Growth & Strategy
Personas
SaaS & Startup
Time to ROI
Medium-term (3-6 months)
OK so here's the thing about getting traction strategies - most advice you'll find online is complete bullshit. I'm talking about those "growth hacking" articles that tell you to "just create viral content" or "leverage influencers" without actually explaining how to do any of it.
When I started working with SaaS startups as a freelancer, I kept seeing the same pattern. Founders would come to me saying "we need more users" but when I'd dig deeper, they hadn't even validated if people actually wanted what they were building. They were obsessing over conversion optimization and paid ads when they should have been focusing on finding product-market fit first.
Here's what I learned after working with dozens of startups: distribution beats product quality every time. You can have the most beautiful, feature-rich product in the world, but if nobody knows about it, you're essentially running a beautiful store in an empty mall.
In this playbook, I'm going to walk you through the exact framework I developed after seeing too many startups waste money on the wrong channels. You'll learn:
Why the bullseye method actually works better than spray-and-pray marketing
How to validate traction channels before spending a single dollar
The manual tactics that don't scale but get you your first 100 customers
When to transition from manual validation to scalable systems
The distribution-first mindset that changes everything
This isn't another theory-heavy post. This is the exact playbook I use with clients, complete with the mistakes we made and what actually moved the needle.
Reality Check
What startup advisors won't tell you about traction
Let's start with what every startup founder has heard at least a hundred times: "Build something people want, and they will come." This is the classic Silicon Valley wisdom that sounds profound but is actually terrible advice in practice.
The traditional approach to getting traction usually follows this pattern:
Build an MVP - Spend months perfecting your product features
Launch on Product Hunt - Hope for a viral moment that brings thousands of users
Try growth hacking tactics - Implement referral programs, viral loops, and gamification
Scale paid advertising - Throw money at Facebook and Google ads
Focus on conversion optimization - A/B test your way to growth
Here's why this approach fails for 90% of startups: you're optimizing for the wrong thing. You're treating distribution as an afterthought when it should be your primary focus from day one.
The problem with most traction advice is that it assumes you already have product-market fit. But if you're struggling to get traction, chances are you don't have PMF yet - and no amount of growth hacking will fix that fundamental issue.
Most founders spend 90% of their time building the product and 10% thinking about distribution. It should be the reverse. The technology to build products has never been easier, but the challenge of getting noticed in a crowded market has never been harder.
The industry tells you to "find your growth channels" but doesn't explain how to systematically test and validate channels before committing resources. That's where most startups burn through their runway - throwing money at channels that were never going to work for their specific business model.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
So let me tell you about this B2B SaaS client I worked with last year. They came to me frustrated because they'd been "doing marketing" for eight months with almost nothing to show for it. They had a decent product - a project management tool for creative agencies - but were getting maybe 10 signups per month.
When I audited their approach, I found the classic mistake: they were trying to do everything at once. Facebook ads, Google ads, content marketing, cold email, partnerships - you name it. But none of it was working because they hadn't actually validated what channels their ideal customers used.
The founder kept saying "we need to scale" but when I asked basic questions like "where do your best customers hang out online?" or "what problem were they trying to solve before they found you?" - crickets. They had no idea.
Their customer acquisition was completely random. Sometimes they'd get a signup from a blog post, sometimes from a Google ad, sometimes from word of mouth. But there was no systematic way to understand what was working and why.
The real kicker? They were spending $3,000 per month on paid ads but couldn't tell me the lifetime value of their customers or which channels brought in users who actually stuck around. They were optimizing for vanity metrics instead of real business outcomes.
What I realized was that they needed to go back to basics. Instead of trying to scale channels that weren't proven, we needed to find one channel that worked and double down on it. But first, we had to understand their customers better than they understood themselves.
This is when I introduced them to what I call the "distribution-first" approach to getting traction. Instead of building more features and hoping customers would find them, we flipped the script and started with distribution.
Here's my playbook
What I ended up doing and the results.
Here's the exact framework I developed after seeing this pattern repeat with multiple clients. I call it the Manual-to-Scale Validation Framework, and it's based on a simple principle: validate channels manually before you automate them.
