Growth & Strategy
Personas
SaaS & Startup
Time to ROI
Short-term (< 3 months)
I used to obsess over marketing attribution. Every click, every touchpoint, every microscopic interaction had to be tracked and assigned to the "right" channel. My clients demanded it. "Show me the ROI of each channel," they'd say. "Which Facebook ad brought this customer?"
So I built elaborate attribution models. Multi-touch attribution, first-click, last-click, time-decay models - you name it, I implemented it. The dashboards looked beautiful. The reports were comprehensive. And they were completely useless for making actual business decisions.
Here's what nobody talks about: attribution is fundamentally broken in 2025. Privacy regulations killed third-party cookies. iOS updates destroyed Facebook's tracking. And even when tracking "worked," it was telling us fairy tales about linear customer journeys that don't exist.
After working with dozens of SaaS startups and ecommerce stores, I've learned that the companies winning at growth aren't the ones with perfect attribution - they're the ones who focus on distribution over measurement.
In this playbook, you'll discover:
Why traditional attribution models are misleading your marketing decisions
The dark funnel reality that most attribution systems miss
A practical framework for measuring what actually matters
How to optimize marketing spend without perfect attribution data
Real examples of companies that grew faster by ignoring attribution
Industry Reality
What every marketer has been told about attribution
Walk into any marketing conference or open any growth blog, and you'll hear the same attribution gospel repeated endlessly:
"You can't manage what you can't measure." Every marketer has heard this. The conventional wisdom says you need to track every touchpoint, build sophisticated attribution models, and assign revenue to specific channels with mathematical precision.
The standard recommendations include:
Multi-touch attribution models that credit multiple touchpoints along the customer journey
Marketing mix modeling to understand channel effectiveness at a macro level
First-party data collection to replace third-party cookies and maintain tracking accuracy
UTM parameter hygiene to ensure proper campaign tracking across all channels
Customer journey mapping to identify all potential touchpoints and optimize them
This advice exists because it feels logical and scientific. Marketing has physics envy - we want our discipline to be as measurable as engineering. Attribution models promise to turn marketing into a precise science where you can optimize inputs to achieve predictable outputs.
The problem? This approach fundamentally misunderstands how customers actually discover and buy from businesses. Real customer journeys aren't linear paths with trackable touchpoints. They're messy, multi-device, multi-channel experiences that span weeks or months, often involving offline conversations, dark social sharing, and subconscious brand building that no attribution model can capture.
Most attribution systems are measuring the wrong things while giving marketers false confidence in their optimization decisions.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
My wake-up call came from an ecommerce client who was drowning in attribution complexity. They sold fashion accessories through multiple channels: Facebook ads, Google ads, email marketing, influencer partnerships, and organic social.
The team was obsessed with attribution. They had implemented Google Analytics Enhanced Ecommerce, Facebook's Conversions API, server-side tracking, and even hired a data analyst to build custom attribution models. Their monthly reports looked like PhD dissertations.
But here's what was actually happening: their Facebook ROAS jumped from 2.5 to 8-9 within a month of launching our SEO strategy. Obviously, Facebook didn't magically become 3x more effective. What happened was classic attribution lying - SEO was driving significant traffic and conversions, but Facebook's attribution model was claiming credit for organic wins.
The client's typical customer journey looked nothing like what their attribution showed:
Someone would Google search for their problem
Browse products on the website
Get retargeted with Facebook ads
Research reviews on third-party sites
Return through email marketing
Complete purchase
But the attribution model would show: "Facebook ad drove the conversion." The dark funnel - all those unmeasurable touchpoints - was completely invisible.
I realized we were optimizing for attribution accuracy instead of business growth. The client was making budget allocation decisions based on fictional data while the real growth drivers remained hidden.
Here's my playbook
What I ended up doing and the results.
Instead of fighting the attribution dragon, I developed a framework that embraces the dark funnel reality. Here's exactly how I approach marketing measurement now:
Step 1: Accept Attribution is Directional, Not Precise
I stopped promising clients perfect attribution data. Instead, I position attribution as directional intelligence - useful for spotting trends, not making precise ROI calculations. This mindset shift alone improves decision-making quality.
