Sales & Conversion
Personas
Ecommerce
Time to ROI
Short-term (< 3 months)
Last year, I was managing Facebook ads for a Shopify client who was burning through budget faster than they were making sales. Despite having what looked like perfectly crafted audience segments - interest targeting, lookalikes, detailed demographics - their ROAS was stuck at a disappointing 2.5x.
The breakthrough came when I completely flipped the strategy. Instead of trying to outsmart Facebook's algorithm with detailed targeting, I let the platform do what it does best: find customers automatically through creative testing.
This shift from audience-obsessed to creative-focused advertising changed everything. We went from struggling with mediocre performance to discovering that creatives are the new targeting in 2025.
Here's what you'll learn from this experience:
Why detailed audience targeting is actually hurting your Facebook ad performance
The simple framework I used to test 3 new creatives every single week
How one broad audience outperformed 12 different "perfect" segments
The creative testing rhythm that scales with any e-commerce budget
Why Facebook's algorithm is better at finding customers than you are
If you're tired of complex targeting setups that don't deliver results, this approach will simplify your ad strategy while improving performance. No more audience guesswork - just consistent creative testing that actually works. For more scaling strategies, check out our conversion optimization playbook.
Industry Reality
What every e-commerce advertiser has been told
The Facebook ads industry has been built on a fundamental belief: targeting is everything. Every course, every guru, every agency pitches the same approach.
Here's the conventional wisdom you've probably heard:
Build detailed audience segments - Layer interests, behaviors, and demographics for "laser-focused" targeting
Create lookalike audiences - Upload your customer list and let Facebook find similar people
Test different audience sizes - Start narrow, then expand based on performance
Use interest stacking - Combine multiple interests to narrow down to your "ideal" customer
Exclude audiences - Remove people who already bought or aren't qualified
This approach exists because it feels logical. If you can describe your ideal customer, shouldn't you be able to target them directly? It's intuitive, it's controllable, and it makes advertisers feel smart.
The problem? Privacy regulations killed detailed targeting. iOS 14.5+ and GDPR have made audience data increasingly unreliable. What used to work in 2019 is actually limiting your reach in 2025.
But here's what most advertisers miss: Facebook's algorithm has gotten dramatically better at finding customers automatically. The platform processes billions of signals every day. It knows who's likely to buy better than your carefully crafted audience segments ever could.
The shift I'm about to share isn't just a tactic - it's recognizing that the entire game has changed.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
When I started managing this Shopify client's Facebook ads, they had the "perfect" setup according to every Facebook ads course out there. Multiple ad sets with different audience segments, carefully crafted interest combinations, and detailed demographic targeting.
The client was a B2C e-commerce store with over 1,000 products in their catalog. They were spending about €3,000 per month on Facebook ads but struggling to make the math work. With a €50 average order value and small margins, that 2.5 ROAS meant they were barely breaking even.
The problem became clear when I audited their account structure. They had:
12 different ad sets targeting various interest combinations
Age and gender restrictions on every campaign
Multiple lookalike audiences at different percentages
The same creative running across all these segments
What I discovered was fascinating: their "best performing audience" was actually just the one that happened to get the newest creative first. When I dug deeper into the account history, every time performance improved, it coincided with new creative being added - not audience optimizations.
The real problem wasn't their targeting - it was creative fatigue. They were running the same product images and basic promotional copy across all segments. Facebook's algorithm was getting bored, and so were their potential customers.
That's when I realized we were solving the wrong problem entirely. Instead of trying to find the perfect audience, we needed to give Facebook's algorithm better creative signals to work with.
Here's my playbook
What I ended up doing and the results.
I completely restructured their Facebook ads approach around one core principle: let Facebook find the customers while you focus on creative diversity.
Here's the exact system I implemented:
Step 1: Simplified Campaign Structure
Instead of 12 ad sets with different audiences, I created one main campaign with a single broad audience. No detailed interests, no demographic restrictions beyond basic geography. Just one large, broad audience that gave Facebook maximum flexibility.
Step 2: Creative-First Testing Framework
I established a rhythm of testing 3 new creative variations every single week. These weren't just different product shots - they were completely different angles:
Lifestyle-focused creatives (showing products in use)
Problem-solving creatives (addressing specific pain points)
Social proof creatives (user-generated content and reviews)
Benefit-driven creatives (highlighting key features)
Step 3: Algorithm Learning Optimization
Each creative variation ran as its own ad set within the broad campaign. This gave Facebook multiple signals about what resonated with different customer segments without me having to guess who those segments were.
Step 4: Performance-Based Creative Rotation
Instead of targeting optimization, I focused entirely on creative performance metrics. Ads that maintained strong CTR and conversion rates kept running. Those that showed fatigue got paused and replaced with new variations.
The beauty of this approach was its simplicity. Instead of managing complex audience matrices, I spent my time on what actually moved the needle: creating diverse, engaging creative content that gave Facebook's algorithm rich signals to optimize against.
This wasn't about abandoning targeting entirely - it was about recognizing that your creative strategy IS your targeting strategy in the post-iOS 14.5 world.
Creative Diversity
Testing different angles weekly prevents algorithm fatigue and discovers unexpected winner concepts
Broad Targeting
One large audience gives Facebook maximum optimization flexibility compared to restrictive segments
Weekly Rhythm
Consistent creative refresh schedule maintains performance while building a library of proven concepts
Algorithm Signals
Multiple creative variations provide rich data for Facebook to identify your best customer segments automatically
The transformation was immediate and sustained. Within the first month of implementing this creative-focused approach:
The single broad audience campaign outperformed all 12 previous audience segments combined. More importantly, we discovered creative angles that we never would have found through audience targeting alone.
One unexpected winner was user-generated content showing customers using products in unexpected ways. This creative angle attracted an entirely different customer segment that our previous targeting would have missed completely.
The weekly creative testing rhythm meant we always had fresh content in the pipeline. Instead of performance declining over time due to creative fatigue, we maintained consistent results while continuously discovering new winning angles.
Perhaps most valuable was the shift in mindset. Instead of spending hours optimizing audience segments that may or may not be accurate, the focus moved to creating genuinely engaging content that resonated with real people.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
Here are the key insights that emerged from this experience:
Creative testing beats audience testing - Your next breakthrough is more likely to come from a new creative angle than a new targeting combination
Facebook knows your customers better than you do - The algorithm processes billions of signals daily and can identify patterns you'd never catch
Consistency trumps perfection - Regular creative testing with "good enough" content outperforms sporadic "perfect" campaigns
Simplicity scales better - Complex audience structures become unmanageable as you grow, while creative-focused approaches scale naturally
Your creative IS your targeting - Different creative angles naturally attract different customer segments without manual audience setup
Algorithm learning needs variety - Multiple creative signals help Facebook optimize more effectively than single-creative campaigns
Privacy changes favored this approach - As detailed targeting becomes less reliable, creative-based optimization becomes more valuable
What I'd do differently: Start creative testing from day one instead of trying audience optimization first. The weeks spent on audience tweaking could have been used to discover winning creative angles earlier.
This approach works best for e-commerce stores with visual products and sufficient budget for consistent testing. It's less effective for high-consideration purchases or very niche products where detailed targeting still adds value.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS companies adapting this approach:
Focus on testing different value propositions and use cases in creative
Test demo videos, customer testimonials, and feature highlights as creative angles
Use broad professional targeting (job titles) rather than detailed interest stacking
For your Ecommerce store
For e-commerce stores implementing this strategy:
Commit to testing 3 new creative angles every week consistently
Use user-generated content, lifestyle shots, and problem-solution creatives
Start with one broad campaign and resist the urge to over-segment audiences