Most GTM strategies fail not because they're wrong, but because they're solving yesterday's problems.
Here's the thing about perfection in GTM - it's a mirage that keeps moving away as you chase it. As someone who obsesses over every pixel in design (yes, I'm that Apple fanboy who can quote Steve Jobs), I had to learn this lesson the hard way. Sometimes the most perfect thing you can do is to be imperfect but right.
When founders ask me about go-to-market strategy, they usually want a roadmap, full-blown calculated strategies. What they need is a compass. After 14 years of helping a few B2B tech companies navigate market entry both in Vietnam and Singapore (a few of them are Decision Lab, Trusting Social, Grove HR, Atalink, Rework.com, Filum.ai, Omni HR, and Esevel), I and my co-founder we’ve noticed something counter-intuitive: the companies that succeed fastest are rarely the ones with the most detailed plans.
In fact, the best GTM strategies often look messy from the outside, quite the contrary. They're full of quick turns, unexpected discoveries, and moments that look like mistakes until they don't.
The conventional playbook says you need everything figured out before you move: detailed market research, perfect positioning, complete marketing infrastructure, full team. Believe me, I've attended countless webinars, can't even remember how many books and downloads or frameworks I’ve digested and internalized—indeed those are the kind of advice that sounds smart in board meetings but commonly fails in real markets.
We learned this firsthand helping Rework.com enter six new markets. Traditional wisdom said to do it sequentially. Build one market, then move to the next, then you are rounded up as a success. Makes sense, right?
Instead, we did something that probably looked quite reckless to outsiders: we launched in all markets almost simultaneously. Not because we can see the future, but because we'd learned something very important about modern B2B tech markets: the ability to learn quickly is more valuable than the ability to plan perfectly (for this one, most of the startup influencers get it right - Fail fast, and pivot quickly).
Within 4.5 weeks, we had our first customer. Within a few months, 68 customers across all markets. We didn't say it's a remarkable result, but give them enough traction for scaling-up. The key? We built a learning engine instead of a perfect plan.
Like Jobs's famous 'connecting the dots' philosophy, you can only understand the value of a learning engine by looking backward. But you have to build it moving forward. Here's what this really means:
Think of modern GTM like this: you're not building a road to market. You're building a vehicle that can navigate any terrain it encounters – the 4WD vehicle and you do need those especially when entering uncharted territory. This vehicle has four key components:
Instead of annual market reports, you need real-time signal detection. When we helped Filum.ai launch their CX management platform in Vietnam, traditional analysis said the market wasn't ready. But our signal detection picked up something different: enterprises were quietly struggling with exactly the problems Filum.ai solved.
Every interaction, whether successful or not, should feed back into your system. With NetNam's livestream services, each customer conversation reshaped our understanding. We didn't just collect feedback; we built a system that could turn feedback into action within days. This required close collaboration between us and our clients, the kind of in-house setting you usually anticipated, but in a more agile and effective way.
The key isn't having a perfect plan; it's having clear triggers for when and how to adapt. What signals will cause you to shift resources? Change messaging? Adjust pricing? Testing new ads? The best GTM systems have clear answers to these questions.
This is the part most people miss. Your GTM system needs to be buildable in pieces but workable as a whole. Like how Amazon started with books but built systems that could eventually sell everything.
Yes, it’s going to be very counter-intuitive. So here's what's fascinating: the more markets you enter simultaneously, the better this system works. It seems to defy logic. Surely focusing on one market would be safer?
But here's what we've learned: markets inform each other. When we were helping Rework.com expand, insights from the Philippines helped us in Malaysia. Learnings from Australia accelerated our progress in other more developed markets. Each market became a learning lab that benefited all other markets. And yes, in this digital age, you have the luxury of multi-market entry, without breaking the bank.
While in hindsight, summarizing lessons like above seems to be easy, the reality is messier - and more beautiful - than any plan could capture. As Jobs would say, "Real artists ship." In GTM, real strategists learn.
