Last updated: February 2026
For years, the gold standard in ecommerce advertising was granularity. More campaigns. More ad groups. More exact match keywords. More control. The logic made sense: the more precisely you could target, the better your results.
Google is now telling us that era is over.
In a recent episode of Google's Ads Decoded podcast, Brandon Ervin, Director of Product Management for Search Ads, made it clear: elaborate multi-layered campaign structures may actually be holding advertisers back in the AI era. This isn't just Google PR — it's a fundamental shift in how their algorithms work best.
For ecommerce advertisers running Performance Max and Shopping campaigns, this raises some uncomfortable questions. Have you been over-engineering your account structure? Is your quest for control actually hurting performance?
Here's what simplified campaign structures actually mean for your business — and how to streamline without losing the control that matters.
Why Google Is Pushing Simplification
Let's understand what's driving this shift. Google's AI-powered advertising tools — Performance Max, AI Max for Search, and Smart Bidding — are fundamentally different from the rule-based systems they replaced.
The Old Model: Human Precision
In the pre-AI era, Google's algorithm needed explicit instructions:
- Keywords told Google what to target
- Bids told Google how much to pay
- Campaigns segmented traffic so you could control budgets and strategies
- Granularity = control, and control = performance
Sophisticated advertisers built complex structures because the algorithm was relatively dumb. Your job was to think of every possible query variation, set appropriate bids, and segment meticulously.
The New Model: AI Prediction
Today's AI-powered campaigns work differently:
- Machine learning predicts conversion probability in real-time
- Automation adjusts bids dynamically based on thousands of signals
- Cross-channel optimization finds conversions wherever they are
- Consolidation = data, and data = performance
The AI needs volume to learn. When you fragment your campaigns into dozens of tiny segments, you starve each one of the conversion data it needs to optimize effectively.
The 30-Conversion Threshold
Here's the practical reality: Google recommends at least 30 conversions per month per campaign for optimal machine learning performance. For PMax campaigns, some practitioners report needing even more — 50-100 conversions monthly for consistent optimization.
Do the math on your current structure. If you're running 10 campaigns with a total of 100 monthly conversions, that's only 10 conversions per campaign on average. You're making Google's AI fly blind.
What "Simplified Structure" Actually Means
Let's be clear about what Google is (and isn't) suggesting:
What Google Wants
- Fewer campaigns with larger budgets and more conversion data
- Broader targeting to let AI find opportunities you'd miss manually
- Consolidated asset groups where logical (not fragmented micro-segments)
- Trust in automation for bidding and placement decisions
What Google Doesn't Mean
- One campaign for everything (that's oversimplification)
- No segmentation at all (business logic still matters)
- Abandoning control (you still guide the AI with signals and constraints)
- Ignoring performance data (segment intelligently, not arbitrarily)
The goal is strategic simplification, not mindless consolidation.
The Case for Consolidation: Real Benefits
Before we get into how to simplify, let's acknowledge the genuine benefits:
1. Faster Learning
More conversions per campaign means faster exit from the learning phase. A campaign with 100 monthly conversions will optimize much faster than one with 15.
2. Better Auction Insights
Google's AI can only optimize against data it has. When conversions are scattered across campaigns, the algorithm can't see patterns that emerge at scale.
3. Budget Efficiency
Consolidated budgets eliminate the "one campaign is capped while another has unspent budget" problem. AI can reallocate spend to wherever conversions are cheapest.
4. Less Management Overhead
Fewer campaigns means less time spent on structure decisions and more time on strategy, creative, and customer experience.
5. Cross-Segment Learnings
When products are in the same campaign, learnings from one can inform optimization for others. A consolidated campaign understands that someone who bought shoes might want socks.
The Case Against Over-Consolidation: Where Control Still Matters
Now here's where the "just consolidate everything" advice falls apart for sophisticated ecommerce advertisers:
Different Products Have Different Margins
A 60% margin product and a 15% margin product shouldn't share the same ROAS target. If they're in the same campaign with a single tROAS, you'll either:
- Under-bid on high-margin products (leaving profit on the table)
- Over-bid on low-margin products (buying unprofitable conversions)
Different Categories Have Different Seasonality
Your swimwear and your winter coats shouldn't compete for the same budget in January. Consolidation makes seasonal budget shifts harder to manage.
