Sales & Conversion
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 pre-sale landing pages in 2025. Most founders think they need to build first, then validate. But here's what I've learned after turning down that $XX,XXX project: your pre-sale landing page should do the heavy lifting before you write a single line of code.
The client came to me excited about the no-code revolution and new AI tools. 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."
After working with dozens of startups on their early validation strategies, here's what you'll learn from this playbook:
Why your MVP should be your marketing process, not your product
The exact pre-sale landing page framework I use for client validation
How to validate demand manually before building anything
The metrics that actually matter for pre-launch validation
When to pivot from validation to development
This isn't about fancy landing page builders or conversion optimization tricks. It's about fundamentally changing how you think about product validation. Building with AI tools is easier than ever, but knowing what to build and for whom remains the biggest challenge.
Market Reality
What every startup founder gets wrong about validation
Walk into any startup accelerator, and you'll hear the same advice repeated like gospel: "Build an MVP, get user feedback, iterate quickly." The standard playbook looks something like this:
Build a minimum viable product with basic features
Launch to a small group of beta users
Collect feedback and usage data
Iterate based on insights from real users
Scale what works and eliminate what doesn't
This conventional wisdom exists because it worked in the past. When building software required months of development and significant upfront investment, the MVP approach minimized risk by getting something to market quickly.
Here's where this falls short in practice: even "minimum" viable products take significant time and resources to build properly. Most founders spend 3-6 months building their MVP, only to discover fundamental flaws in their assumptions. By then, they're emotionally and financially invested in a solution that might not have a market.
The bigger issue? The industry confuses validation with building. True validation happens before you write code, not after. Product-market fit requires understanding demand first, then building the solution.
The shift that's happening now: with AI and no-code tools making development faster and cheaper, the constraint isn't building anymore — it's knowing what to build and for whom. Your pre-sale landing page becomes your true MVP: a way to validate demand, understand your audience, and refine your value proposition before investing in development.
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 no existing audience, no validated customer base, and no proof of demand. Just an idea and enthusiasm. They wanted to spend months building a complex platform to "test if their idea works."
This reminded me of a pattern I'd seen repeatedly: founders treating their product as their validation tool instead of their marketing process. The fundamental flaw in their approach wasn't the technology choice — it was the assumption that building would teach them about their market.
I told them something that initially shocked them: "If you're truly testing market demand, your MVP should take one day to build — not three months."
Here's what I recommended instead: Rather than building their platform, I suggested they create a simple landing page explaining their value proposition, start manual outreach to potential users on both sides of their marketplace, and manually match supply and demand via email for the first month.
The client's reaction was telling. They pushed back, saying this approach wouldn't give them "real" data about user behavior. But that's exactly the point — you don't need to understand user behavior until you've proven people want your solution.
This experience reinforced something I'd learned from previous client projects: distribution and validation come before development. Most founders have this backwards. They think building creates demand, when actually understanding demand should drive what you build.
The marketplace client ultimately went elsewhere, probably to build their platform. But this conversation crystallized my approach to pre-sale validation: your landing page isn't a marketing tool — it's your business model validation engine.
Here's my playbook
What I ended up doing and the results.
Based on this experience and similar client situations, I developed a systematic approach to pre-sale landing page strategy that validates demand before development begins.
Phase 1: The One-Day Landing Page (Day 1)
Instead of spending weeks perfecting a landing page, I create what I call a "demand probe" — a simple page that tests one core hypothesis. For the marketplace client, this would have been: "Do potential users on both sides of this market actually want this solution?"
The page structure I use:
Problem-focused headline that speaks to genuine pain points
Simple value proposition in one clear sentence
Three bullet points explaining the core benefits
Email capture form with the promise: "Get notified when we launch"
Optional survey asking "What's your biggest challenge with [problem]?"
This isn't about conversion optimization or beautiful design. It's about testing demand with minimal investment.
Phase 2: Manual Market Testing (Week 1-4)
While the landing page collects passive interest, I run active validation experiments:
Direct outreach to potential users — not selling, but understanding their current solutions and pain points
Manual process simulation — if it's a marketplace, manually match buyers and sellers via email or WhatsApp
Payment intent testing — ask people if they'd pay for this solution and at what price point
Competitive analysis — understand how people currently solve this problem
The key insight: if you can't manually create the value your product promises, automation won't solve the fundamental problem.
Phase 3: Validation Metrics (Month 2)
After 30 days of manual testing, I look at specific metrics to determine if there's genuine demand:
Email signup rate from organic traffic (should be >15%)
Response rate to direct outreach (should be >10%)
Payment intent conversion from conversations (should be >30%)
Manual transaction success rate (should be >50%)
Only after proving demand through manual processes do I recommend building automation. This approach prevents the expensive mistake of building solutions for problems that don't exist or markets that aren't ready to pay.
Demand Validation
Test market appetite before building anything. Manual outreach and email capture reveal genuine interest levels.
Process Simulation
Manually deliver your promised value first. If you can't do it manually, automation won't fix the core problem.
Payment Intent
Ask for money before building. Even pre-orders or deposits indicate stronger demand than email signups alone.
Pivot Indicators
Set clear metrics for go/no-go decisions. Bad numbers early save months of development on the wrong solution.
The results from this approach have been consistently revealing. In the case of similar pre-sale validation projects I've worked on, the metrics tell the real story:
Most ideas that founders are excited about fail the manual validation test. When you're forced to create value manually, you quickly discover if there's genuine demand or if you're solving a problem that doesn't exist.
The successful validations I've seen typically show:
High email signup rates from people finding the landing page organically
Strong response rates to cold outreach when the problem resonates
Willingness to pay even for manual processes that deliver value
Word-of-mouth growth when early users see genuine value
The failed validations show the opposite: low engagement, weak responses to outreach, and resistance to paying for manual solutions. This feedback comes in weeks, not months, saving significant time and resources.
The most important outcome isn't just validation — it's understanding. By the time you decide to build, you know exactly who your customers are, what they'll pay for, and how they currently solve their problems. This insight makes the eventual product development much more focused and effective.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
Here are the key lessons I've learned from implementing this pre-sale landing page strategy across multiple client projects:
Manual first, automation second — If you can't deliver value manually, technology won't solve the fundamental problem
Demand beats features — Proven market demand is more valuable than product features
Speed of learning matters — Get to "no" quickly if there's no market, or "yes" if there is
Payment intent is the ultimate validator — People saying they'll pay is different from people actually paying
Distribution comes before development — Understanding how to reach customers matters more than product features
Simple pages work better — Complex landing pages distract from the core validation goal
Personal outreach scales validation — Manual conversations provide insights no analytics can capture
What I'd do differently: I'd push even harder on payment validation earlier. Getting people to put down a deposit or pre-order is the strongest signal of genuine demand. Everything else is just interest.
This approach works best when you're testing new market opportunities or unproven business models. It's less useful when you're iterating on existing products with established demand.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS startups, focus on:
Validate workflow integration manually first
Test willingness to switch from current tools
Understand buying processes and decision makers
Measure time-to-value expectations
For your Ecommerce store
For ecommerce stores, prioritize:
Test product demand before inventory investment
Validate price points and margin expectations
Understand customer acquisition channels
Manual fulfillment testing for service quality