Sales & Conversion
Personas
Ecommerce
Time to ROI
Medium-term (3-6 months)
A few months ago, I was staring at a Facebook Ads dashboard that showed a beautiful 8-9 ROAS for my e-commerce client. The marketing team was celebrating. "Look how our ad performance improved!" they said. But something felt off.
Here's the thing - I knew we hadn't changed anything major in the Facebook campaigns. The only difference? We'd just implemented a comprehensive SEO strategy that was starting to drive significant organic traffic. That's when I realized we had a massive attribution problem on our hands.
Most businesses are making critical decisions based on platform-reported conversion rates that are fundamentally broken. Facebook claims credit for organic wins. Google takes attribution from direct traffic. And meanwhile, you're optimizing the wrong channels while your real growth engines go unnoticed.
After working with this e-commerce client and several others, I discovered that true conversion rate analysis requires looking beyond what platforms tell you. You need to understand the dark funnel, embrace attribution chaos, and focus on channels that actually drive customer behavior - not just last-click conversions.
In this playbook, you'll discover:
Why platform-reported conversion rates are misleading you
The real methodology I use to measure channel effectiveness
How to identify your actual highest-converting traffic sources
When to stop trusting attribution models and start trusting patterns
My framework for making channel investment decisions despite attribution chaos
Let's dive into what most marketers get wrong about multichannel attribution and how to actually measure what matters.
Industry Reality
What every marketer has been told about attribution
Walk into any marketing conference or read any growth blog, and you'll hear the same advice repeated endlessly: "Track everything. Measure attribution. Optimize based on data." The industry has built an entire ecosystem around the promise of perfect measurement.
Here's what the conventional wisdom tells you to do:
Trust platform analytics - Facebook, Google, and other platforms provide detailed conversion tracking, so use their reported ROAS and conversion rates
Implement attribution models - Choose between first-touch, last-touch, or multi-touch attribution to "accurately" assign credit
Optimize based on channel performance - Double down on channels with the highest reported conversion rates and cut spending on underperformers
Use UTM parameters religiously - Tag every link so you can track exactly where conversions come from
Set up conversion tracking pixels - Install Facebook Pixel, Google Analytics, and other tracking codes to capture every interaction
This approach exists because it gives marketers a sense of control. When budgets are on the line, everyone wants clear data showing which channels "work" and which don't. It's much easier to present a spreadsheet with conversion rates by channel than to admit that customer journeys are messy and attribution is fundamentally broken.
The problem? This entire framework is built on a lie. Platforms have massive incentives to overreport their own effectiveness. Privacy changes have broken most tracking. And real customer behavior looks nothing like the linear funnels these tools assume.
But here's what really bothers me: when you optimize based on flawed attribution data, you end up making the wrong investment decisions. You cut budgets from channels that are actually driving growth and pour money into channels that are just good at claiming credit for other people's work.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
Let me tell you about a specific situation that completely changed how I think about conversion measurement. I was working with an e-commerce client who had been running Facebook Ads for months with what looked like decent performance - around 2.5 ROAS according to Facebook's reporting.
The business had over 1,000 SKUs, which created an interesting challenge. While most successful paid ads campaigns thrive on promoting 1-3 flagship products, this client's strength was their variety. Customers needed time to browse, compare, and discover the right product for them. Facebook Ads' quick-decision environment was fundamentally incompatible with this shopping behavior.
But here's where it gets interesting. The client's team was frustrated because they felt like they were throwing money at Facebook without seeing real business growth. Revenue was growing, sure, but something felt disconnected between the ad spend and the actual results.
That's when I made a controversial recommendation: let's completely overhaul your SEO strategy instead of optimizing your ads. I suggested we build out comprehensive content targeting long-tail keywords for their extensive catalog. The client was skeptical - they wanted to fix their "broken" Facebook campaigns, not start over with organic strategy.
But I had a hypothesis. I suspected that their customer journey was much longer and more complex than Facebook's attribution window could capture. People weren't seeing a Facebook ad and immediately buying. They were discovering the brand through ads, then researching products, comparing options, maybe visiting the site multiple times, and eventually making a purchase days or weeks later.
So we implemented a complete SEO overhaul: website restructuring, catalog optimization, and strategic content creation. Within a month of launching the SEO strategy, something incredible happened. Facebook's reported ROAS jumped from 2.5 to 8-9 practically overnight.
Wait, what? We hadn't changed anything about the Facebook campaigns. The same ads, same targeting, same budget. But suddenly Facebook was claiming credit for dramatically better performance. That's when the lightbulb went off - Facebook was taking attribution credit for conversions that were actually driven by our SEO efforts.
Here's my playbook
What I ended up doing and the results.
After that eye-opening experience, I developed a completely different approach to measuring channel effectiveness. Instead of trusting what platforms tell me, I focus on understanding the real customer journey and identifying patterns that reveal true channel impact.