Phase 1: Customer Interview Deep Dive
Before testing any channels, we spent two weeks doing intensive customer interviews. Not product feedback sessions - distribution research. We asked questions like:
"What were you doing the day before you signed up for our tool?"
"Where do you typically look for solutions to business problems?"
"What blogs, podcasts, or communities do you follow?"
"How did you hear about your last three software purchases?"
From 15 interviews, a clear pattern emerged: their best customers were active in specific Facebook groups for creative agency owners and listened to two particular podcasts.
Phase 2: The Manual Channel Test
Instead of buying ads or building complex funnels, we started with the most manual approach possible. The founder began actively participating in those Facebook groups - not spamming, but genuinely helping people solve problems and occasionally mentioning their tool when relevant.
We also reached out to the podcast hosts with a simple offer: "We'll sponsor one episode for $500, but instead of a traditional ad, let us share a specific case study that would be valuable to your audience."
The key insight: we weren't trying to scale yet. We were trying to validate that these channels could produce quality leads at all.
Phase 3: The Bullseye Method in Practice
After four weeks of manual testing, we had data. The Facebook groups were producing 2-3 qualified leads per week, and the podcast sponsorship brought in 12 leads from one episode. Now we could start systematically testing and scaling.
Using the bullseye method, we ranked potential channels based on our manual experiments:
High potential: Facebook group engagement, podcast sponsorships
Medium potential: LinkedIn content, industry newsletter sponsorships
Low potential: Google ads, cold email (too competitive/saturated)
Phase 4: The Scale Transition
Once we validated the channels manually, we could start building systems. We created a content calendar for Facebook groups, developed relationships with multiple podcast hosts, and eventually hired a community manager to scale the personal outreach.
But here's the crucial part: we only scaled what we'd already proven worked manually. No more throwing money at unproven channels.
Channel Validation
Test manually before spending on automation or ads
Distribution Research
Interview customers about where they discover solutions
Manual Outreach
Start with personal, non-scalable tactics that work
Systematic Scaling
Only automate channels you've proven manually
Within three months, this client went from 10 signups per month to 85. But more importantly, their customer quality improved dramatically because we were reaching people where they actually spent time, not where we thought they should be.
The manual Facebook group engagement evolved into a systematic content strategy that drove 40% of their new signups. The podcast sponsorships became a predictable channel - we could invest $500 and reliably get 8-12 qualified leads.
What surprised everyone was that their Google ads performance actually improved once we understood their customers better. We weren't just targeting keywords anymore; we were targeting the exact phrases their ideal customers used when describing their problems.
The founder told me: "I wish we'd done this customer research eighteen months ago. We wasted so much money trying to make channels work that were never going to work for our business."
By month six, they had predictable, sustainable growth and could accurately forecast their customer acquisition costs across different channels. More importantly, they finally understood what distribution-product fit meant for their specific business.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
Looking back on this project and similar ones, here are the key lessons that completely changed how I think about getting traction:
Distribution research beats product research - Spend more time understanding where your customers hang out than what features they want
Manual validation prevents expensive mistakes - A week of manual outreach can save you months of failed ad campaigns
Channel-market fit is real - What works for other companies might not work for yours, even in the same industry
Quality beats quantity in early stages - 10 engaged customers are worth more than 100 tire-kickers
Build systems around proven channels - Don't automate until you've manually proven something works
Customer interviews reveal distribution channels - Ask about behavior, not preferences
The bullseye method works - But only if you actually test channels systematically instead of guessing
The biggest mistake I see startups make is treating distribution as a growth problem when it's actually a research problem. You can't growth-hack your way to traction if you don't understand your customers' behavior patterns.
Remember: your goal isn't to find the perfect growth channel - it's to find one channel that works and master it before moving to the next one.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS startups implementing this playbook:
Start with 15 customer interviews focused on discovery behavior, not product feedback
Test channels manually for 2-4 weeks before investing in automation
Track channel quality, not just quantity - measure trial-to-paid conversion by source
Focus on one proven channel before testing others
For your Ecommerce store
For ecommerce stores applying these strategies:
Interview customers about their discovery process, not just purchase decisions
Test community engagement before paid social media advertising
Validate channel-product fit through manual outreach first
Scale successful conversion channels systematically