Different Product Lines Have Different Goals
Are you trying to maximize profit on established products while growing market share on new launches? Those objectives require different strategies, not unified optimization.
Some Products Deserve Priority
Your bestsellers (Cash Cows) shouldn't compete for impressions with your underperformers (Dogs). Consolidation without smart segmentation can drag down your winners.
The Balanced Approach: Strategic Segmentation for Ecommerce
Here's the framework I recommend for ecommerce advertisers trying to simplify without sacrificing control:
Segment by Business Objective, Not by Product
Instead of creating campaigns for every category, segment by what you're trying to achieve:
Campaign 1: Profit Maximization (High-Margin Products)
- Products: Cash Cows and high-margin Contenders
- Goal: Maximum efficiency, conservative tROAS
- Budget: Flexible, uncapped where profitable
Campaign 2: Growth & Scale (Volume Products)
- Products: Contenders and high-potential Stars
- Goal: Acquire customers, acceptable efficiency
- Budget: Growth-oriented allocation
Campaign 3: Testing & Evaluation
- Products: New launches, Stars under review
- Goal: Gather data, prove viability
- Budget: Controlled test spend
Campaign 4: Catch-All / Long Tail
- Products: Everything else that still converts
- Goal: Capture incremental conversions efficiently
- Budget: Minimal, high-efficiency target
This is 4 campaigns instead of 20, but with clear strategic logic.
Use Asset Groups for Product Segmentation Within Campaigns
Within each campaign, asset groups provide the product-level segmentation you need:
Example: Profit Maximization Campaign
- Asset Group 1: Electronics (high-margin accessories)
- Asset Group 2: Premium Apparel (full-price items)
- Asset Group 3: Home & Garden (best sellers)
Each asset group has tailored creative, but they share a campaign budget and optimization goal.
Let Performance Data Drive Structure
Here's where tools like DukesMatrix become essential. Instead of guessing which products belong where, let data decide:
- Classify your entire catalogue by revenue contribution and performance
- Identify your Cash Cows, Contenders, Stars, Dogs, and Zombies automatically
- Segment campaigns based on actual performance, not assumptions
- Update classifications dynamically as performance changes
Performance-based segmentation ensures your campaign structure reflects reality, not organizational charts.
Practical Implementation: Simplifying Your Current Structure
If you're currently running a complex account structure, here's how to simplify strategically:
Step 1: Audit Your Current State
Pull a campaign report for the last 90 days:
- How many campaigns are you running?
- How many conversions does each campaign get monthly?
- Which campaigns have overlapping products or audiences?
- Which campaigns have similar ROAS targets?
Identify campaigns with fewer than 30 monthly conversions — they're candidates for consolidation.
Step 2: Identify Consolidation Opportunities
Look for campaigns that can merge:
- Same ROAS target? Consider combining
- Same product category? Consider combining
- Both underperforming? Definitely combine or pause
- Both successful with similar margins? Consider combining
Step 3: Preserve Strategic Separation
Keep campaigns separate when:
- Margin differences exceed 20% (different tROAS needed)
- Seasonality is inverse (budget allocation matters)
- Brand vs. Non-Brand (for search campaigns)
- Strategic priority differs (growth vs. profit)
Step 4: Consolidate and Monitor
When combining campaigns:
- Export current settings for rollback if needed
- Combine listing groups into the surviving campaign
- Adjust budget to equal the sum of merged campaigns
- Set tROAS based on the weighted average target
- Monitor closely for 2-3 weeks during learning phase
- Compare performance to baseline (combined historical data)
Step 5: Review Quarterly
Your structure should evolve as your business does:
- Products move between performance tiers
- New categories launch
- Seasonality shifts budget priorities
- Performance data reveals new patterns
Schedule quarterly reviews to evaluate whether your structure still makes sense.
AI Max for Search: The Future of Simplification
Google's AI Max for Search represents where this simplification trend is heading. Key features:
Expanded Reach
AI Max automatically expands targeting beyond your keywords to reach queries you haven't thought of. Google reports it's unlocking billions of net-new searches that advertisers weren't reaching before.
Automated Creative
AI generates and tests ad variations automatically, reducing the need for granular ad group structures based on creative testing.
Unified Optimization
Instead of optimizing each ad group independently, AI Max optimizes across your entire campaign for overall performance.
