Sales & Conversion
Personas
Ecommerce
Time to ROI
Medium-term (3-6 months)
When my e-commerce client told me their Facebook ROAS jumped from 2.5 to 8-9 overnight, I knew something was wrong. We hadn't changed any ad creative, targeting, or budget. The only thing we'd done was launch an SEO strategy a month earlier.
That's when I realized Facebook was claiming credit for organic conversions. The dark truth? Attribution lies, but distribution doesn't.
Most ecommerce stores are flying blind, trusting platform-reported metrics that inflate performance by 30-50%. You're making budget decisions based on fairy tales while your actual profit drivers remain invisible.
After working with multiple ecommerce clients, I've learned that product-channel fit issues often hide behind attribution problems. In this playbook, you'll discover:
Why Facebook's attribution model is fundamentally broken
How to build a free attribution system using Google Sheets and UTM parameters
The simple framework I use to track the real customer journey
Why embracing the "dark funnel" changed everything for my clients
Practical steps to implement omnichannel tracking without expensive tools
This isn't about perfect tracking - it's about getting close enough to the truth to make profitable decisions.
Industry Reality
What the expensive consultants won't tell you
Every ecommerce marketing guru preaches the same gospel: "Track everything perfectly." They'll sell you expensive attribution tools, complex customer data platforms, and multi-touch attribution models that promise to solve all your problems.
The typical industry approach looks like this:
Last-click attribution - Give all credit to the final touchpoint
First-click attribution - Credit the initial interaction
Linear attribution - Split credit equally across all touchpoints
Time-decay attribution - Give more credit to recent interactions
Position-based attribution - Weight first and last clicks more heavily
The problem? These models assume you can track everything. But the reality of modern ecommerce is messier:
iOS 14.5 killed Facebook's tracking accuracy. Third-party cookies are dying. Customers research on mobile but buy on desktop. They see your Instagram ad, Google your brand, read reviews, then buy weeks later through organic search.
The industry's response? More complex tools, more expensive software, more "sophisticated" tracking. But here's what they won't tell you: Perfect attribution is impossible, and chasing it is a waste of money.
The dark funnel - those unmeasurable interactions between awareness and purchase - accounts for 70-80% of the customer journey. Instead of fighting this reality, smart ecommerce operators learn to work with it.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
The breaking point came when I was analyzing data for an ecommerce client spending €10K monthly on Facebook ads. Their reported ROAS looked healthy at 2.5x, but something felt off when I looked at their actual profit margins.
This client had over 1,000 SKUs - everything from artisanal home goods to tech accessories. Facebook Ads demands quick decisions, but their customers needed time to browse, compare, and discover the right products. The mismatch was obvious, but the attribution data was telling a different story.
Then we launched an SEO overhaul: website revamp, content optimization for their extensive catalog, strategic content creation targeting long-tail keywords. Within a month, something bizarre happened - Facebook's reported ROAS jumped to 8-9x.
My client was celebrating their "improved ad performance," but I knew better. The timeline was too convenient. SEO was driving significant organic traffic and conversions, but Facebook's attribution model was claiming credit for these wins.
That's when I realized the fundamental problem: we were trying to track a messy, multi-channel customer journey through the lens of individual platform reporting. Each platform - Facebook, Google, email - was claiming credit for the same conversions.
The typical customer journey actually looked like this: Google search for the problem → Social media browsing → Retargeting ad exposure → Review site research → Email nurture sequence → Multiple touchpoints across channels → Purchase weeks later.
Facebook saw: Ad impression → Purchase (claiming full credit)
Google saw: Search → Purchase (claiming full credit)
Email platform saw: Email open → Purchase (claiming full credit)
We were triple-counting success and making budget decisions based on fiction. The solution wasn't better attribution software - it was accepting that the dark funnel exists and building a simple system to approximate the truth.
Here's my playbook
What I ended up doing and the results.
Instead of fighting the unmeasurable, I embraced it. Here's the framework I developed after years of trying complex attribution tools that promised the world but delivered confusion:
Step 1: The Reality Check Audit
I started with a simple question: If Facebook/Google ads are performing so well, why aren't overall profits increasing proportionally? I pulled three months of data:
Total ad spend across all platforms
Platform-reported ROAS for each channel
Actual revenue and profit margins
Organic traffic and conversion trends
The discrepancy was massive. If the platforms were correct, we should have been printing money. Instead, we were barely breaking even.
