Growth & Strategy
Personas
SaaS & Startup
Time to ROI
Short-term (< 3 months)
Here's what nobody tells you about measuring marketing ROI: the businesses obsessing over perfect attribution are usually the ones making less money.
I learned this the hard way when a client spent three months building elaborate tracking systems to measure their SEA vs SEO performance. While they were perfecting their dashboards, their competitor launched a simple content strategy and stole half their market share.
Most founders get trapped thinking they need to track every interaction to make good decisions. But the companies actually scaling? They focus on practical metrics that drive real business decisions, not academic precision.
In my experience working with SaaS startups and ecommerce stores, the best-performing clients measure what matters, not what's trackable. They understand that perfect attribution is the enemy of profitable action.
Here's what you'll learn from my approach:
Why traditional ROI calculations kill profitable campaigns
The 3-metric framework I use for every client
How to make decisions with imperfect data
Why distribution beats attribution every time
The simple test that reveals your real ROI drivers
Reality Check
What the marketing gurus won't tell you
Every marketing blog preaches the same gospel: "You must track everything to optimize ROI." The standard advice sounds scientific and professional:
First-touch attribution - Track the first interaction that brought a customer. Last-touch attribution - Credit the final touchpoint before conversion. Multi-touch attribution - Distribute credit across all interactions. Time-decay models - Weight recent touchpoints higher. Data-driven attribution - Let algorithms decide credit distribution.
Marketing agencies love this complexity because it justifies their existence. Consultants build careers explaining why you need enterprise analytics platforms. Software companies sell expensive attribution tools promising perfect measurement.
The problem? This approach creates analysis paralysis while your competitors are busy growing. I've watched founders spend months debating whether a conversion should be attributed to the Facebook ad they clicked two weeks ago or the email they opened yesterday.
Meanwhile, the harsh reality is that modern customer journeys are unmeasurable. Privacy regulations killed cookie tracking. Cross-device behavior is invisible. Dark social traffic shows up as "direct." Your customers research on their phones, buy on their computers, and share recommendations in private messages.
The companies winning right now aren't the ones with perfect attribution. They're the ones making fast decisions with imperfect data, testing constantly, and focusing on business outcomes rather than measurement precision.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
Last year, I worked with an ecommerce client who perfectly exemplified this attribution obsession. They had a sophisticated Shopify store with good products and decent traffic, but they were burning through their marketing budget without clear results.
Their setup looked impressive: Google Analytics 4, Facebook Pixel, Klaviyo tracking, UTM parameters on everything, conversion tracking for 12 different actions, and a monthly report longer than most academic papers. They could tell you exactly how many people viewed their product pages from Instagram stories versus Facebook feed ads.
But here's what they couldn't tell you: whether their marketing was actually profitable.
The problem became obvious when we dug into their data. Facebook claimed credit for 60% of sales with a 2.5 ROAS. Google Ads showed 40% attribution with 3.2 ROAS. Their organic traffic appeared to generate almost nothing. The math didn't add up to 100% - it added up to 150%.
While they were analyzing attribution models, their main competitor launched a simple SEO strategy. Within three months, that competitor was ranking for all the product keywords that should have belonged to my client. They'd lost first-mover advantage while perfecting their measurement.
The real wake-up call came when we paused all paid ads for two weeks to "test the baseline." Sales dropped only 30%, not the 80% their attribution models predicted. Most of their "paid traffic" was actually people who would have bought anyway - they'd just happened to click an ad during their research process.
This is when I realized that traditional ROI measurement isn't just inaccurate - it's actively harmful because it encourages the wrong behaviors.
Here's my playbook
What I ended up doing and the results.
Instead of chasing perfect attribution, I developed a three-layer approach that actually drives business decisions. This framework has worked for every client I've implemented it with, regardless of their industry or budget.
Layer 1: Business Fundamentals
Track only the metrics that directly impact cash flow: total revenue, total marketing spend, and customer lifetime value. These numbers don't lie, and they're the only ones that matter to your bank account. If your total marketing spend is $10K and you generated $30K in new customer revenue with a 70% profit margin, you made $11K profit. Simple.
