Growth & Strategy
Personas
SaaS & Startup
Time to ROI
Medium-term (3-6 months)
You know that sinking feeling when you're looking at your marketing dashboard and the numbers just don't add up? Facebook says it drove 500 conversions, Google Ads claims 300, and your email platform is taking credit for 200 - but you only had 400 total sales that month.
I've been there, staring at reports that made no sense, trying to explain to clients why their attribution was more fiction than fact. The harsh reality? Most businesses are flying blind when it comes to multi-channel campaign tracking, making decisions based on data that's fundamentally flawed.
After working with dozens of SaaS and e-commerce clients, I discovered that the problem isn't just technical - it's philosophical. We're trying to force a messy, non-linear customer journey into neat, tidy attribution models that simply don't reflect reality.
Here's what you'll learn from my experience tracking campaigns across multiple channels:
Why traditional attribution models are lying to you (and costing you money)
The "dark funnel" reality that most marketers ignore
A practical framework for tracking what actually matters
How to make strategic decisions with imperfect data
The one metric that transformed how I measure distribution success
The Reality
What the industry tells you about attribution
Walk into any marketing conference or read any growth blog, and you'll hear the same gospel: "You need proper attribution to optimize your campaigns." The industry has built an entire ecosystem around this belief, selling expensive tools and complex setups that promise to solve the attribution puzzle.
Here's what every marketing expert will tell you to do:
Implement UTM parameters everywhere - Tag every link, track every source
Set up multi-touch attribution models - First-touch, last-touch, linear, time-decay
Use advanced tracking pixels - Facebook Pixel, Google Analytics 4, custom event tracking
Invest in attribution platforms - Tools like Triple Whale, Northbeam, or Hyros
Create detailed customer journey maps - Document every touchpoint and interaction
This conventional wisdom exists because we desperately want marketing to be scientific. We want clean data, clear cause-and-effect relationships, and the ability to say "this campaign generated exactly X revenue." It feeds our need for control and justification of marketing spend.
The problem? Real customer behavior is messy. Someone might see your Facebook ad, Google your company name, read three blog posts, get your newsletter, see a retargeting ad, ask a friend, check review sites, and finally convert through direct traffic two weeks later. Which channel gets the credit?
Most attribution models pick one touchpoint or distribute credit using arbitrary rules. But these models are built on the assumption that we can track most of the customer journey - an assumption that's becoming less true every day with iOS updates, cookie restrictions, and privacy regulations.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
I learned this lesson the hard way while working with an e-commerce client who was spending heavily on Facebook Ads. On paper, they had a solid setup - proper UTM tracking, Facebook Pixel installed correctly, Google Analytics configured for e-commerce. Everything looked professional.
But something was off. The client had been running Facebook Ads for months with what Facebook reported as a healthy 2.5 ROAS. Not amazing, but decent enough to keep the campaigns running. However, when I dug deeper into their overall business metrics, the numbers didn't add up.
Their total revenue had grown significantly over the past few months, but their Facebook ad spend increases didn't correlate with the revenue growth. More puzzling, when they had technical issues that paused their Facebook campaigns for a week, their sales barely dropped.
That's when I started questioning everything. I spent three months building a comprehensive SEO strategy for them, optimizing their website structure, creating targeted content, and improving their organic visibility. The results were dramatic - their organic traffic increased substantially, and more importantly, their total conversions grew.
But here's where it gets interesting: Facebook's reported ROAS jumped from 2.5 to 8-9 during this same period, even though we hadn't changed anything about their ad campaigns.
The reality hit me like a brick wall. Facebook's attribution model was claiming credit for conversions that were actually driven by our SEO efforts. Customers were discovering the brand through organic search, researching products, comparing options, and then - maybe - clicking a retargeting ad before purchasing. Facebook got the credit, but SEO did most of the heavy lifting.
This wasn't just a problem with Facebook. I saw similar issues across multiple clients and channels. Google Ads claimed credit for branded search terms that people would have searched anyway. Email platforms attributed sales to newsletter opens that happened days after the customer had already decided to buy. Every platform was fighting for attribution credit in what I now call "the attribution wars."
Here's my playbook
What I ended up doing and the results.
After discovering how broken traditional attribution really is, I developed a different approach. Instead of trying to track every touchpoint perfectly, I focus on understanding the overall system and making strategic decisions based on incremental impact.
