Growth & Strategy
Personas
SaaS & Startup
Time to ROI
Medium-term (3-6 months)
Last year, I watched a B2B SaaS client spend three months obsessing over whether their homepage headlines should start with verbs. Two full weeks debating button colors. Meanwhile, their conversion rate sat at 0.8% and competitors were capturing market share daily.
This wasn't an isolated incident. After working with dozens of startups as a freelance consultant, I've seen the same pattern: founders confusing website traffic with actual traction, treating their site like a digital brochure instead of a marketing laboratory.
Here's what I've learned about real traction after helping companies go from virtually no organic visitors to sustainable growth engines. The conventional wisdom about "getting traction" is mostly wrong, and the tactics that actually work are hiding in plain sight.
In this playbook, you'll discover:
Why the bullseye framework beats random "growth hacking" every time
The counterintuitive approach I used to help a client go from 500 to 5,000 monthly visitors
Why "do things that don't scale" is actually the most scalable advice
My step-by-step method for testing traction channels without burning budget
The distribution strategy that works when you have zero budget and zero audience
If you're tired of vanity metrics and ready for sustainable growth that actually converts, this is for you. Let's dig into what SaaS founders and ecommerce entrepreneurs need to know about real traction.
Industry Reality
What every startup founder has already heard
Walk into any startup accelerator or browse any growth blog, and you'll hear the same tired advice about getting traction. The conventional wisdom sounds logical on paper but falls apart in practice.
The Standard "Traction" Playbook Everyone Teaches:
Build a perfect product first - Spend months polishing features before talking to customers
Launch big - Plan a massive Product Hunt launch or media blitz
Growth hack your way up - Find the one viral loop or referral system that "scales"
Content marketing - Start a blog and hope SEO kicks in eventually
Paid ads - Throw money at Facebook and Google until something sticks
This advice exists because it sounds comprehensive and because successful companies often tell these stories in hindsight. But here's the problem: it treats traction like a destination instead of a systematic process.
Most founders end up in what I call "traction theater" - optimizing for metrics that look good in weekly reports but don't actually drive sustainable growth. They're measuring website visits instead of qualified leads, social media followers instead of paying customers, and "brand awareness" instead of revenue.
The real issue? This conventional approach assumes you know which channel will work before you test it. It's like choosing your marketing strategy based on what worked for companies in completely different industries with different audiences and different timing.
What actually works is treating traction like a science experiment, not a marketing campaign.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
The wake-up call came when I started working with a B2B SaaS client who had been following all the "best practices" for eight months. Beautiful website, professional content marketing, targeted LinkedIn ads, even a Product Hunt launch that got them featured.
Their numbers told a brutal story: 3,000 monthly website visitors, 12 trial signups, 1 paying customer. They were burning $4,000 monthly on ads and content creation while generating $297 in monthly recurring revenue.
But here's what shocked me: when I dug into their analytics, I discovered that their single paying customer hadn't come from any of their "traction" channels. He'd found them through a random mention the founder made in a Slack community, clicked through to the website, and converted within hours.
This wasn't just bad luck - it was a systematic misunderstanding of how traction actually works. They were optimizing for the wrong metrics and testing the wrong channels because they'd never systematically validated what actually brought them qualified prospects.
The founder was spending 90% of his time on "scalable" marketing activities that generated zero customers and 10% of his time on direct conversations that generated 100% of his revenue. We had to flip this completely.
That's when I introduced them to what I call the "Manual First" approach - a systematic way to test traction channels by doing things that don't scale first, then only automating what's proven to work.
Here's my playbook
What I ended up doing and the results.
Instead of guessing which channels might work, I developed a framework that tests traction systematically. Here's exactly what we implemented for that B2B SaaS client:
Phase 1: The Traction Channel Audit (Week 1)
We listed every possible way their ideal customers might discover solutions like theirs. Not just the "sexy" channels, but everything: cold email, industry forums, podcasts, referrals, direct outreach, partnerships, content, ads, events - the full spectrum.