Step 2: The Simple UTM System
I implemented a clean UTM structure that actually made sense:
utm_source: facebook, google, email, organic, direct
utm_medium: cpc, social, email, organic, referral
utm_campaign: specific campaign names
utm_content: ad creative or email variant
The key was consistency. Every link, everywhere, got tagged. No exceptions.
Step 3: The Google Sheets Attribution Dashboard
I built a simple dashboard that imported data from Google Analytics and cross-referenced it with actual sales data. The magic happened in the analysis:
Channel overlap analysis - Tracking which customers hit multiple channels
Time-to-conversion patterns - Understanding purchase timelines
Incremental lift testing - Turning channels on/off to measure true impact
Step 4: The Dark Funnel Acceptance Model
Instead of trying to track every interaction, I created buckets:
Measurable influence (30%) - Direct clicks from ads, emails, etc.
Probable influence (40%) - Brand searches after ad exposure, direct traffic spikes
Dark funnel (30%) - Word-of-mouth, offline discussions, unmeasurable interactions
This framework helped set realistic expectations and guided budget allocation decisions.
Step 5: The Incrementality Testing Protocol
The real breakthrough came from testing incrementality:
Pause Facebook ads for 2 weeks → Track impact on total revenue
Reduce Google Ad spend by 50% → Measure organic traffic changes
Test different attribution windows → Find the sweet spot for your business
This revealed the true contribution of each channel, not just the last-click fiction.
Quick Wins
Immediate steps that cut through attribution noise
Long-term Strategy
Building sustainable measurement systems
Data Analysis
Understanding what metrics actually matter
Implementation
Practical tools and tracking setup
The results were eye-opening, not just for attribution accuracy but for overall marketing efficiency. Within 3 months of implementing this system:
Budget Reallocation Impact: We discovered that 40% of Facebook's claimed conversions were actually driven by SEO efforts. This led to reallocating €4K monthly from Facebook to content creation and technical SEO improvements.
Channel Performance Reality: Direct traffic increased 60% after we started tracking brand search patterns. What Facebook called "direct conversions" were actually people who saw ads, searched the brand later, then purchased through organic search.
Customer Journey Insights: The average time from first touchpoint to purchase was 18 days, not the 1-day attribution window Facebook used. This completely changed our retargeting strategy and budget planning.
True ROAS Discovery: After incrementality testing, we found that Facebook's true ROAS was closer to 1.8x, not the reported 8-9x. Google Search had the highest incremental impact, while Facebook excelled at awareness and initial consideration.
The real breakthrough wasn't perfect tracking - it was honest tracking. We stopped making decisions based on platform fiction and started optimizing for actual business outcomes.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
After implementing this attribution framework across multiple ecommerce clients, here are the key insights that consistently emerge:
Platform attribution is marketing, not measurement - Every platform has an incentive to over-report its contribution. Build your own view of the truth.
The dark funnel is your friend, not your enemy - Instead of fighting unmeasurable interactions, factor them into your planning. Assume 30-40% of conversions have invisible influences.
Incrementality beats attribution models - Testing what happens when you turn channels off reveals more truth than complex attribution mathematics.
Time windows matter more than touchpoint counting - Understanding your customer's typical research timeline is more valuable than tracking every click.
Simple systems beat complex ones - A Google Sheets dashboard that you actually use is better than expensive software that sits ignored.
Brand searches are the best attribution signal - Increases in branded search volume often indicate paid channel effectiveness better than last-click data.
Cross-device behavior is the norm, not the exception - Most customers research on mobile and buy on desktop, breaking traditional attribution chains.
The biggest mistake is chasing perfect attribution instead of actionable insights. Focus on directional accuracy and business outcomes, not measurement perfection.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS companies, attribution challenges are different but equally important:
Track trial-to-paid conversion paths, not just initial signups
Monitor product usage data alongside marketing touchpoints
Focus on customer lifetime value attribution, not just acquisition cost
For your Ecommerce store
For ecommerce stores, this approach is essential for profitable growth:
Implement consistent UTM tagging across all marketing channels
Run incrementality tests monthly to validate channel performance
Track brand search volume as a proxy for paid channel effectiveness