Growth & Strategy
Personas
Ecommerce
Time to ROI
Short-term (< 3 months)
I used to be obsessed with finding the "perfect" paid advertising network. Facebook vs Google vs TikTok vs Pinterest - I'd spend hours analyzing CPMs, audience sizes, and targeting capabilities for my B2C Shopify client. Sound familiar?
Then I discovered something that completely changed how I think about paid loops: the network doesn't matter anymore. What matters is whether you can feed the algorithm enough creative variations to find what works.
While everyone's debating which platform has better targeting (spoiler: they're all pretty broken now), I learned that successful paid loops are built on creative testing systems, not network selection. This shift in thinking helped my client move from mediocre ROAS across multiple platforms to consistently profitable campaigns by focusing on the right fundamentals.
Here's what you'll learn:
Why choosing a paid network is the wrong question in 2025
The creative testing framework that actually moves the needle
How privacy changes killed traditional targeting (and what to do instead)
My systematic approach to creative production that scales
When to abandon a network vs when to double down
Reality Check
What every marketer asks about paid advertising networks
Walk into any marketing conference or scroll through any advertising forum, and you'll hear the same questions over and over: "Which network gives the best ROAS?" "Is TikTok better than Facebook for Gen Z?" "Should I try Pinterest for my product?"
The industry has convinced everyone that network selection is the key to paid advertising success. Marketing gurus create detailed comparison charts showing audience demographics, average CPCs, and engagement rates across platforms. Agencies position themselves as "Facebook specialists" or "Google Ads experts" as if the platform itself determines success.
This obsession with network selection exists because it's easier to talk about platforms than creative strategy. It's more comfortable to debate targeting options than to admit that most ads just aren't good enough to stop people scrolling.
The conventional wisdom goes like this:
Facebook: Great for detailed targeting and lookalike audiences
Google Ads: Perfect for high-intent search traffic
TikTok: Best for reaching younger demographics
Pinterest: Ideal for lifestyle and visual products
LinkedIn: The go-to for B2B targeting
Here's the problem: privacy regulations killed detailed targeting. iOS updates, cookie deprecation, and GDPR have made audience targeting largely ineffective across all platforms. Yet marketers keep acting like it's 2018 and detailed targeting still works.
While everyone's still debating network features that barely work anymore, the real winners have shifted to what actually drives results in the privacy-first era: creative quality and testing velocity.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
About two years ago, I was managing Facebook Ads for a B2C Shopify store selling fashion accessories. Like most marketers, I was convinced that Facebook's targeting was the secret sauce. I spent weeks building detailed audience segments - interest targeting, lookalike audiences, behavioral data. The works.
The results were... mediocre. ROAS hovered around 2.5, which wasn't terrible, but wasn't great either given the product margins. More frustrating was the inconsistency - some weeks we'd hit 4x ROAS, other weeks barely break even.
My first instinct was classic marketer thinking: "Maybe I need to try other networks." So I launched the same campaigns on Google Shopping, Pinterest, and even tested TikTok. Same targeting strategies, same ad creative, different platforms.
The results were eerily similar across all networks. Some performed slightly better, some slightly worse, but nothing dramatically different. That's when it hit me - I was solving the wrong problem.
The real wake-up call came during a campaign analysis. I noticed that our best-performing Facebook ads weren't winning because of better targeting. They were winning because of the creative. The audiences were almost identical, but one video format was crushing everything else.
This led to an uncomfortable realization: I'd been spending 80% of my time on audience research and 20% on creative development. That ratio was completely backwards for what actually drives performance in 2025.
The client's business was successful, but we were leaving money on the table by treating network selection as the primary lever instead of creative testing as the growth engine.
Here's my playbook
What I ended up doing and the results.
Instead of jumping between networks, I completely restructured how we approached paid advertising. The framework I developed focuses on creative testing velocity rather than platform optimization.
Step 1: The One Big Campaign Strategy
I consolidated everything into a single, broad Facebook campaign. No detailed targeting, no interest-based audiences, just basic demographics (gender, age, country). This might sound counterintuitive, but here's why it works: Facebook's algorithm is incredibly good at finding the right people if you give it the right creative signals.
