Growth & Strategy
Personas
SaaS & Startup
Time to ROI
Medium-term (3-6 months)
Last month, a client called me frustrated. Their Facebook ROAS jumped from 2.5 to 8-9 overnight, and their marketing team was celebrating. "We finally cracked the code!" they said.
I had to break some hearts that day.
The reality? Their SEO strategy had started driving significant conversions, but Facebook's attribution model was stealing all the credit. This is the dirty secret of modern marketing: your attribution is lying to you, and you're making decisions based on fantasy data.
After 7 years building websites and implementing tracking systems for SaaS and ecommerce clients, I've learned that product-channel fit issues often mask themselves as attribution problems. Most businesses think they need better tracking when they actually need better understanding of their customer journey.
Here's what you'll learn from my real-world experiments:
Why Facebook's 8x ROAS was actually an SEO win in disguise
The "dark funnel" approach that reveals true customer behavior
How to track without trying to control every touchpoint
A 3-month framework for building attribution that actually works
Real metrics from clients who stopped chasing perfect attribution
This isn't another post about UTM parameters. This is about embracing the chaos of modern customer journeys and building systems that work with reality, not against it.
Industry Reality
What Every Marketer Gets Wrong About Attribution
Walk into any marketing meeting, and you'll hear the same obsessions. "We need better attribution." "Let's implement first-touch tracking." "Why can't we see the complete customer journey?"
The industry has convinced us that perfect attribution is possible if we just use the right tools. Marketers spend thousands on complex tracking systems, believing they can map every touchpoint from awareness to conversion.
Here's what the "experts" typically recommend:
Multi-touch attribution models - Track every interaction across every channel
UTM parameter obsession - Tag everything with detailed campaign tracking
Cross-device tracking - Follow users from mobile to desktop
First-party data collection - Build detailed user profiles
Attribution software - Invest in expensive platforms that promise clarity
This conventional wisdom exists because marketers hate uncertainty. We want to believe that marketing is a science where we can control variables and predict outcomes. The software industry feeds this fantasy by selling "complete visibility" and "360-degree customer views."
But here's where this approach fails in practice: the customer journey isn't linear. People don't follow neat attribution models. They Google your brand after seeing a Facebook ad. They bookmark your site after a LinkedIn post. They sign up weeks later after three different touchpoints you never tracked.
The harder you try to track everything, the more you discover you're missing. And while you're obsessing over attribution accuracy, your competitors are focusing on distribution and reach.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
When I started working with this e-commerce client, they were drowning in attribution confusion. They had Facebook Ads generating a 2.5 ROAS with a €50 average order value. On paper, it looked decent. But their margins were thin, and something felt off about the math.
The client was typical of what I see: over-reliant on a single channel (Facebook) and terrified of what would happen if that channel died. They'd built their entire growth engine around Meta's algorithm and ad costs, creating a dangerous single point of failure.
Here's what their "beautiful" attribution dashboard was telling them:
Facebook Ads: 2.5 ROAS, driving 70% of conversions
Direct traffic: 20% of conversions ("loyal customers")
SEO: 10% of conversions ("nice to have")
But when I dug deeper into their Google Analytics, I noticed something strange. Their direct traffic had unusual patterns - people typing in very specific product URLs, not just the homepage. Users were arriving with clear purchase intent, not browsing behavior.
That's when I realized: their attribution was fundamentally broken. Those "direct" conversions weren't loyal customers returning. They were people who had discovered the brand through organic search, bookmarked products, and returned later to buy.
The real customer journey looked like this:
User searches for specific product on Google
Finds the site through organic results
Browses, maybe sees a retargeting ad on Facebook
Returns by typing the URL directly
Facebook gets the conversion credit
This client wasn't alone. I'd seen this pattern before with other projects, but this was the most dramatic example of attribution lies destroying strategic decisions.
Here's my playbook
What I ended up doing and the results.
Instead of chasing perfect attribution, I implemented what I call the "Dark Funnel Acceptance Framework." This approach acknowledges that modern customer journeys are messy and focuses on understanding patterns rather than tracking individual paths.
