Growth & Strategy
Personas
SaaS & Startup
Time to ROI
Medium-term (3-6 months)
So here's what happened. I was managing marketing for multiple clients - SaaS startups, e-commerce stores, agencies - and every single one of them was obsessing over the same metrics. PPC click-through rates, cost per acquisition, ROAS from Google Ads. Meanwhile, their organic traffic was stagnating, content strategy was non-existent, and they were burning through budgets faster than a startup burns through seed funding.
The breaking point came when one of my e-commerce clients with a 2.5 ROAS on Facebook Ads asked me why their "amazing" paid performance wasn't translating to sustainable growth. That's when I realized we were all playing the wrong game.
The problem isn't that PPC metrics are useless - they're not. The problem is that most businesses are comparing apples to oranges when they pit SEO against PPC, then making strategic decisions based on incomplete data. It's like judging a marathon runner against a sprinter and wondering why your long-term growth strategy isn't working.
Here's what you'll learn from my experience comparing these two channels across dozens of client projects:
Why traditional PPC vs SEO comparison tools give you misleading insights
The hidden attribution problem that makes Facebook claim credit for organic wins
A practical framework for measuring what actually drives long-term growth
Real metrics from client projects that show the dark funnel reality
How to build a measurement system that guides better strategic decisions
This isn't another "SEO vs PPC" think piece. This is about understanding which metrics actually matter for your business and building a measurement framework that prevents expensive mistakes. Let's dive into what the industry gets wrong about channel comparison.
Industry Reality
What every marketer thinks they know about measuring channels
Walk into any marketing team meeting and you'll hear the same conversation. "Our Google Ads are performing at 3.2 ROAS, but SEO is hard to measure." "Facebook shows 4x return, so let's double down on paid social." "Our PPC is profitable, but organic traffic isn't converting."
The industry has built an entire ecosystem around this false choice. Marketing dashboards separate paid and organic performance into neat little boxes. Attribution tools promise to "solve" the measurement problem by assigning credit to first-touch, last-touch, or some mathematical model that supposedly represents reality.
Here's what every marketing course and agency pitch will tell you:
PPC gives you immediate, measurable results - You can track every click, conversion, and dollar spent with surgical precision
SEO takes 6-12 months but provides "free" traffic - Organic rankings compound over time without ongoing ad spend
Use attribution tools to compare channel performance - Google Analytics, Facebook Attribution, or enterprise solutions will show you which channel drives more value
Allocate budget based on cost per acquisition - Put money where CPA is lowest and ROAS is highest
Test budget shifts between channels - Pause underperforming channels and scale winners
This conventional wisdom exists because it's simple, measurable, and makes marketing feel scientific. Executives love dashboards with clear numbers. Agencies can show immediate value. Performance marketers can optimize toward specific metrics.
But here's where this approach falls apart in practice: customer journeys aren't linear, attribution is fundamentally broken in the privacy-first world, and optimizing for short-term metrics often destroys long-term growth. Most businesses using this framework are making strategic decisions based on incomplete data - and it's costing them millions in opportunity cost.
The real question isn't "which channel performs better" - it's "how do these channels work together to drive sustainable growth, and how do we measure that correctly?"
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
Let me tell you about the moment I realized everything I thought I knew about channel comparison was wrong. I was working with an e-commerce client who was religiously tracking their Facebook Ads performance. The dashboard showed a solid 2.5 ROAS, and everyone was reasonably happy with the numbers. Not amazing, but profitable enough to keep the ads running.
Then we implemented a complete SEO overhaul - website restructuring, content optimization, technical improvements. Within a month of the SEO work going live, something interesting happened. Facebook's reported ROAS jumped from 2.5 to 8-9. The marketing team started celebrating their "improved ad performance."
But I knew better. The reality? SEO was driving significant traffic and conversions, but Facebook's attribution model was claiming credit for organic wins. This wasn't a Facebook Ads success story - this was a perfect example of how attribution lies while distribution doesn't.
This experience taught me that the customer journey looks nothing like what our tracking tools report. A typical journey actually unfolds like this:
Customer googles their problem (organic search)
Browses through social media feeds (dark social)
Sees a retargeting ad (gets the "credit")
Researches reviews and competitors (direct traffic)
Receives email nurture sequence (email gets partial credit)
Finally converts through multiple touchpoints
The problem with traditional comparison tools is that they're trying to assign linear cause-and-effect to a messy, multi-touchpoint reality. Facebook says the ad drove the conversion. Google Analytics might credit organic search. Your email platform claims the nurture sequence closed the deal. Everyone's claiming victory, but nobody has the full picture.
This wasn't isolated to one client. I started seeing the same pattern everywhere. Businesses would pause their "underperforming" organic efforts to double down on "high-performing" paid channels, only to watch their overall growth plateau or decline. They were optimizing for attribution artifacts instead of actual business growth.
Here's my playbook
What I ended up doing and the results.
After seeing attribution chaos destroy strategic decisions across dozens of client projects, I developed a different approach. Instead of trying to perfectly track channel performance, I focus on measuring what actually matters for sustainable business growth. Here's the framework I use:
Step 1: Embrace the Dark Funnel Reality
First, I stopped believing in clean attribution. Instead, I implemented what I call "coverage measurement." Rather than trying to track every interaction, I measure how many touchpoints we're covering across the customer journey. The goal isn't to control every interaction - it's to ensure visibility across all possible discovery points.
