Growth & Strategy
Personas
SaaS & Startup
Time to ROI
Medium-term (3-6 months)
When I started working with a B2C e-commerce client, they had what looked like a solid business on paper. Single revenue channel, predictable Facebook ad spend, decent 2.5 ROAS. Most agencies would have called it a success and focused on optimizing what was already working.
But I saw a massive vulnerability hiding in plain sight: their entire growth engine depended on Meta's algorithm and ad costs. One iOS update, one policy change, one competitor bidding war, and their business could collapse overnight.
Three months later, we had transformed their single-channel dependency into a distribution machine generating revenue from multiple sources. But here's the thing - it wasn't about adding more channels randomly. It was about understanding that distribution beats product quality every single time, and building systems that scale without proportional resource increases.
Here's what you'll learn from my experience scaling distribution efforts:
Why the "test everything" approach actually kills scaling momentum
The distribution framework I use to prioritize channels based on compound growth potential
How to build dark funnel coverage that multiplies your apparent ROAS
The automation systems that let you scale without hiring a team
Why attribution lies are actually your friend when scaling distribution
If you're stuck in single-channel dependency or struggling to scale beyond your first profitable channel, this playbook will show you the systematic approach I've used across multiple client projects. Check out our growth strategies for more distribution insights.
Industry Reality
The distribution advice that's everywhere but doesn't scale
Every growth guru preaches the same distribution scripture: "Test all channels! Find your winners! Double down!" On the surface, this makes perfect sense. The bullseye framework teaches us to test systematically, and platforms like Reforge have built entire curriculums around channel diversification.
Here's what the industry typically recommends for scaling distribution efforts:
Channel Testing Approach: Run small experiments across 10-15 channels, measure performance, then scale the winners
Attribution Obsession: Track every touchpoint, optimize for last-click attribution, and kill underperforming channels based on direct ROI
Resource Allocation Model: Hire specialists for each channel - a Facebook ads expert, an SEO specialist, a content marketer, etc.
Platform Best Practices: Follow each platform's recommended strategies and optimize within their ecosystems
Linear Scaling Mindset: If Channel A generates $10k at $1k spend, then $10k spend should generate $100k
This conventional wisdom exists because it's safe, measurable, and fits neatly into quarterly planning cycles. Agencies love it because they can bill for multiple channel management, and attribution software companies built billion-dollar businesses selling the dream of perfect tracking.
But here's where this approach falls apart in practice: real customer journeys are messy, attribution is fundamentally broken in 2025, and the best distribution strategies create compound effects that can't be measured in isolation. Most businesses following this playbook end up with a bunch of mediocre channels that compete for the same audience, rather than a distribution machine that amplifies itself.
The breakthrough came when I stopped trying to control every touchpoint and started building for the dark funnel instead.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
The client was a Shopify store with a solid product catalog and had been running Facebook ads for over a year. When I first reviewed their setup, everything looked textbook perfect: good creative rotation, proper audience targeting, clean conversion tracking. The 2.5 ROAS was respectable for their industry.
But I've seen this movie before - businesses that look healthy on the surface but are actually one algorithm change away from disaster. Their entire customer acquisition strategy lived and died by Meta's ad auction. No email list growth, minimal organic traffic, zero word-of-mouth systems.
The wake-up call came during our first strategy session. I asked a simple question: "What happens if Facebook ads stop working tomorrow?" The silence told me everything. They had no backup plan, no alternative traffic sources, no distribution strategy beyond paying for visibility.
My first instinct was to follow the traditional playbook - let's test Google Ads, try some influencer partnerships, maybe spin up a content marketing program. But then I remembered a key insight from my SaaS work: distribution isn't about adding more channels, it's about creating coverage across the entire customer journey.
The real problem wasn't that they needed more traffic sources. The problem was that their customers were already interacting with their brand across multiple touchpoints, but they only had visibility into the final click. SEO traffic wasn't showing up because Facebook was claiming attribution. Word-of-mouth referrals looked like "direct" traffic. Their brand awareness efforts were invisible in the data.
That's when I realized we weren't dealing with a distribution problem - we were dealing with a measurement problem disguised as a scaling challenge. The solution wasn't to find new channels; it was to build a system that captured value from the dark funnel and created compound growth effects across touchpoints.
Here's my playbook
What I ended up doing and the results.
Instead of the traditional "test and scale" approach, I implemented what I call the Distribution Coverage Framework. The core insight: stop trying to measure individual channel performance and start building systems that amplify each other.
Phase 1: Dark Funnel Audit
First, I spent three weeks mapping the invisible customer journey. Using Google Analytics, customer surveys, and heat mapping tools, we discovered that 70% of their customers had multiple touchpoints before converting. Someone might see a Facebook ad, Google the brand name, read reviews on a third-party site, then come back "direct" to purchase.
The attribution system was giving Facebook credit for conversions that actually resulted from a complex journey involving organic search, social proof, and brand recall. This is why their "2.5 ROAS" Facebook campaign was actually part of a much more complex acquisition system.