Step 2: Focus on Incrementality Testing
Rather than relying on attribution models, I run incrementality tests. For Facebook ads, we'll pause campaigns for 2-4 weeks and measure the impact on overall conversions. If conversions drop significantly, we know Facebook is driving incremental value. If they don't, we know the attribution was lying.
Step 3: Track Leading Indicators by Channel
Each channel gets measured on its logical contribution:
SEO: Organic traffic growth, keyword rankings, search visibility
Paid ads: Reach, click-through rates, cost per click trends
Email: List growth, engagement rates, deliverability
Content: Brand search volume, social mentions, traffic quality
Step 4: Implement Portfolio Theory for Marketing
Instead of optimizing individual channels, I optimize the marketing portfolio. Some channels (like brand awareness) drive unmeasurable value that enables other channels (like retargeting) to perform better. You can't optimize them in isolation.
Step 5: Use Blended Metrics for Decision Making
I track overall business metrics - total revenue, customer acquisition cost, lifetime value - and correlate them with marketing activities over time. This gives a more accurate picture than channel-specific attribution.
The key insight: Stop trying to control and measure everything. Start building systems that work even when you can't track their exact contribution.
Key Insight
Attribution is directional intelligence, not precise measurement. Use it to spot trends, not calculate exact ROI.
Incrementality Over Attribution
Run pause tests to measure true incremental value rather than relying on attribution models to tell you what's working.
Portfolio Optimization
Optimize your entire marketing mix, not individual channels. Some channels enable others to perform better.
Leading Indicators
Track channel-specific metrics that indicate health rather than forcing revenue attribution on everything.
The results speak for themselves. Clients who adopted this approach saw immediate improvements in marketing effectiveness:
Faster Decision Making: Without waiting for perfect attribution data, teams made quicker optimizations based on leading indicators and incrementality signals.
Better Budget Allocation: Portfolio thinking led to more balanced marketing mixes. Instead of over-investing in "high-attribution" channels, clients invested in brand building and awareness that improved overall performance.
Reduced Analytics Overhead: Teams spent less time building complex tracking systems and more time on creative strategy and channel optimization.
Improved Channel Performance: Counterintuitively, caring less about precise attribution led to better channel performance. When you optimize for the channel's natural strengths rather than forcing attribution, results improve.
Most importantly, teams became more experimental. Without the pressure of proving immediate attribution, they were willing to test newer channels and longer-term strategies that drive sustainable growth.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
Here are the five most important lessons I learned about marketing attribution:
1. The Dark Funnel is Bigger Than You Think
Most customer touchpoints are unmeasurable. Word-of-mouth, offline conversations, podcast listening, social media browsing - none of this shows up in attribution models, but it drives significant buying behavior.
2. Attribution Accuracy Decreases Over Time
Privacy regulations, ad blockers, and iOS updates make attribution less accurate each year. Building your marketing strategy on attribution data is building on quicksand.
3. Channel Synergy is Real
Channels don't operate in isolation. Brand awareness campaigns make retargeting more effective. SEO content improves paid ad quality scores. Email marketing increases social media engagement. You can't optimize these relationships with single-channel attribution.
4. Leading Indicators Trump Lagging Indicators
Revenue attribution is a lagging indicator. Leading indicators (traffic quality, engagement rates, brand search volume) give you faster feedback loops for optimization.
5. Incrementality Testing Reveals Truth
The only way to know if a channel truly drives incremental value is to turn it off and measure the impact. This is uncomfortable but necessary for honest marketing measurement.
What I'd Do Differently: I'd implement incrementality testing from day one instead of spending months building attribution models first.
When This Approach Works Best: This framework works for any business with multiple marketing channels and complex customer journeys. It's especially valuable for B2B SaaS and ecommerce businesses where customers research extensively before buying.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS startups, focus on these key points:
Track trial-to-paid conversion by channel, not just signups
Measure engagement quality, not just attribution volume
Test incrementality quarterly to validate channel performance
Optimize for portfolio growth, not individual channel ROAS
For your Ecommerce store
For ecommerce stores, implement these strategies:
Focus on customer lifetime value across the entire marketing mix
Track brand search volume as a leading indicator of attribution health
Use incrementality tests during seasonal lows to avoid disrupting peak periods
Measure repeat purchase rates by acquisition channel