The campaign structure was simple:
1 campaign with a clear objective (purchases)
1 broad audience (women 25-55 in target countries)
Multiple ad sets with different creative angles
Step 2: The 3-Creative Weekly Rhythm
This is where the magic happened. Instead of obsessing over audience tweaks, we committed to producing and testing 3 new creative variations every single week. Not 3 campaigns, not 3 audiences - 3 completely different creative approaches.
The creative testing categories were:
Problem-focused: Highlighting the specific issue our product solved
Lifestyle-focused: Showing the product in aspirational contexts
Social proof-focused: Featuring customer testimonials and reviews
Feature-focused: Demonstrating unique product benefits
Step 3: The Creative Performance System
I built a simple tracking system to monitor which creative angles were winning. Each week, we'd analyze:
Cost per click by creative type
Click-through rates by format (video vs static)
Conversion rates by message angle
Overall ROAS by creative category
Step 4: The Creative Scaling Framework
When a creative angle showed promise (CTR above 2%, CVR above 3%), we'd create 5-7 variations of that specific approach. Same core message, different executions. This is where we saw the biggest ROAS improvements.
The key insight: platforms are distribution channels, but creatives are targeting mechanisms. A lifestyle-focused creative will naturally attract lifestyle-conscious buyers. A problem-focused creative will attract people actively looking for solutions. The algorithm figures out who to show what to.
Step 5: Network Expansion Strategy
Only after we had a proven creative system on Facebook did we expand to other networks. But here's the crucial part - we brought the same creative-first approach to each platform. We didn't optimize for the platform; we optimized for the creative angles that were already working.
Creative Testing
Focus on testing velocity, not perfect targeting. 3 new creative angles weekly beats 30 audience variations monthly.
Broad Targeting
Use basic demographics only. Let the algorithm find your people through creative signals rather than detailed interests.
Performance Tracking
Monitor creative performance, not just campaign metrics. Track which message angles drive the highest conversion rates.
Scaling Framework
Double down on winning creative themes with multiple variations rather than spreading budget across random experiments.
The results were dramatic and consistent across the board. Within 8 weeks of implementing the creative-first approach, we saw significant improvements that sustained over months.
ROAS Performance: Overall ROAS improved from 2.5 to consistently above 4.2, with our best-performing creative angles hitting 6x+ ROAS during peak periods.
Creative Insights: The biggest surprise was which creative angles actually worked. Our assumption that lifestyle content would perform best was completely wrong - problem-solving demonstrations consistently outperformed aspirational content by 40%.
Platform Performance: When we eventually expanded to other networks using the same creative approach, the performance translated almost directly. Google Shopping campaigns using our best-performing video formats achieved 5.8x ROAS within the first month.
Operational Efficiency: Perhaps most importantly, we stopped wasting time on platform optimization. The team could focus entirely on creative production and testing, which is where the real leverage exists in modern paid advertising.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
This experience completely changed how I think about paid advertising strategy. The biggest lessons learned challenge most of what the industry teaches about network selection.
1. Networks are commoditized distribution - They all have similar audiences and similar capabilities. The differentiation comes from your creative strategy, not your platform choice.
2. Privacy changes leveled the playing field - With detailed targeting mostly dead, all networks are essentially broad reach platforms now. Creative quality is the only remaining competitive advantage.
3. Testing velocity trumps testing volume - It's better to test 3 high-quality creative variations weekly than 20 audience segments monthly. The creative insights compound faster.
4. Algorithm optimization beats manual optimization - Modern ad platforms are incredibly sophisticated at finding the right people if you give them the right signals through creative content.
5. Creative angles are the new targeting - A problem-focused creative naturally attracts people with that problem. A lifestyle creative attracts lifestyle-conscious buyers. Your creative becomes your targeting mechanism.
6. Cross-platform creative strategies work - Once you understand which creative angles work for your audience, they translate across platforms much better than targeting strategies do.
7. Focus creates better results than diversification - One campaign with systematic creative testing outperforms multiple campaigns with scattered approaches.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS startups looking to implement this approach:
Start with one platform and broad targeting before expanding
Test problem-focused vs solution-focused creative messaging
Focus on demo request quality over volume metrics
Use customer interview insights to inform creative angles
For your Ecommerce store
For ecommerce stores implementing this creative-first strategy:
Test product demonstration vs lifestyle context regularly
Use customer reviews as creative inspiration sources
Focus on purchase conversion rates over click metrics
Scale winning creative angles before testing new platforms