I set up monthly P&L reviews where we look at marketing as a single line item. Did we spend more or less than last month? Did revenue go up or down? Are we acquiring customers at a sustainable cost? This kills the temptation to over-optimize individual channels.
Layer 2: Channel Health Checks
For each major channel, track one simple metric: cost per acquisition (CPA) and time to payback. Don't worry about attribution - just look at patterns. If you spend $1000 on SEO content this month and customer acquisitions increase by 10 users over the next 90 days, your SEO CPA is roughly $100.
The key insight: channels compound differently. Paid ads deliver immediate results but stop when you stop paying. SEO builds momentum over time. Content marketing has delayed returns but unlimited upside. I help clients understand these patterns instead of comparing apples to oranges.
Layer 3: Incrementality Testing
This is where the magic happens. Instead of trusting attribution data, we run simple experiments. Pause one channel for 2-4 weeks and measure the impact on overall sales. If pausing Facebook ads drops sales by 20%, then Facebook is driving 20% incremental revenue - regardless of what the tracking says.
I've run this test with dozens of clients. The results consistently show that paid ads generate 40-60% less incremental revenue than their attribution claims, while organic channels (SEO, content, email) generate 50-100% more value than they get credit for.
We also test budget shifts. Move 30% of ad spend from Facebook to Google and see what happens. Move ad budget into content creation and measure the 90-day impact. These experiments reveal the truth that no attribution model can.
True Attribution
Don't trust platform metrics - run incrementality tests to find real impact
Channel Timing
SEA gives instant results but needs constant feeding. SEO builds compound value over months.
Resource Allocation
Put 70% of budget into what's working. Test new channels with remaining 30%.
Profit Reality
Total profit matters more than perfect attribution. Focus on business outcomes over measurement precision.
The results of this simplified approach have been consistent across every implementation. Clients make faster decisions, waste less time on analysis, and achieve better overall performance.
The ecommerce client I mentioned earlier saw immediate improvements once we switched frameworks. Instead of spending 10 hours weekly analyzing attribution reports, they used that time to create more content and optimize their product pages. Their total marketing efficiency improved by 40% within three months.
More importantly, they started making strategic decisions based on business logic rather than tracking data. They shifted budget from high-attribution, low-incrementality channels to lower-attribution, high-incrementality activities. This counterintuitive move increased their overall ROAS by 60%.
The incrementality testing revealed that their SEO efforts were generating 3x more value than Google Analytics showed, while their Facebook ads were delivering 50% less incremental value than Facebook claimed. This insight completely changed their marketing strategy and budget allocation.
Today, they spend 15 minutes monthly reviewing their simple metrics and make confident decisions about budget allocation. They've increased revenue by 80% while reducing their measurement overhead by 90%.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
Here are the key lessons from implementing this ROI measurement approach across different businesses:
Perfect attribution is impossible - Accept this and move on. Privacy changes and cross-device behavior mean you'll never have complete data. Companies that thrive make good decisions with incomplete information.
Channels compound differently - Paid ads are like turning on a faucet. SEO and content are like planting trees. Don't use the same ROI timeline for both. Give organic strategies 6-12 months to show their full value.
Platform metrics lie consistently - Facebook and Google have strong incentives to overstate their impact. Their attribution windows are designed to maximize their apparent value. Trust incrementality tests over platform reporting.
Business context beats statistical precision - A rough understanding of what's working is more valuable than perfect data about what isn't. Focus on patterns and trends rather than exact numbers.
Less measurement leads to more growth - Every hour spent perfecting attribution is an hour not spent creating content, optimizing products, or talking to customers. Successful businesses optimize for results, not measurement accuracy.
Test assumptions with experiments - Instead of trusting tracking data, run simple tests. Pause channels, shift budgets, and measure business impact. This reveals truth that no analytics platform can provide.
Optimize for customer lifetime value - A customer acquired through "expensive" SEO who stays for two years is more valuable than a "cheap" Facebook customer who churns after one month. Look beyond immediate conversion costs.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS startups implementing this approach:
Track MRR growth as your primary metric
Test content marketing for 6-month periods
Focus on trial-to-paid conversion over attribution
For your Ecommerce store
For ecommerce stores using this framework:
Monitor total profit margins over channel attribution
Test seasonal budget allocation strategies
Prioritize customer lifetime value metrics