Growth & Strategy
Personas
SaaS & Startup
Time to ROI
Medium-term (3-6 months)
OK, so here's something that happened to me that made me completely rethink how we approach marketing channels. I was working with this B2B SaaS client, and on paper, everything looked fine. They had multiple channels running, decent traffic numbers, and their paid ads were showing "good" metrics according to every marketing guru out there.
But here's the thing - they were burning through budget faster than a startup at a tech conference, and conversions were... well, let's just say they weren't paying the bills.
The real problem wasn't their ads, their copy, or even their product. The problem was something most businesses completely ignore: product-channel fit. They were trying to force their complex B2B solution through channels designed for impulse purchases. It's like trying to sell a house through a vending machine.
Most companies focus on optimizing within their channels - better ad copy, more targeting options, prettier landing pages. But what if the channel itself is wrong for your product? What if you're playing the wrong game entirely?
In this playbook, you'll learn:
The 5 warning signs your channel fit is completely off
Why "good" metrics can actually hide terrible channel decisions
My framework for testing channel fit without wasting budget
How to pivot channels without starting from scratch
The one question that reveals if you're in the right channel
Because sometimes the best marketing decision is knowing when to stop marketing altogether - at least in the wrong places.
Industry Reality
What everyone tells you about channel optimization
Every marketing course, guru, and "growth hacker" will tell you the same thing: optimize your way to success. They'll say your channels are fine, you just need to:
Improve your targeting - Create more specific audience segments, use lookalike audiences, try behavioral targeting
Test more creative variations - A/B test everything from headlines to button colors
Optimize your funnel - Reduce friction, improve landing pages, fix your conversion flow
Increase your budget - "You just need more data points to make it work"
Be more patient - "Good marketing takes time to compound"
This conventional wisdom exists because it's easier to sell courses on optimization than to admit some channels simply don't work for certain products. The optimization industry has a vested interest in keeping you optimizing rather than questioning fundamental assumptions.
The problem is, you can optimize a square peg all you want - it's still not going to fit in a round hole. Facebook Ads might be perfect for impulse purchases, but terrible for complex B2B sales. LinkedIn might work for thought leadership, but fail completely for e-commerce. SEO might be great for discovery, but useless for urgent solutions.
Where this advice falls short is simple: it assumes the channel itself is right for your product. It assumes that with enough optimization, any channel can work for any business. That's not just wrong - it's expensive wrong.
The reality is that product-channel fit is more important than optimization. You can't optimize your way out of a fundamental mismatch between what your product needs and what a channel provides.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
So here's what happened with that B2B SaaS client I mentioned. They came to me because their marketing was "broken." They were spending about €8,000 per month on Facebook Ads, getting decent click-through rates, and their landing pages were converting at around 2.5% - which sounds reasonable, right?
But when I dug deeper, the story was different. Their product was a complex workflow automation tool for mid-market companies. The sales cycle was typically 3-6 months, involved multiple decision makers, and required significant change management. The average deal size was around €15,000 annually.
Here's what was actually happening: People would click their Facebook ads, sign up for a free trial, maybe poke around for 10 minutes, and then... nothing. The trial-to-paid conversion rate was under 3%. They were getting lots of "leads" but almost no real prospects.
The first thing I tried was the traditional approach - better targeting, improved onboarding emails, more personalized demos. We spent two months optimizing everything. Results? Marginal improvements that didn't move the needle on revenue.
That's when I realized we had a fundamental problem. Facebook Ads work great for products you can understand and evaluate quickly. But their solution required prospects to really understand their current pain points, map out complex workflows, and envision a different way of working.
People scrolling Facebook aren't in "solve my complex business process" mode. They're in "quick entertainment" mode. We were trying to sell a business transformation to people looking for cat videos.
The breakthrough came when I started tracking what happened to users after they signed up. I discovered that the few people who actually converted to paid plans had all followed a similar pattern: they'd found the company through search (usually looking for specific solutions), spent significant time on the website reading case studies and documentation, and then signed up for the trial already half-convinced.
That's when I knew we had a channel fit problem, not an optimization problem.
Here's my playbook
What I ended up doing and the results.
Here's exactly what I did to diagnose and fix the channel fit problem:
Step 1: The Channel Audit
First, I stopped looking at vanity metrics and started tracking what actually mattered. Instead of focusing on click-through rates and signup numbers, I created a simple spreadsheet tracking the full customer journey by channel:
Time from first touch to trial signup
Trial engagement depth (features used, time spent)
Trial-to-paid conversion rate by channel
Customer lifetime value by acquisition channel
The data was eye-opening. Facebook traffic converted to trials quickly but showed almost no product engagement. SEO traffic took longer to convert but showed 10x higher trial engagement and 5x better trial-to-paid conversion.