Here's my framework for tracking multi-channel campaigns that actually works:
Step 1: Establish True Baseline Metrics
Before you can measure the impact of any channel, you need to understand your baseline performance. I track total website traffic, total conversions, and total revenue as my north star metrics. These aggregate numbers tell the real story of business growth, regardless of attribution squabbles.
For the e-commerce client I mentioned, their baseline was simple: total monthly revenue and total monthly orders. Everything else was secondary.
Step 2: Implement Channel Pause Testing
The most reliable way to measure channel impact is to turn it off and see what happens. I regularly run controlled experiments where we pause specific channels for 1-2 weeks and measure the impact on overall conversions.
This sounds scary, but it's the only way to get true incremental data. When we paused that client's Facebook campaigns, their sales dropped by only 15%, even though Facebook was claiming credit for 60% of their revenue.
Step 3: Focus on Leading Indicators, Not Attribution
Instead of obsessing over last-click attribution, I track leading indicators that correlate with business growth:
Brand search volume - Are more people searching for your company name?
Direct traffic growth - Are people coming to your site directly?
Organic reach expansion - Are you appearing for more relevant keywords?
Customer lifetime value trends - Are customers from different channels behaving differently long-term?
Step 4: Build Cross-Channel Coverage, Not Perfect Tracking
Rather than trying to track every interaction, I focus on ensuring comprehensive coverage across all potential touchpoints. This means being present where customers are looking, regardless of which platform gets attribution credit.
For my clients, this typically means:
Strong organic presence for product-related keywords
Retargeting campaigns across multiple platforms
Email nurture sequences for different customer segments
Social proof and reviews visible across channels
Step 5: Accept and Plan for the Dark Funnel
The "dark funnel" represents all the customer interactions you can't track - word-of-mouth recommendations, screenshot sharing, offline conversations, private browsing sessions. Instead of ignoring this reality, I plan for it.
I allocate budget specifically for brand building and trust development, knowing that these investments will drive conversions that no attribution model will capture correctly.
Channel Testing
Run controlled pause experiments to measure true incremental impact of each marketing channel
Leading Indicators
Track brand searches and direct traffic instead of relying on platform attribution claims
Dark Funnel Planning
Budget for untrackable influences like word-of-mouth and offline conversations that drive conversions
Coverage Strategy
Focus on omnichannel presence rather than perfect tracking of individual touchpoints
The results of this approach were eye-opening. For the e-commerce client, we discovered that their actual Facebook ROAS was closer to 1.5, not the 8-9 that the platform claimed. However, their SEO efforts were driving significantly more value than any traditional attribution model showed.
More importantly, this understanding allowed us to make better strategic decisions. Instead of increasing Facebook ad spend based on inflated attribution data, we doubled down on SEO and content marketing, which were clearly driving incremental growth.
Within six months, their total organic traffic increased by 300%, and their overall revenue grew by 150%. The best part? They reduced their total advertising costs by 40% while growing faster than ever.
This pattern repeated across multiple clients. When we stopped chasing perfect attribution and started focusing on incremental growth and comprehensive coverage, business results improved dramatically. The key was accepting that marketing attribution will always be imperfect and building strategies that work despite this limitation.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
Here are the most important lessons I learned from years of wrestling with multi-channel tracking:
Attribution models are fiction, but useful fiction. Use them for directional insights, not absolute truth.
Platform-reported metrics favor the platform. Facebook, Google, and others are incentivized to overstate their impact.
Incremental testing beats attribution modeling. Pause tests and holdout groups provide real impact data.
Customer journeys are longer and messier than we think. Plan for multiple touchpoints and extended consideration periods.
Brand building efforts drive "invisible" conversions. Invest in activities that build trust and awareness, even if you can't track direct ROI.
Focus on business outcomes, not channel metrics. Total revenue and customer acquisition matter more than platform-specific KPIs.
The best attribution strategy is comprehensive distribution. Be everywhere your customers are looking, regardless of tracking capabilities.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS startups, focus on tracking trial-to-paid conversion rates by traffic source and implement proper trial attribution while accepting that multi-touch journeys are the norm.
For your Ecommerce store
For e-commerce stores, prioritize total revenue growth over individual channel attribution and use comprehensive coverage strategies across all customer touchpoints.