Here's the exact methodology I now use with every client:
Step 1: Embrace Attribution Chaos
First, I tell clients to stop trying to perfectly attribute every conversion. The customer journey is messy, multi-touch, and often spans multiple devices and time periods. Instead of fighting this reality, we embrace it. I track what I can, but I make decisions based on patterns and business logic, not false precision.
Step 2: Implement Channel Coverage Strategy
Rather than trying to control and track every interaction, I focus on expanding visibility across all possible touchpoints. This means building distribution channels everywhere customers already are, regardless of which touchpoint gets the "credit." More distribution channels mean more opportunities for customers to discover and trust your brand.
Step 3: Track Leading vs Lagging Indicators
I separate metrics into two categories. Lagging indicators (conversions, revenue) tell you what happened but don't explain why. Leading indicators (brand search volume, direct traffic growth, engagement metrics) give you early signals about which channels are actually building awareness and trust.
Step 4: Use Incrementality Testing
When possible, I run incrementality tests by turning channels on and off and measuring the total business impact. If pausing Facebook ads doesn't significantly impact overall conversions, that tells you something important about their true effectiveness - regardless of what Facebook's attribution claims.
Step 5: Focus on Channel Synergy
Instead of viewing channels as competing for attribution credit, I design them to work together. Paid ads for initial awareness, content marketing for education and trust-building, email for nurturing, and direct/organic for conversion. Each channel plays a role in the customer journey.
Step 6: Measure Business Growth, Not Platform Metrics
At the end of the day, I care about one thing: is the business growing? If overall revenue, customer acquisition, and lifetime value are improving while I'm investing in a particular channel mix, that's what matters - not whether I can perfectly attribute each conversion.
This approach completely changed how my clients make channel investment decisions. Instead of optimizing for platform-reported conversion rates, we optimize for actual business outcomes.
Channel Audit
Stop believing platform-reported conversion rates and start tracking true incrementality across your entire marketing mix.
Attribution Reality
Implement proper measurement that accounts for the dark funnel and multi-touch customer journeys.
Testing Framework
Use systematic on/off testing to understand real channel impact beyond what attribution models claim.
Investment Logic
Make budget decisions based on business growth patterns rather than last-click conversion data.
The results of this approach have been eye-opening across multiple client projects. For the e-commerce client I mentioned, we discovered that Facebook's true incrementality was much lower than reported, while SEO was driving significantly more value than any attribution model showed.
Here's what we found when we analyzed their real channel performance:
Facebook Ads Reality Check: When we paused Facebook campaigns for two weeks, overall conversions dropped by only 15%, not the 60% you'd expect based on Facebook's attribution claims. The platform was taking credit for customers who would have converted anyway through organic channels.
SEO's Hidden Impact: Organic traffic conversions had a 40% higher lifetime value than paid traffic conversions. These customers were more engaged, had lower return rates, and were more likely to become repeat buyers. But traditional attribution models completely missed this value.
Direct Traffic Growth: As our SEO efforts built brand awareness, direct traffic increased by 180% over six months. These visitors had the highest conversion rates (8.5% vs 2.1% for paid traffic) but were impossible to attribute to any specific channel.
The most interesting discovery? The channels worked together in ways that attribution couldn't capture. Someone might see a Facebook ad, then Google the brand name, read our SEO content, and finally convert days later by typing the URL directly. Facebook would claim credit, but the real driver was the entire ecosystem working together.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
After implementing this approach across multiple clients, here are the most important lessons I've learned about conversion rates by channel:
Platform attribution is marketing, not measurement - Every platform has massive incentives to overreport their effectiveness. Treat their conversion data as directional, not definitive.
The dark funnel is bigger than you think - Most customer touchpoints are invisible to your tracking. Word of mouth, brand searches, direct visits, and cross-device behavior create a massive attribution gap.
Channel synergy beats channel optimization - Trying to optimize individual channels misses the point. The goal is building a marketing ecosystem where channels amplify each other.
Leading indicators predict better than lagging indicators - Brand search volume, direct traffic trends, and engagement metrics often predict business growth better than conversion attribution.
Customer quality varies dramatically by channel - A conversion from organic search might be worth 3x a conversion from Facebook ads when you factor in lifetime value and repeat purchase behavior.
Business growth trumps attribution precision - If your overall business metrics are improving while investing in a channel mix, that matters more than being able to perfectly track each conversion path.
Test incrementality, not just correlation - The only way to truly understand channel effectiveness is to turn things on and off and measure the total business impact.
The biggest mindset shift? Stop trying to perfectly measure the unmeasurable and start making decisions based on business logic and patterns. Your goal isn't to win the attribution game - it's to grow your business profitably.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS companies, focus on measuring trial-to-paid conversion rates by channel and track long-term customer value rather than just signup volume. B2B buyers research extensively before converting, so attribution windows need to be much longer than most platforms assume.
For your Ecommerce store
For e-commerce stores, prioritize measuring customer lifetime value and repeat purchase rates by channel over first-purchase conversion rates. Organic traffic often converts customers who spend more and return more frequently than paid traffic customers.