Month 1: Stop Believing Your Current Data
First, we conducted an "attribution audit." I analyzed three months of data looking for these red flags:
Unusual "direct" traffic patterns (specific product URLs)
High-intent keywords driving "low-value" traffic
Channels showing amazing performance that felt too good to be true
The audit revealed that 40% of their "direct" conversions were actually coming from organic search behavior. Users would Google "[brand] + [product]" after initial discovery, then return later via direct URL entry.
Month 2: Build Omnichannel Presence
Rather than trying to track everything perfectly, we focused on being discoverable everywhere customers might look. I implemented a comprehensive SEO strategy while maintaining the Facebook ads:
Complete website restructuring for SEO optimization
Content strategy targeting search intent, not just brand messaging
Local SEO for geographic targeting
Long-tail keyword targeting for product discovery
The key insight: instead of trying to control the customer journey, we made sure we'd be found at every possible touchpoint.
Month 3: Measure Coverage, Not Attribution
We shifted metrics from "which channel gets credit" to "how well are we covering the customer journey." New KPIs included:
Brand search volume growth
Organic traffic quality (time on site, pages per session)
Multi-channel conversion patterns
Customer lifetime value by discovery method
The results were immediate. Within a month of implementing SEO, Facebook's reported ROAS jumped to 8-9. But I knew better – SEO was driving the growth, Facebook was just getting the credit.
This taught me the most important lesson about modern attribution: distribution beats attribution. Focus on being everywhere your customers are, not on perfectly tracking how they found you.
Attribution Reality
Stop trying to track the untrackable. Focus on being discoverable across all touchpoints where customers research and buy.
Channel Coverage
Map all possible customer touchpoints and ensure you have presence, not perfect tracking, at each stage of their journey.
Pattern Recognition
Look for unusual traffic patterns that reveal hidden attribution. Direct traffic with specific URLs often masks other channel influence.
Metric Evolution
Shift from attribution accuracy to coverage metrics. Measure brand search growth and cross-channel engagement patterns instead.
The transformation was dramatic but took time to understand. Here's what actually happened over the 3-month implementation:
Month 1 Results:
Discovered 40% of "direct" traffic was misattributed SEO
Found 60% of customers touched 3+ channels before converting
Identified the real customer journey patterns
Month 2-3 Transformation:
Organic traffic increased from 300 to 1,200+ monthly visitors
Facebook "ROAS" jumped to 8-9 (but we knew why)
Overall conversion rate improved 45% with better channel coordination
But the most important result wasn't visible in any dashboard: the client stopped making decisions based on attribution fantasy. They understood that their success came from comprehensive channel coverage, not perfect tracking.
Six months later, when iOS 14.5 broke everyone's Facebook tracking, this client barely noticed. They'd already built a business model that didn't depend on platform-specific attribution.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
Here are the 7 key lessons from implementing cross-channel tracking that actually works:
Attribution lies, patterns tell truth. Stop believing individual channel reports. Look for customer behavior patterns across all touchpoints.
Direct traffic is never really direct. When you see specific product URLs in direct traffic, someone found you elsewhere first.
Coverage beats precision. Being discoverable everywhere matters more than tracking everywhere perfectly.
Channels don't work in isolation. Your Facebook ads work better when you have strong SEO. Your SEO works better with retargeting support.
Customer journeys are non-linear. People research on mobile, buy on desktop, and return via bookmarks. Plan for complexity.
Platform attribution is self-serving. Facebook, Google, and every other platform will overstate their impact. That's how they make money.
Focus on total business growth. If overall conversions and revenue are increasing, worry less about which channel gets credit.
This approach works best for businesses with multiple customer touchpoints and longer consideration cycles. It's less effective for simple, impulse-purchase products where single-touch attribution actually reflects reality.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS implementing cross-channel tracking:
Track trial-to-paid conversion patterns by discovery source
Monitor brand search volume as a leading indicator
Focus on content marketing for long sales cycles
Build retargeting around specific feature interests
For your Ecommerce store
For Ecommerce implementing cross-channel tracking:
Optimize for product discovery across all search platforms
Use email marketing to bridge channel gaps
Focus on customer lifetime value over single-purchase attribution
Implement consistent messaging across all touchpoints