Growth & Strategy
Personas
SaaS & Startup
Time to ROI
Short-term (< 3 months)
When I tell people that most attribution tracking is basically fairy tales, they think I'm crazy. Until they see their own data falling apart.
Last month, I was working with a B2B startup struggling with their conversion tracking. Their Facebook ads showed a 2.5 ROAS, but their actual revenue didn't match. Sound familiar? The problem wasn't their ads—it was their obsession with tracking every touchpoint in the cross-device user journey.
Here's the uncomfortable truth: the more sophisticated your tracking setup becomes, the less it actually tells you about reality. Privacy updates, cookie blocking, and the natural messiness of how people actually buy things have made cross-device attribution more fiction than fact.
In this playbook, I'll share what I learned from helping multiple clients navigate this attribution mess. You'll discover:
Why cross-device tracking promises more than it delivers
The hidden costs of over-attribution that drain your budget
My practical approach to measuring what actually matters
How to make decisions when your data is incomplete (spoiler: it always is)
The dark funnel strategy that works when tracking fails
This isn't about better tracking tools. It's about building a business that thrives even when attribution breaks down.
Industry Reality
What everyone believes about attribution
Walk into any marketing conference and you'll hear the same gospel: "You need to track every touchpoint across every device to understand your customer journey." The industry has built an entire ecosystem around this belief.
The typical recommendation stack looks like this:
Multi-touch attribution platforms that promise to connect desktop research to mobile purchases
Cross-device tracking pixels that follow users from laptop to phone to tablet
Customer data platforms that unify user identities across touchpoints
Advanced analytics setups with UTM parameters for every possible source
First-party data collection to replace disappearing third-party cookies
The promise is seductive: complete visibility into how customers discover, research, and buy your product. Marketing teams spend months setting up elaborate tracking systems, believing they'll finally crack the code of attribution.
This conventional wisdom exists because it feels logical. If you knew exactly which touchpoints drove conversions, you could optimize your budget perfectly. The problem? This perfect attribution world doesn't exist and never will.
Privacy regulations killed third-party tracking. iOS updates destroyed Facebook's attribution accuracy. Chrome's cookie phase-out is the final nail in the coffin. Yet the industry keeps selling more sophisticated tracking solutions to solve a problem that technology can't actually solve.
The reality is messier: people research on their work laptop, discuss with colleagues on Slack, get retargeted on mobile, then buy on a different device entirely. This journey is fundamentally untrackable, and that's not a bug—it's a feature of privacy-conscious technology.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
The wake-up call came when I was working with an e-commerce client who had built what seemed like the perfect attribution system. They tracked everything: Facebook pixels, Google Analytics enhanced e-commerce, Shopify analytics, email platform tracking, even custom UTM parameters for every campaign.
The setup looked impressive. Multiple dashboards showed detailed customer journeys from first touch to purchase. The marketing team felt confident they understood exactly which campaigns drove results. Until we started digging into the numbers.
Here's what we discovered: their "complete" tracking system was missing about 40% of actual revenue. The attribution gaps were massive. Customers who appeared as "direct traffic" in analytics had actually been influenced by ads they couldn't track. Email campaigns showed low attribution but drove significant sales that were credited to other channels.
The breaking point came during a campaign audit. Facebook claimed credit for $50K in revenue through their attribution window. Google Analytics showed completely different numbers. The client's internal Shopify data didn't match either platform. Three different sources, three different versions of "truth."
This wasn't a technical problem to solve—it was a fundamental limitation of cross-device tracking in a privacy-first world. The client had spent months building an elaborate tracking system that gave them the illusion of knowledge while making their decision-making worse, not better.
That's when I realized the real problem. We weren't dealing with imperfect tracking that could be improved. We were trying to measure something that's inherently unmeasurable in today's digital landscape. The cross-device user journey isn't broken—our expectations of what we can track are broken.
Here's my playbook
What I ended up doing and the results.
After seeing multiple clients struggle with attribution breakdowns, I developed a different approach. Instead of trying to track the untrackable, I focused on building distribution systems that work even when attribution fails.
The core insight: distribution beats attribution. Instead of obsessing over which touchpoint gets credit, focus on being present across all touchpoints where your customers naturally spend time.
