Growth & Strategy
Personas
SaaS & Startup
Time to ROI
Medium-term (3-6 months)
Last year, I watched a client burn through €15,000 on Facebook Ads for their beautifully designed SaaS product. Great UI, solid features, happy beta users. But their ROAS was stuck at 1.2.
The problem? They were trying to force a square peg into a round hole. Their product was perfect for patient discovery, but Facebook Ads demand instant decisions.
This isn't about having a bad product. It's about product-channel fit – the idea that your product's strengths need to align with your marketing channel's physics. Get this wrong, and even the best products fail. Get it right, and average products can 10x their ROI.
After working with dozens of SaaS and ecommerce clients, I've seen the same pattern: companies obsessing over product perfection while ignoring whether their chosen marketing channels actually suit their product's nature.
Here's what you'll learn from my real experiments:
Why paid ads failed for my 1000+ SKU ecommerce client but SEO 10x'd their traffic
How I discovered LinkedIn personal branding was driving all the "direct" conversions for a B2B SaaS
The exact framework I use to match products with their ideal marketing channels
Real data from channel switching experiments across different industries
When to abandon popular channels that don't fit your product
Industry Reality
The Product-First Obsession That's Killing ROI
Walk into any startup accelerator or marketing conference, and you'll hear the same advice repeated like gospel:
"Build a great product and the marketing will take care of itself."
The industry has convinced itself that product quality trumps everything. VCs fund "product-led growth." Consultants sell "conversion optimization." Everyone's chasing the perfect funnel, the ideal user experience, the most compelling value proposition.
Here's what the conventional wisdom says you should do:
Perfect your product until it's irresistible
Test different marketing channels with A/B tests
Scale the ones with the best CPM/CPC metrics
Optimize landing pages for higher conversion rates
Throw more budget at "winning" channels
This approach exists because it feels logical and measurable. Marketing teams love metrics they can optimize. "Our CPM improved 15%!" sounds impressive in board meetings.
But here's where this falls apart: it assumes all products work equally well in all channels. It treats marketing channels like neutral distribution pipes instead of environments with their own rules, user behaviors, and decision-making physics.
Facebook Ads reward instant gratification. SEO rewards patient research. LinkedIn favors thought leadership. TikTok demands entertainment value. Each channel has fundamentally different physics that either amplify or kill your product's natural strengths.
The result? Companies waste months optimizing tactics in the wrong channels instead of finding channels where their product naturally thrives.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
The wake-up call came with an ecommerce client who contacted me in frustration. They had over 1,000 products – beautiful, quality items with great margins. But their Facebook Ads ROAS was stuck at 2.5, barely breaking even after ad spend.
Most consultants would have started optimizing ad creative, testing audiences, or improving landing pages. But when I dug into their business model, I spotted the fundamental mismatch.
Their strength was variety and discoverability. Customers needed time to browse, compare products, and find exactly what they wanted. Think of it like a specialty store where the joy is in exploring the entire catalog.
Facebook Ads, on the other hand, work best with 1-3 hero products that sell instantly. The platform's physics demand quick decisions from users who are scrolling through social feeds, not shopping with intent.
Meanwhile, I was simultaneously working with a B2B SaaS client whose analytics showed tons of "direct" conversions with no clear attribution. The marketing team was celebrating their "organic brand strength," but something felt off.
I started digging deeper into their traffic sources and user behavior. What I discovered changed everything: most of those "direct" conversions weren't really direct at all.
People were finding the founder's LinkedIn content, following him for weeks or months, building trust through his insights, then typing the company URL directly when they were ready to evaluate solutions.
The attribution was wrong, but more importantly, the marketing strategy was backwards. They were spending thousands on cold Facebook Ads when their real growth engine was the founder's personal branding on LinkedIn.
Both clients taught me the same lesson: you can't change the rules of a marketing channel, but you can choose channels where your product's rules become advantages.
Here's my playbook
What I ended up doing and the results.
After seeing this pattern across dozens of clients, I developed a systematic approach to product-channel fit that consistently improves ROI. Here's the exact framework I use:
Step 1: Map Your Product's Natural Behavior
Before touching any marketing channels, I audit how the product naturally wants to be discovered and evaluated:
Decision timeline: Does your product require instant decisions or patient evaluation?
Discovery method: Do customers know they need this, or do they stumble into the need?
Evaluation process: Do they need to compare options or trust your expertise?
Purchase complexity: Simple checkout or multi-stakeholder approval?
For my ecommerce client, this revealed: long decision timeline, discovery-driven browsing, comparison shopping, simple individual purchase. Perfect for SEO, terrible for Facebook Ads.
