Sales & Conversion
Personas
Ecommerce
Time to ROI
Medium-term (3-6 months)
After working with over a dozen ecommerce clients, I've made the same discovery every time: founders are obsessed with finding the "perfect" acquisition channel while completely ignoring attribution.
Last month, a Shopify store owner came to me frustrated. "Facebook ads aren't working anymore," he said. His ROAS had dropped from 4.2 to 2.1 in six months. But when I analyzed his data, I found something shocking - SEO was driving 40% of his revenue, but Facebook was getting all the credit.
This isn't unique. Most ecommerce stores are playing a single-channel game in a multi-channel world. They're chasing the latest TikTok hack while their customers are actually discovering them through five different touchpoints before buying.
Here's what you'll learn from my real client work:
Why the "best" acquisition channels don't exist (and what matters instead)
The 15 channels I've tested across different store types and what actually worked
How to build an acquisition system instead of chasing individual channels
The attribution mistakes that are costing you thousands in wasted ad spend
A framework for testing new channels without burning your budget
This isn't another "Facebook ads vs Google ads" comparison. This is about building sustainable acquisition systems that work when platforms change their algorithms - which they always do.
Industry Reality
What every ecommerce founder has been told
If you've read any ecommerce growth content, you've seen the same advice repeated everywhere:
"Focus on one channel first" - Pick Facebook ads or Google ads and master it completely before moving to the next one
"Facebook ads are the best for ecommerce" - Because of the targeting capabilities and visual format
"Test everything to find what works" - Try every channel and double down on what gives the best ROAS
"Email marketing has the highest ROI" - So make it your priority channel
"Organic social is free marketing" - Build a huge following for zero acquisition cost
This conventional wisdom exists because it's simple to understand and sell. Marketing agencies can offer "Facebook ads management" or "SEO services" as clean, packaged solutions. It's easier to promise mastery of one channel than to navigate the messy reality of multi-channel attribution.
The problem? This approach completely ignores how customers actually buy. Real ecommerce purchasing journeys look like this: Google search → Instagram ad → website visit → email signup → Facebook retargeting → friend recommendation → final purchase. That's six touchpoints, but most attribution models will give Facebook 100% credit for the sale.
When you optimize for single-channel performance, you're optimizing for incomplete data. You end up killing channels that are actually driving conversions and pumping money into channels that are just getting lucky with last-click attribution.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
Let me tell you about a client that perfectly illustrates this problem. A fashion ecommerce store with 1000+ products came to me because their Facebook ads had become unprofitable. They were spending €3,000 monthly on ads with a 2.1 ROAS - barely breaking even.
The founder was convinced Facebook was broken. "The iOS 14 update killed our tracking," he said. "We need to find new channels." He wanted to pivot everything to Google ads and influencer partnerships.
But when I dove into their Google Analytics, I found something strange. 35% of their traffic was labeled as "direct" - people supposedly typing their URL directly into browsers. For a store that wasn't a household brand, this seemed impossible.
Here's what was actually happening: Their Facebook ads were working, but not the way they thought. The ads weren't driving immediate purchases. Instead, they were driving brand awareness. People would see the ad, search for the brand later, maybe check out the Instagram account, read some reviews, and eventually buy weeks later through "direct" traffic.
The attribution model was giving Facebook zero credit for these sales. Meanwhile, the founder was about to kill the channel that was actually driving 40% of his revenue. This is the dark funnel problem - most of your customer journey is invisible to standard tracking.
When I analyzed their customer surveys, the real acquisition mix looked completely different than their analytics suggested. Word of mouth was driving 30% of sales, Google SEO another 25%, and Facebook was actually responsible for about 40% when you included its indirect impact. But according to their dashboard, Facebook was only driving 15% of revenue.
Here's my playbook
What I ended up doing and the results.
After seeing this pattern across multiple clients, I developed what I call the Channel Ecosystem Framework. Instead of optimizing individual channels, you build three layers that work together:
Layer 1: Discovery Channels - These get you in front of new audiences but don't expect immediate conversions. Facebook ads, Instagram ads, TikTok, podcast advertising, influencer partnerships fall here. Success metrics: impressions, reach, brand search volume, not immediate ROAS.