Phase 2: SEO Foundation Layer
Rather than competing with paid ads, I built SEO as the foundation layer that would amplify paid performance. We created content hubs around their main product categories, optimized for branded searches, and built landing pages for high-intent keywords.
The key insight: SEO doesn't need to drive direct conversions to be valuable. When someone clicks a Facebook ad, then Googles the brand name and finds professional, optimized content, it increases the likelihood they'll convert from the original ad touchpoint.
Phase 3: Attribution Embrace Strategy
Here's where I broke from conventional wisdom: instead of trying to fix attribution, I embraced the lies. I set up tracking to understand directional trends rather than precise numbers. When Facebook reported an 8-9 ROAS increase after we launched SEO content, I didn't celebrate the "improved ad performance" - I recognized it as proof that our omnichannel strategy was working.
Phase 4: Compound Growth Systems
The final layer was building systems where each channel made the others more effective:
Content amplified ads: Blog posts became landing pages for specific ad campaigns, creating alignment between paid and organic messaging
Email enhanced retargeting: Email subscribers became custom audiences for more effective Facebook campaigns
Social proof multiplication: Reviews and testimonials collected through email flows became creative assets for ads and SEO content
Automation bridges: Zapier workflows connected different platforms to share data and trigger cross-channel campaigns
The beauty of this approach: each new channel made the existing channels more effective rather than competing for the same audience. We weren't just scaling distribution; we were scaling the multiplier effects between channels.
Channel Synergy
Focus on channels that amplify each other rather than competing for the same audience. SEO supports paid ads by improving brand searches.
Dark Funnel Coverage
Build systems to capture value from touchpoints you can't track. Your best distribution strategy might be invisible in your analytics.
Attribution Acceptance
Embrace that attribution is broken. Use directional data to understand trends rather than precise channel performance.
Automation Bridges
Connect channels through automated workflows. Let each touchpoint trigger relevant actions in other channels rather than operating in silos.
Within 90 days, the results spoke for themselves, but not in the way most people expect to measure distribution success.
The measurable metrics: Organic traffic increased from virtually zero to 15% of total site traffic. Email list growth accelerated 300%. Direct traffic (the mysterious category) jumped 40%, which I interpret as improved brand recall and word-of-mouth.
The compound effects: Facebook's reported ROAS jumped from 2.5 to 8-9, but this wasn't because the ads got better - it was because the supporting infrastructure made the entire customer journey more effective. When someone clicked an ad and found professionally optimized organic content reinforcing the same value proposition, conversion rates improved across the board.
The resilience test: When iOS 14.5 privacy updates hit the industry six months later, their business barely felt the impact. While competitors saw their Facebook performance crater, this client had built enough distribution diversification to maintain growth. The SEO foundation we'd built became their primary acquisition channel during the attribution apocalypse.
The unexpected outcome: The most valuable result wasn't any single channel's performance - it was building a distribution machine that became more valuable than the sum of its parts. Each new touchpoint made every other touchpoint more effective, creating sustainable competitive advantages that couldn't be easily replicated.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
Here are the top insights from scaling distribution efforts across multiple client projects:
Distribution beats optimization: Adding a new effective channel will always outperform optimizing an existing one by 10%. Focus 80% of your effort on coverage, 20% on optimization.
Measure systems, not channels: The best distribution strategies create value that can't be attributed to individual touchpoints. If you can perfectly measure it, you're probably not thinking big enough.
Automation is your scaling advantage: Small teams can compete with agencies by building smart connections between channels rather than hiring specialists for each one.
The dark funnel is your friend: Your customers are having conversations about your brand that you can't track. Build systems to amplify these invisible touchpoints rather than trying to control them.
Start with foundation layers: SEO and email aren't sexy, but they make every other channel more effective. Build the infrastructure before adding the amplifiers.
Embrace attribution lies: When Facebook claims credit for conversions that involved organic search, celebrate it as proof your omnichannel strategy is working.
Think compound, not linear: The goal isn't 10 channels generating $10k each. The goal is 5 channels that make each other 2x more effective.
The biggest mistake I see businesses make is treating distribution scaling like a math problem - more channels equals more growth. In reality, it's a systems problem. The businesses that win build distribution machines where each component amplifies the others, rather than competing for the same limited attention.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS startups looking to scale distribution efforts:
Build SEO content around use cases and integrations before scaling paid ads
Use email sequences to nurture users across multiple touchpoints rather than single conversion events
Focus on product-led growth loops that turn users into distribution channels
Create API documentation and integration guides that serve as SEO-optimized landing pages
For your Ecommerce store
For e-commerce stores scaling distribution:
Build category and product pages optimized for organic search before increasing ad spend
Use email automation to create custom audiences for more effective paid campaigns
Implement review collection systems that feed content back into ads and SEO
Create gift guides and seasonal content that amplify paid promotional campaigns