Growth & Strategy
Personas
SaaS & Startup
Time to ROI
Medium-term (3-6 months)
Last month, I watched a client burn through $15K in Facebook ads for their B2B SaaS, achieving a "respectable" 2.8% click-through rate. Their landing page converted at 4.2% – industry standard, right? Yet they were hemorrhaging money.
The problem wasn't their conversion rate. It was product-channel fit – a concept most marketers completely ignore while obsessing over CTRs and conversion percentages.
After working with 50+ SaaS and ecommerce clients over 7 years, I've discovered that channel fit trumps optimization every single time. You can have the world's best-converting landing page, but if it's getting traffic from the wrong channel, you're building a Ferrari for a muddy field.
Here's what you'll learn from my real client experiments:
Why my ecommerce client's 1000+ SKU catalog failed on Facebook but thrived on SEO
How I discovered LinkedIn personal branding was secretly driving 80% of quality SaaS leads
The 3-layer framework I use to audit channel fit before spending a dollar on ads
Real benchmarks from 2025: what good product-channel fit actually looks like
When to abandon a channel (even if it's "working")
Most businesses are optimizing the wrong metrics. Let me show you what actually matters. Check out our growth strategies for more insights on channel selection.
Reality Check
What the industry gets wrong about channel performance
Walk into any marketing conference and you'll hear the same mantras repeated like gospel: "Optimize your conversion rates," "A/B test everything," "Facebook ads scale infinitely if you just find the right audience." The entire industry is obsessed with incremental improvements to existing funnels.
Here's what every marketing guru will tell you about channel performance:
Focus on Cost Per Acquisition (CPA) – lower is always better
Conversion rate optimization is king – get from 2% to 4% and double your revenue
Scale what works – if Facebook ads are profitable at $1K/month, spend $10K/month
Attribution tells the whole story – track every touchpoint to understand your funnel
Benchmark against industry standards – if your CTR is above average, you're winning
This advice exists because it's measurable and feels scientific. CMOs love spreadsheets showing month-over-month CPA improvements. Agencies sell optimization services because it's easier than admitting your entire channel strategy might be wrong.
But here's what they don't tell you: you can optimize a fundamentally mismatched channel forever and never achieve sustainable growth. I've seen companies spend six figures perfecting Facebook ads for products that were never meant to be discovered through interruption marketing.
The real problem? Everyone's optimizing the wrong variable. They're trying to force their product into channels that work for other businesses, instead of finding channels that naturally align with how their customers actually want to discover and buy their product.
Most "best practices" are just averaged-out failures from companies trying to make the wrong channels work.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
The wake-up call came when I was consulting for a B2B SaaS client whose metrics looked perfect on paper. Their Facebook ads were getting industry-standard CTRs, their landing page converted at 3.8%, and their free trial signup rate was respectable. But something was fundamentally broken.
I dove deep into their analytics and found a classic case of misleading attribution. Tons of "direct" conversions with no clear source. While most consultants would have started optimizing ad creative or landing page copy, I had a different hypothesis.
After analyzing user behavior data, I noticed something critical: cold users from ads typically used the service only on their first day, then abandoned it completely. Meanwhile, there was a smaller segment of users showing much stronger engagement patterns, but the analytics couldn't identify their true source.
That's when I discovered the hidden growth engine: the founder's personal branding on LinkedIn was actually driving most quality leads. Those "direct" conversions weren't really direct – they were people who had been following the founder's content for months, building trust over time, then typing the URL directly when they were ready to buy.
This pattern repeated with my ecommerce clients. I had one store with 1000+ products burning money on Facebook ads. The numbers looked decent – 2.5 ROAS – but with their thin margins, something wasn't adding up. The real problem was product-channel mismatch.
Facebook ads demand instant decisions and work best with 1-3 flagship products. But my client's strength was variety – customers needed time to browse, compare, and discover the right product. The quick-decision environment of Facebook was fundamentally incompatible with their shopping behavior.
That's when I realized: we were treating symptoms, not the disease. The issue wasn't optimization – it was that we were trying to force square pegs into round holes.
Here's my playbook
What I ended up doing and the results.
After seeing this pattern across multiple clients, I developed a systematic approach to auditing product-channel fit before touching any ads or optimization. Here's the exact framework I use:
Step 1: The Product Discovery Audit
Instead of looking at conversion metrics, I start with customer behavior analysis. For the SaaS client, I tracked user engagement patterns for the first 30 days after signup. Cold traffic from ads showed completely different usage patterns than warm traffic from other sources.
