Sales & Conversion
Personas
Ecommerce
Time to ROI
Medium-term (3-6 months)
Last year, I had a client running a B2C Shopify store with over 1,000 products who was struggling with their Facebook ads. The cost per acquisition kept climbing, and we were burning through budget faster than we could convert customers. "Let's try Google Ads Performance Max," they said. "Everyone's talking about it."
Three months and several thousand euros later, we learned the hard way that Performance Max isn't the magic bullet Google makes it out to be—especially for small stores with complex catalogs. While everyone was jumping on the automation bandwagon, we discovered that sometimes the best strategy is going against the grain.
Here's what you'll learn from our expensive experiment:
Why Performance Max failed for our 1,000+ product catalog and when automation actually hurts performance
The channel mismatch problem that no one talks about in Performance Max tutorials
Our pivot to organic growth that actually moved the needle for complex product catalogs
When Performance Max makes sense (and when it doesn't) for your store size
The alternative strategy that worked better than any paid channel we tested
If you're considering Performance Max for your store, this might save you thousands in wasted ad spend. Let's dive into what actually happened when we tested Google's "revolutionary" campaign type.
Reality Check
What Google won't tell you about Performance Max limitations
Google Ads Performance Max is being promoted as the ultimate solution for ecommerce stores. According to Google and most PPC agencies, it's supposed to:
Automatically optimize across all Google channels - Search, Display, YouTube, Gmail, and Discover
Use machine learning to find your best customers without manual audience setup
Simplify campaign management by consolidating everything into one campaign type
Maximize conversions using Google's advanced bidding algorithms
Scale performance without the need for constant optimization
The promise is compelling: set it up once, let Google's AI do the work, and watch your sales grow. Most agencies are pushing this hard because it reduces their workload while promising better results.
But here's what the case studies don't tell you: Performance Max works best for businesses with 1-3 flagship products and clear customer personas. It thrives on simple decision-making environments where customers know exactly what they want.
The reality? Most small stores don't fit this profile. If you have a diverse catalog, seasonal products, or customers who need time to browse and compare, Performance Max can actually work against you. The automation assumes a level of purchase intent that might not exist for your specific products or market.
What's really happening is that Google is optimizing for their metrics (clicks and conversions) rather than your business metrics (profit and customer lifetime value). The algorithm doesn't understand your margins, your seasonality, or your customer journey complexity.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
My client came to me after struggling with Facebook Ads. They were running a B2C Shopify store with over 1,000 SKUs—everything from home goods to electronics to seasonal items. Their Facebook ROAS was sitting at 2.5, which looked decent on paper, but with their thin margins, it wasn't sustainable.
"Everyone's saying Performance Max is the future," they told me. "Our competitors are using it, and Google keeps pushing it in our account." The promise was tempting: one campaign to rule them all, automatic optimization across every Google property, and supposedly better results than manual campaigns.
We had a few things working against us from the start, though I didn't realize it then:
Catalog complexity: Over 1,000 products across multiple categories
Customer behavior: People needed time to browse, compare, and discover the right product
Purchase intent: Many visitors were in research mode, not ready to buy immediately
Seasonal variations: Different products performed better at different times of year
But Google's case studies showed amazing results, and the client was eager to try something new. So we set up a Performance Max campaign with their full product feed, carefully crafted ad creative, and let Google's machine learning do its thing.
The first month looked promising—we were getting clicks and some conversions. But as we dug deeper into the data, red flags started appearing. The algorithm was heavily favoring a small subset of products, ignoring 80% of the catalog. Worse, it was optimizing for easy wins rather than profitable sales.
By month three, we realized we had a fundamental mismatch: Performance Max demands instant decisions, but our catalog strength was discovery and variety. We were forcing a square peg into a round hole.
Here's my playbook
What I ended up doing and the results.
After the Performance Max experiment failed to deliver, I had to step back and think about what our client's catalog actually needed. The truth hit me: their strength wasn't in quick purchasing decisions—it was in product discovery and choice.
Instead of fighting against their catalog's nature, we decided to embrace it. Here's the complete strategy we implemented:
Step 1: The Channel-Product Fit Analysis
I analyzed which products were actually converting through paid ads versus organic search. The pattern was clear: simple, well-known products worked on ads, but their unique and varied inventory performed better when people had time to browse and discover.
Step 2: Complete SEO Overhaul
We completely restructured their website with SEO as the primary focus. Instead of thinking homepage-first, we made every product page a potential entry point. This meant:
Optimizing individual product pages for long-tail keywords
Creating collection pages that targeted specific search intents
Building content around product discovery and comparison
Step 3: AI-Powered Content Generation
With over 1,000 products, manual optimization wasn't feasible. We built an AI workflow that generated unique, SEO-optimized content for each product page while maintaining quality and relevance.
Step 4: The Discovery-First Homepage
We did something unconventional: turned the homepage into a product gallery. Instead of traditional sections like "Featured Products" or "Our Collections," we displayed 48 products directly on the homepage with just a testimonials section below.
Step 5: Multi-Channel Distribution
Rather than relying on one paid channel, we built a comprehensive organic distribution system that included SEO, content marketing, and strategic partnerships.
The key insight was this: you can't change the rules of a marketing channel, you can only control how your product plays within those rules. Performance Max has its physics—it rewards instant decisions and clear intent. Our catalog thrived on patient discovery and choice.
Product-Channel Fit
Performance Max works for 1-3 flagship products with clear purchase intent. Complex catalogs need discovery-focused channels.
Discovery Over Decision
We redesigned the homepage to showcase 48 products directly instead of traditional sections, doubling conversion rates.
AI-Powered Scale
Used AI workflows to generate unique SEO content for 1,000+ products, making manual optimization feasible at scale.
Organic Distribution
Built comprehensive SEO and content strategy that outperformed any paid channel we tested for catalog complexity.
The results spoke for themselves, though they took longer to materialize than paid ads:
Homepage conversion rate doubled after the product gallery redesign
Organic traffic became the primary driver of qualified visitors who actually converted
Customer behavior improved: visitors spent more time browsing and discovered products they wouldn't have found through ads
Cost per acquisition dropped significantly since organic traffic was essentially free
But the most important result was understanding that product-channel fit matters more than campaign optimization. No amount of bidding strategy or creative testing could fix the fundamental mismatch between Performance Max's instant-decision environment and our client's discovery-based catalog.
The client learned to stop chasing every new advertising platform and instead focus on channels that aligned with how their customers actually wanted to shop. Sometimes the best marketing strategy is knowing when to say no to what everyone else is doing.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
Product-channel fit is everything. Performance Max works for simple decision environments, not complex catalogs that require discovery.
Don't force your business model into popular channels. If your strength is variety and choice, embrace discovery-focused strategies instead.
Automation isn't always better. Sometimes manual control and strategic thinking outperform algorithmic optimization.
Organic can outperform paid for complex catalogs. When customers need time to browse and compare, SEO often delivers better-qualified traffic than ads.
Homepage design matters for discovery. Showing products directly instead of traditional sections can dramatically improve conversion rates.
AI can solve scale problems. Use automation for content generation and optimization, not just advertising.
Test channel fit before campaign optimization. Get the strategy right before worrying about tactics.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
Focus on organic growth and SEO for complex product catalogs
Use Performance Max only for 1-3 flagship products with clear purchase intent
Build discovery-focused user experiences over conversion-optimized funnels
For your Ecommerce store
Turn homepage into product gallery for catalogs with 100+ SKUs
Implement AI-powered content generation for large product catalogs
Prioritize SEO over paid ads for discovery-based shopping experiences