For my SaaS clients, this means tracking:
Search visibility for problem-aware keywords (SEO coverage)
Retargeting reach across platforms (paid coverage)
Content distribution across channels (content coverage)
Email list growth and engagement (owned media coverage)
Step 2: Implement Constraint-Based Measurement
Instead of asking "which channel drives more conversions," I ask "what constraints is each channel operating under?" This completely changes how you evaluate performance.
PPC operates under budget constraints. SEO operates under content and technical constraints. Understanding these constraints helps you make better allocation decisions. If your PPC is constrained by budget and your SEO is constrained by content production, the solution isn't to shift budget from SEO to PPC - it's to remove the content constraint.
Step 3: Track Business-Level Metrics
I measure three core business metrics that matter more than channel-specific performance:
Total Qualified Pipeline Growth - How much high-quality demand are we generating across all channels?
Customer Acquisition Cost Trend - Is our blended CAC improving or deteriorating over time?
Channel Vulnerability Index - How dependent are we on any single traffic source?
Step 4: Use Incrementality Testing
When clients want to understand true channel impact, I run incrementality tests instead of relying on attribution. This means deliberately pausing channels or dramatically shifting spend to see the actual impact on business metrics. It's messier than looking at a dashboard, but it reveals real causation instead of correlation.
For one e-commerce client, we paused Facebook Ads for 30 days while maintaining SEO efforts. Despite Facebook claiming 60% of conversions, overall revenue only dropped 20%. This showed us that Facebook was getting credit for conversions that would have happened anyway through organic channels.
Step 5: Build a Strategic Dashboard
Instead of separate SEO and PPC dashboards, I create one strategic view that shows:
Total search demand capture (paid + organic)
Cost per qualified lead across all channels
Customer lifetime value by acquisition source
Channel saturation indicators
This framework doesn't eliminate the complexity of multi-touch customer journeys - it acknowledges that complexity and builds measurement around it. The goal isn't perfect attribution; it's making strategic decisions based on what actually drives long-term business growth.
Coverage Thinking
Instead of tracking perfect attribution, measure how many customer touchpoints you're covering across their entire journey
Incrementality Tests
Run deliberate experiments by pausing channels to see real impact on business metrics rather than trusting attribution data
Strategic Metrics
Focus on blended CAC, qualified pipeline growth, and channel vulnerability rather than channel-specific performance metrics
Dark Funnel Reality
Accept that most customer interactions happen in unmeasurable spaces and optimize for coverage rather than tracking
The results of this framework shift have been dramatic across client projects. Instead of playing attribution whack-a-mole, teams now make strategic decisions based on actual business impact.
For my e-commerce client who was obsessing over Facebook ROAS, implementing this framework revealed that their organic traffic was actually driving 40% more qualified conversions than Facebook attributed to itself. They shifted resources from ad optimization to content production and saw a 60% increase in total qualified traffic within three months.
A B2B SaaS client using this approach discovered that their "underperforming" SEO was actually supporting their PPC campaigns. When they improved their organic rankings for target keywords, their Google Ads quality scores improved and CPCs decreased by 30%. The channels weren't competing - they were complementing each other.
Most importantly, teams using this framework stop making knee-jerk decisions based on last week's attribution data. They understand that sustainable growth comes from building comprehensive market coverage, not optimizing for whatever channel happened to get the last-click credit.
The framework also prevents the boom-and-bust cycle that destroys many performance marketing efforts. When you understand your channel constraints and vulnerability, you make steadier decisions that compound over time.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
After implementing this framework across dozens of projects, here are the key lessons that fundamentally changed how I approach channel comparison:
Attribution tools create more confusion than clarity - They give you the illusion of precision while hiding the messy reality of customer behavior
Channel synergy matters more than channel performance - SEO and PPC working together often outperform either channel independently
Customer acquisition cost should be measured as a blend - Optimizing individual channel CAC often increases overall CAC
Coverage beats conversion - Being visible across multiple touchpoints drives more sustainable growth than optimizing single touchpoints
Constraint identification trumps performance optimization - Removing bottlenecks creates more growth than improving what's already working
Incrementality testing reveals truth - Actually pausing channels shows real impact better than any attribution model
Strategic metrics prevent tactical mistakes - Measuring business-level outcomes keeps teams focused on what actually matters
The biggest mistake I see teams make is optimizing for what's measurable instead of what's valuable. This framework helps you measure what's actually valuable for long-term business growth, even when it's messier than traditional channel reporting.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS startups implementing this framework:
Track qualified pipeline growth across all channels rather than individual channel conversion rates
Measure customer acquisition cost as a blended metric, not per-channel
Focus on reducing dependency on any single traffic source
Use incrementality tests to validate channel impact before major budget shifts
For your Ecommerce store
For e-commerce stores applying this approach:
Build comprehensive search demand capture combining paid and organic efforts
Track customer lifetime value by acquisition source rather than just first-purchase metrics
Measure channel saturation indicators to prevent over-reliance on paid advertising
Focus on total qualified traffic growth rather than channel-specific performance