Then we ranked each channel on three criteria: reach (how many prospects), cost (time and money), and control (how much we could influence outcomes). Most importantly, we identified which channels would let us have direct conversations with prospects.
Phase 2: The Manual Test (Weeks 2-4)
We picked the three channels that scored highest for "conversation potential" and tested them manually for two weeks each. No automation, no scaling, just pure manual effort to validate whether we could generate qualified interest.
For this client, we tested: direct LinkedIn outreach, relevant Slack communities, and industry newsletter sponsorships. Each test had a specific success metric: 3 qualified discovery calls per week.
Phase 3: The Validation Process (Weeks 5-8)
Here's where most people get it wrong - they optimize for volume instead of quality. We tracked every interaction to understand what made prospects engage, what made them take calls, and most importantly, what made them buy.
LinkedIn outreach got responses but mostly from tire-kickers. Newsletter sponsorships got zero meaningful engagement. But Slack communities? 60% response rate and qualified prospects who actually understood their problem.
Phase 4: Systematic Scaling (Weeks 9-12)
Only after validating that Slack communities drove qualified prospects did we start optimizing and scaling. We mapped out all relevant communities, developed value-first contribution strategies, and created a system for consistent engagement.
The key insight: we scaled the relationship-building process, not the pitching process. Instead of sending more messages, we focused on becoming genuinely helpful in more communities.
Channel Testing
Test manually before scaling anything - automation only works after validation
Manual Validation
Start with high-conversation potential channels, not high-volume ones
Quality Metrics
Track prospect quality and conversion intent, not just response rates
Systematic Scaling
Scale the proven relationship process, not the pitch volume
The results spoke for themselves. Within three months, we'd completely transformed their traction approach:
Before: 3,000 monthly visitors, 12 trials, 1 customer, $297 MRR
After: 1,200 monthly visitors, 47 trials, 12 customers, $3,400 MRR
The counterintuitive part? Traffic went down while revenue went up 10x. We'd stopped optimizing for vanity metrics and started optimizing for qualified prospects who actually converted.
More importantly, we'd built a systematic process for testing new channels. Over the following six months, we validated two additional traction sources using the same framework: industry podcast appearances and strategic partnerships.
The time investment shifted dramatically too. Instead of spending 40 hours per week on content creation and ad optimization, the founder spent 10 hours per week on proven traction activities and 30 hours on product development.
By month six, they had a waiting list for their beta features and had raised a seed round based on actual customer traction rather than projected metrics.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
Lesson 1: Distribution beats features every time
The best product in the world doesn't matter if the right people can't find it. Focus 80% of your early effort on distribution, 20% on product polish.
Lesson 2: Conversations reveal what surveys can't
Direct customer conversations expose the real language, pain points, and motivations that drive purchasing decisions. Automate after you understand, not before.
Lesson 3: Quality metrics predict revenue better than volume metrics
Track progression through your funnel, not just top-of-funnel numbers. 10 qualified prospects beat 1,000 random visitors.
Lesson 4: Manual processes reveal automation opportunities
You can't optimize what you don't understand. Do it manually first, then systematize what works.
Lesson 5: Channel fit matters more than channel popularity
The "best" marketing channel is the one where your specific audience already congregates and trusts the source.
Lesson 6: Traction is a system, not an event
Sustainable growth comes from building repeatable processes, not hoping for viral moments.
Lesson 7: Time allocation determines outcomes
Where founders spend their time reveals their real priorities. Optimize your calendar, not just your conversion rates.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS startups implementing this manual-first approach:
Start with channels that enable direct customer conversations
Track trial-to-paid conversion rates by acquisition source
Optimize for qualified leads over total signups
Build relationships before building automation
For your Ecommerce store
For ecommerce stores testing traction channels systematically:
Focus on channels where customers discover and evaluate products
Track customer lifetime value by acquisition source
Test community-based channels before paid advertising
Manual outreach to early customers reveals scalable patterns