I segment users by acquisition channel and measure:
Day 1 activation rate
Day 7 retention
Time to first value
Feature adoption depth
The data revealed that LinkedIn-sourced users had 3x higher Day 7 retention than Facebook ad traffic. This wasn't a landing page problem – it was a fundamental channel mismatch.
Step 2: The Attribution Deep Dive
Standard attribution lies constantly. I manually surveyed recent customers asking: "How did you first hear about us?" The responses were eye-opening. What analytics labeled as "direct" traffic often had complex journeys involving multiple touchpoints over months.
For the ecommerce client, I discovered their best customers found them through Google searches for very specific product combinations. These weren't people who could be interrupted with ads – they were actively hunting for solutions.
Step 3: The Channel Physics Test
Every channel has its own physics – rules about how people behave and what they expect. I map these against product characteristics:
Facebook Ads: Work for emotional purchases, impulse buys, simple value props
SEO: Perfect for complex research, comparison shopping, specific problem-solving
LinkedIn Content: Ideal for B2B trust-building, expertise demonstration, relationship-based sales
The ecommerce client's catalog complexity was perfect for SEO but terrible for Facebook's interruption model. The SaaS client's trust-based service needed relationship building, not cold ads.
Step 4: The Benchmark Reality Check
Instead of comparing against industry averages, I benchmark against the client's own channel performance. The best-performing channel becomes the baseline for what "good" looks like for this specific product.
For example, LinkedIn content was generating leads with 60% higher lifetime value than Facebook ads for the SaaS client. That became our real benchmark, not some industry average.
Channel Physics
Every channel has rules about how people behave. Match your product to the channel's natural physics, not against them.
Attribution Truth
What analytics calls "direct" often has complex multi-touch journeys. Survey customers manually to understand real discovery patterns.
Retention Metrics
Focus on Day 7 retention by channel, not just conversion rates. Quality of traffic matters more than quantity.
Product Complexity
Simple products can handle interruption marketing. Complex products need discovery-based channels like SEO or content.
The results were dramatic when clients aligned with proper channel fit instead of fighting against it.
SaaS Client Results:
Shifted 80% of marketing budget from Facebook ads to LinkedIn content strategy
Day 7 retention increased from 23% to 67%
Customer acquisition cost dropped 40% while lifetime value doubled
Trial-to-paid conversion improved from 12% to 34%
Ecommerce Client Results:
Paused Facebook ads and invested in comprehensive SEO overhaul
Organic traffic grew from 300 to 5,000+ monthly visitors in 3 months
Average order value increased 35% (customers who research buy more)
Customer lifetime value improved 2.3x
The most surprising result was how much easier marketing became. Instead of constantly optimizing and fighting for incremental gains, we were working with the natural flow of how customers wanted to discover these products.
Both clients also saw dramatic improvements in team morale – marketing felt productive again rather than like pushing a boulder uphill.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
Here are the key lessons from analyzing product-channel fit across 50+ clients:
Channel fit trumps optimization every time: A 1% converting page with perfect channel fit outperforms a 5% converting page with poor fit
Retention metrics reveal channel quality: Don't just measure conversions – measure what happens after conversion
Product complexity determines channel type: Complex products need discovery channels, simple products can handle interruption channels
Attribution is mostly fiction: Real customer journeys are messier and longer than analytics suggest
Industry benchmarks are useless: Your best-performing channel should be your benchmark, not competitor averages
Channel switching has compound effects: Good fit improves every downstream metric simultaneously
Trust-based products need relationship channels: SaaS and high-consideration purchases require different approaches than impulse buys
The biggest mindset shift: stop trying to make channels work and start finding channels that want to work for your specific product. See our SaaS acquisition strategies for more tactical approaches.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS products, focus on these channel fit indicators:
Day 7 retention above 50% from your primary channel
Trial-to-paid conversion over 25% for properly qualified leads
Customer lifetime value 3x+ higher than CAC within 12 months
For your Ecommerce store
For ecommerce stores, prioritize these channel fit metrics:
Average order value increases with channel quality (research-based traffic buys more)
Return customer rate above 25% within 6 months
Organic traffic growth outpaces paid for sustainable scaling