What This Means for Ecommerce
For search campaigns specifically, AI Max suggests the future is:
- Fewer, broader campaigns with AI expansion
- Less keyword granularity (AI finds the queries)
- More focus on creative quality over structural complexity
- Greater reliance on signals (audience, context) over keywords
How DukesMatrix Supports Smart Simplification
Performance-based product segmentation is the key to simplifying without losing control:
Automatic Classification
DukesMatrix analyzes your catalogue and automatically classifies products into:
- Cash Cows: Top revenue performers (protect and maximize)
- Contenders: Strong performers with growth potential (invest to scale)
- Stars: Middle tier with uncertain trajectory (test and evaluate)
- Dogs: Underperformers dragging down ROAS (minimize or exclude)
- Zombies: Zero-converters wasting impressions (exclude immediately)
Custom Label Sync
Classifications sync directly to Merchant Center as custom labels, enabling:
- Simplified campaign structure (4-5 campaigns based on performance tier)
- Dynamic segmentation (products move as performance changes)
- Strategic budget allocation (prioritize proven winners)
Data-Driven Decisions
Instead of guessing how to segment, DukesMatrix tells you:
- Which products justify premium campaign placement
- Which products should be consolidated
- Which products to exclude from paid campaigns entirely
Common Mistakes When Simplifying
Mistake 1: Consolidating Everything Into One Campaign
Over-consolidation is just as bad as over-fragmentation. One campaign with a single tROAS target can't account for margin differences across your catalogue.
Fix: Maintain 3-5 campaigns based on strategic objectives.
Mistake 2: Ignoring the Learning Phase
When you consolidate, the surviving campaign enters a learning phase. Performance may dip temporarily as the algorithm recalibrates.
Fix: Allow 2-3 weeks before judging consolidated performance.
Mistake 3: Not Updating Your Structure
A structure that made sense 6 months ago may not make sense today. Products move between performance tiers, and your structure should reflect that.
Fix: Schedule quarterly structure reviews tied to performance data.
Mistake 4: Simplifying Without Data
Consolidating campaigns without understanding which products are winning is gambling. You might merge a high-performer with a drag.
Fix: Use performance segmentation tools before restructuring.
FAQs: Simplified Campaign Structures
How many campaigns should I run for ecommerce?
Most successful ecommerce advertisers with 500+ SKUs run 3-7 campaigns, segmented by business objective (profit vs. growth) or margin tier. Fewer than $10K monthly spend may benefit from consolidation into 1-3 campaigns.
Will simplifying hurt my performance?
Initially, you may see fluctuations during the learning phase. Long-term, consolidated campaigns typically perform better due to improved data density and cross-product learnings.
How do I simplify without losing control?
Segment by business objective rather than product category. Use asset groups for creative differentiation within campaigns. Let performance data (not assumptions) guide segmentation decisions.
Does this apply to Shopping campaigns too?
Yes. Standard Shopping campaigns can also benefit from consolidation, though many advertisers are migrating to Performance Max which inherently encourages broader structures.
What about brand campaigns?
Brand campaigns typically remain separate due to different economics (high conversion rate, low CPC). Don't consolidate brand with non-brand unless you have a specific reason.
How often should I review my structure?
Quarterly is recommended. Products move between performance tiers, seasonality shifts, and business priorities evolve. Your structure should keep pace.
Key Takeaways
Google is pushing simplified structures because AI needs data to learn. Fragmented campaigns starve the algorithm of the conversion volume it needs.
Strategic simplification ≠ mindless consolidation. You still need separation for different margins, objectives, and priorities.
Aim for 30+ conversions per campaign monthly to ensure proper optimization. Audit your current structure against this threshold.
Segment by business objective, not product category. Profit maximization, growth, and testing deserve separate campaigns.
Use asset groups for creative differentiation within consolidated campaigns instead of creating separate campaigns.
Let performance data guide structure decisions. Tools like DukesMatrix automatically classify products so you know which belong together.
Review your structure quarterly to ensure it still reflects your business reality and performance patterns.
Trust the AI, but verify. Simplification works best when combined with strong performance monitoring and willingness to adjust.
Ready to simplify your campaign structure with performance-based segmentation? See how DukesMatrix automatically classifies your products into Cash Cows, Contenders, Stars, Dogs, and Zombies — so you know exactly how to structure your campaigns.