Let me show you what this looks like in practice across different markets and stages, and it's wildly different from company to company, and the copy-paste method usually works halfway, so you do need to be creative, improvise and open-minded on the go.
When helping Filum.ai enter the market, we discovered something unexpected. The initial strategy focused heavily on their advanced AI capabilities - seemingly their strongest selling point. But our learning engine picked up a different signal: enterprise customers cared more about implementation success than AI sophistication.
We pivoted immediately. Instead of technical demos, we led with implementation methodology and success stories. Time-to-close dropped dramatically. A competitor with arguably better technology but a traditional GTM approach took months to achieve what we were doing in weeks.
This pattern of rapid learning and adaptation proved itself again with Omni HR, a Singapore-based HR tech startup. Their initial GTM approach focused on feature comprehensiveness. But our learning engine revealed that mid-market companies were more interested in specific pain point solutions. We adjusted, focused on targeted problem-solving, and built such strong traction that it contributed to their successful $7.4M fundraising in 2024.
With Esevel, another Singapore-based startup in IT management, we discovered that their complex offering needed a different approach. The learning engine helped us identify the precise entry points that resonated with enterprise IT leaders. The GTM system we built continues to drive their growth today.
It’s real because sometimes, the blockers are not the clients, the market difficulties but yourself. This is where my perfectionist tendencies used to clash with market realities. But I've learned that in GTM, like in product design, perfection is often the enemy of good enough to learn from. The confidence to ship something that isn't perfect but is right for right now - that's the real challenge.
The hardest part of implementing this approach isn't technical. It's psychological. It requires accepting that your initial GTM strategy will be wrong in some ways, and building systems to detect and correct those wrong assumptions quickly.
Most founders find this uncomfortable, we do as well, just like waiting for the perfect imaginary moment to propose to someone. We're taught to be confident, to have detailed plans, to know where we're going. But the best GTM strategies come from a different kind of confidence: the confidence to learn and adapt faster than your competition.
Build learning systems before you build detailed plans
Focus on signal detection over market research
Create adaptation protocols before you create marketing campaigns
Design for rapid evolution over perfect execution
And one last thing…, Steve Jobs’s famous closing line that I wanted to borrow to describe a very practical way we've learned: building an effective GTM system doesn't require massive teams or budgets, especially for pre-Series B startups. Just look at the evidence:
Rework.com scaled to 68 enterprise customers across 6 markets in 6 months
Filum.ai secured major enterprise deals within weeks
Omni HR built enough traction to raise $7.4M
The secret? They all leveraged Majoris Digital as their expert GTM team, integrating us deeply into their operations. Weekly strategy sessions with Rework.com, daily stand-ups for market maneuvering, tight collaboration with Filum.ai for rapid adaptation - this wasn't just outsourcing, it was strategic partnership.
The model that worked? They hired key managers to oversee GTM efforts while we provided the expertise, infrastructure, and execution. Omni HR used this approach to build strong traction before transitioning to their internal team. Esevel continues to leverage the GTM system we built together.
And just for the “final final” pitch — think about the ROI:
Traditional approach:
6-12 months building an in-house team
$300K-500K annual budget minimum
Months of trial and error
High fixed costs
Smart approach:
Start executing in weeks
Flexible, scaling costs
Proven systems and expertise
Internal control with external execution
For pre-Series B startups or similar revenue size businesses, this isn't just about saving money - it's about smart capital allocation (loved by most investors and VCs). Why build everything from scratch when you can leverage proven systems and expertise while maintaining strategic control?
Ready to explore this proven GTM approach? We want to have serious talk about building a learning engine that can drive your growth while keeping your organization lean and agile (tltrd save cost + faster).
One final thing—I interpreted quotes from my mentor, because in B2B tech, success isn't about building everything from scratch - it's about making smart choices about what to build and what to leverage.
Stay hungry for market insights. Stay foolish enough to challenge your assumptions.