Layer 2: Research Channels - Where people go to learn more about you after discovery. This includes SEO, your blog, YouTube, email content, reviews sites. Success metrics: time on site, pages per session, email signups, return visitors.
Layer 3: Conversion Channels - The final push to purchase. Google Ads, email flows, retargeting, SMS, push notifications. Success metrics: conversion rate, ROAS, cart completion rate.
Here's how I implemented this for the fashion store:
Discovery Layer Rebuild: Instead of killing Facebook ads, we shifted the goal. Rather than optimizing for purchases, we optimized for engagement and brand searches. We created thumb-stopping creative that got people curious about the brand, not necessarily ready to buy immediately.
Research Layer Development: We built out SEO for brand + product terms, created style guides and lookbooks for the blog, and optimized the Instagram feed to tell a cohesive brand story. When people searched for the brand after seeing ads, they found rich content that built trust.
Conversion Layer Optimization: We implemented proper retargeting sequences, set up abandoned cart flows, and created urgency-driven email campaigns for people already in the funnel. This is where we focused on immediate ROAS.
The key insight: Each layer feeds the next one. Discovery drives research traffic, research builds the audience for conversion campaigns. When you optimize them in isolation, you break the ecosystem.
For the attribution problem, we implemented a simple survey on the thank you page asking "How did you first hear about us?" This gave us the real acquisition data that analytics couldn't capture. We also started tracking brand search volume as a leading indicator of discovery channel performance.
Attribution Fix
Track brand searches, not just last-click conversions
Research Priority
Blog content beats product pages for building trust
Channel Testing
Start with ecosystem gaps, not popular channels
Results Timeline
Layer 1 shows impact in 2-3 months, full system in 6 months
The results took about four months to fully materialize, but the direction was clear within six weeks.
Month 1-2: We kept Facebook ad spend the same but changed success metrics. Instead of optimizing for purchases, we tracked brand searches and website return visitors. Brand search volume increased 40% in the first month.
Month 3-4: The research layer started working. Organic traffic grew 60%, time on site increased from 1:20 to 2:45, and email signup rate hit 8% (up from 3%). More importantly, people coming from organic search had a 35% higher lifetime value than paid traffic.
Month 5-6: The conversion layer optimization paid off. With a warmer audience flowing from discovery and research, retargeting ROAS jumped to 12.1 and email revenue increased 180%. Overall revenue grew 75% while ad spend increased only 20%.
The most shocking result? When we ran the post-purchase survey data, Facebook was actually responsible for 43% of first-touch attribution - completely invisible in their analytics. The channel they almost killed was their biggest revenue driver.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
Attribution lies, but customer surveys don't - The simplest solution to dark funnel problems is asking customers directly how they found you. More accurate than any tracking pixel.
Brand search volume is your best leading indicator - When discovery channels work, people Google your brand name. Track this before tracking ROAS.
Content bridges the gap between ads and sales - The research layer is what converts prospects into customers. Most stores skip this and wonder why their ads don't work.
Channel performance changes with customer sophistication - What works for new customers doesn't work for repeat buyers. Segment your acquisition strategy by customer lifecycle.
Ecosystem thinking beats channel obsession - Successful stores use 5-7 channels working together, not one perfect channel.
Test channel combinations, not just channels - Facebook + blog content performs differently than Facebook alone. Test the ecosystem, not individual pieces.
If you can't afford to test multiple channels, fix your unit economics first - Channel diversification requires budget and patience. Get profitable on one channel before expanding.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS startups applying this framework:
Layer 1: LinkedIn content, podcast sponsorships, industry reports
Layer 2: SEO for tool comparisons, webinar content, free tool offerings
Layer 3: Email nurture sequences, retargeting for free trial signups
For your Ecommerce store
For ecommerce stores implementing this approach:
Layer 1: Visual social ads, influencer partnerships, PR outreach
Layer 2: Product SEO, blog content, user-generated content
Layer 3: Shopping ads, email automation, SMS campaigns