Step 2: The User Behavior Analysis
I started interviewing customers and prospects to understand their discovery and evaluation process. I asked three key questions:
"What was happening in your business when you started looking for this solution?"
"How did you first hear about us?"
"What made you decide to try our product?"
The pattern was clear: successful customers weren't discovering them randomly through ads. They were actively searching for solutions to specific problems. They needed time to research, compare options, and build internal consensus.
Step 3: The Channel Mismatch Framework
I developed a simple framework to evaluate channel fit by mapping product characteristics against channel strengths:
Product Requirements: High consideration, complex evaluation, multiple stakeholders, long sales cycle, significant investment
Facebook Ads Reality: Low consideration, quick decisions, individual buyers, impulse purchases, smaller investments
The mismatch was obvious once we mapped it out.
Step 4: The Strategic Pivot
Instead of trying to make Facebook work, I shifted the budget to channels that matched their customer behavior:
60% to SEO content targeting problem-specific keywords
25% to LinkedIn thought leadership and content distribution
15% to strategic partnerships and referral programs
The content strategy focused on creating in-depth resources for people actively researching solutions - comparison guides, implementation case studies, and ROI calculators.
Step 5: The Measurement Shift
We completely changed how we measured success. Instead of optimizing for signup volume, we optimized for qualified pipeline. Instead of tracking cost-per-click, we tracked cost-per-qualified-opportunity.
This meant accepting lower traffic numbers in exchange for higher-quality prospects who were already in buying mode when they found us.
Channel Audit
Track full customer journey by channel, not just top-of-funnel metrics. Focus on trial engagement depth and lifetime value.
Behavior Mapping
Interview customers to understand their actual discovery process. Map product complexity against channel capabilities.
Strategic Pivot
Shift budget from mismatched channels to ones that align with customer behavior patterns and buying process.
Success Metrics
Redefine success metrics from volume-based to quality-based. Optimize for qualified pipeline, not signup numbers.
The transformation didn't happen overnight, but the results were significant. Within 4 months of implementing the new channel strategy:
The numbers that mattered improved dramatically:
Trial-to-paid conversion rate increased from 3% to 18%
Average deal size grew 40% (better-qualified prospects)
Sales cycle shortened by 6 weeks (prospects came pre-educated)
Customer acquisition cost decreased by 60%
But more importantly, the quality of conversations changed completely. Sales calls went from "What is this product?" to "How do we implement this?" The sales team stopped spending time on education and started focusing on solution design.
The unexpected outcome was that customer success metrics improved too. Because prospects were self-selecting and came with realistic expectations, they had much higher product adoption rates and lower churn.
What surprised me most was how much easier marketing became. Instead of fighting against channel physics, we were working with them. Content performed better because it reached people who actually wanted to read it. LinkedIn engagement increased because we were sharing insights that resonated with our actual audience.
The lesson wasn't just about this specific client - it was about recognizing when you're solving the wrong problem entirely.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
Looking back, here are the key lessons that apply to any business questioning their channel fit:
Good metrics can hide bad strategy. High click-through rates and signup numbers mean nothing if they don't lead to revenue. Always track to the bottom of the funnel.
Channel physics beat optimization every time. You can't optimize your way out of a fundamental mismatch between your product and your channel.
Customer interviews trump data dashboards. Numbers tell you what happened, but conversations tell you why it happened.
Channel fit is about behavior, not demographics. It's not about reaching the right people - it's about reaching people in the right mindset.
Sometimes the best decision is to stop. Cutting a channel that doesn't work frees up resources for channels that do.
Patience pays in the right channels. SEO and content take longer to show results, but they compound in ways that paid ads never do.
Quality beats quantity every time. 10 highly qualified prospects are worth more than 1,000 random signups.
The biggest mistake I see businesses make is treating channel fit like a temporary problem to optimize away. Instead, treat it like a fundamental strategic decision that determines everything else about your marketing approach.
If you're constantly fighting to make a channel work, that's probably your answer right there.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS companies questioning their channel fit:
Track trial engagement depth, not just signup volume
Match your sales cycle length to channel expectations
Focus on channels where prospects are already problem-aware
Prioritize educational content over promotional messaging
For your Ecommerce store
For e-commerce stores evaluating channel performance:
Consider product complexity vs. channel decision speed
Match channel browse behavior to purchase intent
Evaluate customer lifetime value by acquisition channel
Test channels that align with your product discovery process