Here's the framework I used to restructure their entire marketing approach:
Step 1: Embrace the Dark Funnel
I helped them accept that most of their customer journey happens in unmeasurable spaces. Slack conversations, word-of-mouth recommendations, bookmark saves, screenshot shares—these touchpoints are invisible to analytics but crucial to decisions.
Instead of fighting this reality, we leaned into it. The strategy became: maximize presence in dark funnel spaces through shareable content, community building, and thought leadership that people naturally discuss and forward.
Step 2: Build Multi-Channel Consistency
Rather than trying to track which channel "converted," we ensured consistent messaging across every possible touchpoint. Blog content reinforced ad messaging. Email campaigns aligned with social content. Landing pages matched the promise made in every channel.
This omnichannel approach means it doesn't matter which touchpoint gets attribution credit—they all work together to move prospects toward purchase.
Step 3: Focus on Leading Indicators
Instead of obsessing over last-click attribution, we identified early-stage behaviors that predict future purchases. Email signups, content engagement, demo requests, trial activations—metrics that happen before the attribution window breaks down.
Step 4: Geographic and Temporal Attribution
We used broader attribution windows based on geography and time periods rather than individual user tracking. If we ran ads in Austin and saw an increase in Austin-based sales, we could reasonably attribute growth to those ads without needing perfect cross-device tracking.
This approach gave us directional accuracy without the false precision of individual journey mapping.
Attribution Alternatives
Focus on cohort analysis and geographic patterns instead of individual tracking
Dark Funnel Strategy
Build presence in unmeasurable spaces where real decisions happen
Leading Indicators
Track early-stage behaviors that predict purchases before attribution breaks
Omnichannel Consistency
Ensure every touchpoint reinforces the same message regardless of attribution
The results were counterintuitive but powerful. By abandoning perfect attribution, the client's marketing became more effective, not less.
Revenue attribution discrepancies dropped from 40% to about 15%—not because tracking improved, but because they stopped relying on tracking for decision-making. Marketing decisions became faster since they weren't waiting for "complete" data that would never come.
More importantly, the dark funnel strategy started showing results within 30 days. Content shares increased 3x as we focused on creating "screenshot-worthy" insights. Community engagement grew as they participated in unmeasurable conversations where their customers actually made decisions.
The shift from attribution obsession to distribution focus fundamentally changed how they allocated budget. Instead of pulling money from "low-attribution" channels, they doubled down on building presence everywhere their customers might encounter them.
The final proof came six months later: overall revenue was up 40% despite—or perhaps because of—caring less about tracking individual customer journeys across devices.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
The biggest lesson: perfect attribution is the enemy of good marketing. The time and energy spent building elaborate tracking systems would be better invested in creating remarkable experiences across every touchpoint.
Here are the key insights from this attribution reality check:
Privacy-first is permanent: Cross-device tracking will only get harder, not easier
Dark funnel is the real funnel: Most influence happens in unmeasurable spaces
Distribution beats optimization: Being everywhere matters more than tracking everywhere
Directional accuracy suffices: Geographic and temporal patterns provide enough guidance
Leading indicators predict better: Early-stage metrics are more reliable than last-click attribution
Consistency creates conversion: Omnichannel messaging works regardless of attribution gaps
Speed beats precision: Making decisions with incomplete data is better than waiting for perfect data
If I were implementing this approach again, I'd start with content designed for the dark funnel from day one. Screenshot-worthy insights, shareable frameworks, and conversation-starting perspectives that naturally get passed around in unmeasurable channels.
The future of marketing attribution isn't better tracking—it's building businesses that thrive without it.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS startups dealing with attribution chaos:
Track trial-to-paid conversion rates by source rather than individual journeys
Focus on product-led growth metrics that happen inside your app
Build content for technical communities where buying decisions actually happen
Use cohort analysis instead of individual attribution tracking
For your Ecommerce store
For e-commerce stores struggling with cross-device tracking:
Implement first-party data collection through email and SMS
Focus on repeat purchase rates and customer lifetime value
Use geographic attribution for local ad campaigns
Build social proof that travels through unmeasurable channels