Step 2: Channel Physics Analysis
Next, I map each potential marketing channel's inherent characteristics:
Facebook/Meta Ads: Interruption-based, instant decision context, social proof driven, impulse-friendly
Google Ads: Intent-based, solution-seeking context, comparison-friendly, research-mode users
SEO/Content: Patient discovery, educational context, trust-building over time, expertise-driven
LinkedIn (Personal): Relationship-based, thought leadership context, professional trust, long-term nurturing
Step 3: The Fit Matrix
I create a simple matrix scoring how well each product characteristic aligns with each channel's physics. Instead of measuring CPM or CTR, I'm measuring fundamental compatibility.
For the ecommerce client: Facebook scored 2/10 for fit, SEO scored 9/10. For the B2B SaaS: Facebook scored 3/10, LinkedIn personal branding scored 10/10.
Step 4: The Channel Switch Experiment
Rather than optimizing within poorly-fitted channels, I completely pivot to high-fit channels for 90 days.
For the ecommerce store, we paused Facebook Ads entirely and went all-in on SEO. I rebuilt their site architecture around search intent, created content targeting long-tail product discovery keywords, and optimized their product pages for organic visibility.
For the B2B SaaS, we stopped cold outbound and Facebook campaigns. Instead, we focused entirely on the founder's LinkedIn content strategy and SEO for bottom-funnel terms.
Step 5: Results Measurement
I track different metrics depending on the channel's natural timeline:
Short-term channels (Ads): Immediate ROAS, cost per acquisition
Medium-term channels (SEO): 90-day traffic growth, organic conversion rates
Long-term channels (Content): 6-month attribution, relationship-driven conversions
The key insight: measuring a long-term channel with short-term metrics (or vice versa) will always make it look like a failure.
Channel Physics
Understanding each marketing channel's inherent rules and user behaviors
Attribution Mapping
Tracking how customers actually discover and convert, not just last-click data
Fit Scoring
Systematic framework for matching product characteristics with channel strengths
Timeline Alignment
Measuring channels on their natural conversion timelines, not arbitrary windows
The results spoke for themselves, but not always in the timeframe clients expected.
For the ecommerce client, the SEO pivot took 3 months to show results, but when it hit, traffic went from 500 monthly visitors to over 5,000. More importantly, these were high-intent visitors actually browsing and buying, not just clicking and bouncing.
The B2B SaaS saw even more dramatic results. Once we identified that LinkedIn personal branding was their real growth engine, we could double down properly. The founder's content went from sporadic posting to a systematic thought leadership strategy.
Within 6 months, leads attributed to "direct" traffic (actually LinkedIn-driven) increased by 300%. But the real win was lead quality – these prospects came in already educated and pre-sold on the founder's expertise.
Here's what surprised me most: both companies had been optimizing the wrong metrics in the wrong channels for months. They weren't failing because their products were bad or their marketing was incompetent. They were failing because they were trying to make their products work in fundamentally incompatible environments.
The ROI improvement wasn't from better ads or higher conversion rates. It was from finding channels where their natural product strengths became competitive advantages instead of obstacles.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
After running this experiment across multiple industries, here are the seven lessons that changed how I approach marketing strategy:
Channel compatibility beats channel popularity: Don't choose channels because everyone else uses them. Choose channels where your product naturally thrives.
Attribution lies, but behavior doesn't: Dig deeper than last-click attribution. Understand the real customer journey, even if your analytics can't measure it perfectly.
Optimization is useless in the wrong channel: Perfect ad creative can't overcome fundamental product-channel mismatch. Move channels before optimizing tactics.
Timeline mismatch kills everything: Measuring long-term channels with short-term metrics makes everything look like failure. Align measurement windows with channel physics.
Success patterns are industry-specific: What works for SaaS might kill ecommerce ROI. Pattern-match within your industry, not across all businesses.
Multiple channels can confuse attribution: When testing channel fit, go all-in on one channel for 90 days rather than splitting budget across multiple experiments.
Product-channel fit compounds over time: Once you find the right fit, doubling down creates exponential returns rather than linear improvements.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS startups, focus on these product-channel fit principles:
Map your customer's evaluation timeline before choosing channels
Test LinkedIn personal branding for complex B2B products
Use SEO for bottom-funnel "[product] alternative" searches
Avoid paid social for high-consideration purchases
For your Ecommerce store
For ecommerce stores, prioritize channels that match your catalog:
Large catalogs (500+ products) typically thrive on SEO over paid ads
Simple hero products work well with Facebook/Instagram ads
Build organic discovery through programmatic SEO approaches
Test Google Shopping for product-comparison behaviors