt your full-featured platform.
Phase 3: Expansion Testing (Week 7-12)
Once you have beta users actively using your core workflow solution, then you can test adjacent features. But each new feature follows the same rule: it must solve a proven problem that emerged from watching people use your core solution.
The creative agency project never made it to Phase 3 because we discovered in Phase 1 that most agencies weren't sufficiently motivated to change their project management approach. We killed the project after four weeks instead of after 18 months.
Problem Severity
Test if people are already trying to solve this problem with makeshift solutions or by paying for multiple tools.
Workflow Replacement
Don't build features—build a single workflow that's 10x better than their current approach.
Usage Thresholds
Set minimum usage requirements. If beta users don't hit these thresholds, you have a motivation problem, not a feature problem.
Kill Criteria
Define specific metrics that would cause you to pivot or kill the project. Stick to these criteria.
The problem-first beta approach produces dramatically different outcomes than conventional feature-focused testing.
Resource Efficiency: Instead of spending 6-12 months building a full product before learning it won't work, you learn this in 4-6 weeks with minimal code written.
Higher Beta-to-Paid Conversion: When beta users are already solving the problem with your core workflow, converting them to paying customers becomes natural. They're not evaluating whether they need the solution—they're already dependent on it.
Clearer Product Roadmap: Because you understand the problem hierarchy, you know which features to build next. Each feature addresses a validated problem that emerged from real usage patterns.
The most surprising outcome? Several "failed" beta tests revealed much more valuable problems hiding underneath the original hypothesis. That creative agency tool pivoted to become a client onboarding automation platform after beta interviews revealed that project management wasn't the real pain point—client chaos was.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
Here are the seven most important lessons I learned from implementing problem-first beta testing across multiple SaaS projects:
Beta users lie about features but tell the truth about behavior: Don't ask what features they want. Watch what workflows they actually complete.
Problem severity beats solution elegance: A ugly solution to a severe problem will get used. A beautiful solution to a mild annoyance won't.
Set usage thresholds upfront: Define minimum activity levels that indicate real problem severity. If users don't hit these thresholds, pivot the problem, not the solution.
Beta cohort size matters less than beta cohort commitment: Better to have 8 users who desperately need this solved than 50 who think it might be nice to have.
Kill projects faster: Most beta tests should end in pivots or kills, not product launches. This is success, not failure.
Manual solutions reveal automation opportunities: Start with processes you can do manually before building automated solutions.
Beta users should become design partners, not just feedback providers: If they won't commit to helping you design the solution, they don't have the problem severely enough.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS startups specifically:
Start beta testing before you build, not after
Test problems with enterprise customers who have budget authority
Measure usage frequency, not feature satisfaction
Convert beta users to design partners with formal agreements
For your Ecommerce store
For ecommerce businesses running beta programs:
Test product concepts with real purchase behavior, not surveys
Use limited inventory to create urgency during beta
Focus on retention metrics over initial conversion
Beta test pricing sensitivity, not just product features