Case Study: Luxury Retail Achieves 400% ROAS with Performance Max
How strategic segmentation and expert optimisation delivered 45% revenue growth
ROAS Achieved
Revenue Increase
CPA Reduction
The Client
Industry: Luxury leather goods and accessories
Location: United Kingdom
Product Range: Premium leather diaries, wallets, bags, and accessories (£50-£500 price range)
Previous Google Ads Experience: Running Standard Shopping campaigns with in-house management
Monthly Ad Spend: £18,000-£25,000
The Challenge
Primary Goal: Scale Google Ads revenue while maintaining profitability in a highly competitive luxury market with strong established brands.
Specific Pain Points
1. Inconsistent ROAS Across Products
The client’s previous Standard Shopping campaigns treated all products equally. High-margin leather diaries (60% margin) competed for budget with low-margin wallets (30% margin). This meant profitable products were underfunded while marginal products wasted spend.
Impact: Overall ROAS stuck at 280%—profitable for some products, break-even for others.
2. Limited Channel Reach
Standard Shopping only appeared on Google Shopping and Search. The client wanted to expand into Display and YouTube but lacked video creative and expertise in multi-channel campaigns.
Impact: Missing opportunities to reach customers earlier in the buying journey.
3. Seasonal Demand Management
Demand spiked around Christmas, Valentine’s Day, and back-to-school periods. Manual budget adjustments were too slow—by the time they increased budgets, peak demand had passed.
Impact: Lost revenue during key selling periods due to budget constraints.
4. Creative Asset Limitations
Product photography was excellent, but the client had no video content and limited ad copy variations. Standard Shopping didn’t require extensive creative, but Performance Max would need comprehensive assets.
Impact: Barrier to adopting Performance Max without creative investment.
The Strategy
Phase 1: Campaign Architecture (Weeks 1-2)
I designed a 3-campaign Performance Max structure segmented by product margin profile:
✓ Campaign 1: High-Margin Products (60%+ margin)
Products: Premium leather diaries, luxury wallets, bespoke items
ROAS Target: 350% (allowing aggressive scaling)
Budget Allocation: 50% of total budget
Strategy: Capture maximum volume at profitable ROAS
✓ Campaign 2: Medium-Margin Products (40-60% margin)
Products: Mid-range accessories, card holders, smaller bags
ROAS Target: 400% (balanced profitability)
Budget Allocation: 35% of total budget
Strategy: Steady growth with profitability focus
✓ Campaign 3: Lower-Margin Products (30-40% margin)
Products: Entry-level products, sale items
ROAS Target: 500% (strict profitability control)
Budget Allocation: 15% of total budget
Strategy: Customer acquisition focus (lead to higher-margin purchases)
Phase 2: Asset Creation (Weeks 2-3)
Performance Max requires comprehensive creative assets. I worked with the client to develop:
- 15 headlines: Mix of product-focused, benefit-driven, and seasonal messaging
- 5 descriptions: Emphasising British craftsmanship, quality, and gift appeal
- 20+ images: Product shots, lifestyle images, close-ups across all aspect ratios
- 8 videos: 6-second bumpers (craftsmanship close-ups) and 30-second product showcases
- Logo variants: Square and landscape formats
Video Content Strategy: Instead of expensive production, I guided the client to create simple iPhone videos showcasing leather texture, stitching details, and product unboxing. Authenticity over polish for YouTube.
Phase 3: Audience Signal Development (Week 3)
Performance Max uses audience signals to guide Google’s AI. I built signals using:
- First-party data: Website visitors, past purchasers, email subscribers
- Demographics: Targeting professionals aged 30-55, higher income brackets
- Interests: Luxury goods, fashion accessories, business professionals
- Competitor audiences: Targeting customers of similar luxury brands
Phase 4: Launch & Learning (Weeks 4-7)
Staggered campaign launches to manage learning phase:
- Week 4: High-margin campaign (largest budget, fastest learning)
- Week 5: Medium-margin campaign
- Week 6: Lower-margin campaign
- Week 7: Monitor all three campaigns, minor tweaks only
The Results
Overall Performance (8 Weeks Post-Launch)
Overall ROAS
Previous ROAS
ROAS Improvement
💰 Revenue Impact
- 45% increase in total revenue vs previous 3-month period
- 38% higher average order value (£185 vs £134) due to better-qualified traffic
- £67,000 additional revenue in first 8 weeks
📊 Efficiency Improvements
- 28% reduction in cost per acquisition (£38 vs £53)
- 35% improvement in conversion rate (3.8% vs 2.8%)
- 22% lower cost per click despite competitive market
🎯 Channel Performance Breakdown
Using my custom Performance Max channel disaggregation tools, I tracked where results came from:
- Shopping: 42% of conversions, 450% ROAS (top performer)
- Search: 28% of conversions, 380% ROAS (high-intent queries)
- YouTube: 18% of conversions, 320% ROAS (incremental reach)
- Display: 8% of conversions, 280% ROAS (remarketing focus)
- Gmail: 4% of conversions, 340% ROAS (seasonal promotions)
Key Insight: YouTube delivered 18% of conversions—entirely incremental revenue that Standard Shopping never reached.
📈 Campaign-Level Performance
- High-Margin Campaign: 420% ROAS, scaled to 55% of budget (from 50%)
- Medium-Margin Campaign: 395% ROAS, maintained at 35% of budget
- Lower-Margin Campaign: 340% ROAS, reduced to 10% of budget (strict control)
Key Insight: Budget flowed automatically to the most profitable products without manual intervention.
Key Success Factors
1. Margin-Based Segmentation
Separating products by margin profile allowed tailored ROAS targets. High-margin products could scale aggressively; low-margin products stayed profitable with strict controls. This single decision drove most of the ROAS improvement.
2. Comprehensive Asset Library
15 headlines and 8 videos gave Google’s AI plenty of creative options to test. The more assets provided, the better Performance Max performs. Simple iPhone videos worked as well as expensive production.
3. Patient Learning Phase
Resisting the urge to make changes during weeks 4-7 allowed Google’s algorithm to learn effectively. Many advertisers panic and make premature changes, restarting the learning process.
4. Channel-Level Transparency
My custom reporting revealed that YouTube was delivering 18% of conversions—validating the multi-channel approach. Without this insight, the client might have assumed all results came from Shopping and missed the value of video.
5. First-Party Data Utilisation
Using the client’s customer list and website visitor data as audience signals helped Performance Max find similar high-value customers faster than relying on Google’s cold-start algorithm.
Client Testimonial
“We were sceptical about Performance Max after hearing mixed reviews from other businesses. Peter’s approach—especially the margin-based segmentation—made complete sense. The results speak for themselves: 400% ROAS and 45% revenue growth in just two months. What impressed us most was the transparency. Peter’s custom reporting showed us exactly where our budget was going and what was working. We now have a scalable, profitable Google Ads system instead of constantly firefighting campaign performance.”
— Marketing Director, Luxury Leather Goods Brand
Ongoing Optimisation (Months 3-6)
After the initial success, I continued refining the campaigns:
Seasonal Scaling
- Increased budgets 2.5x for Christmas period (November-December)
- Maintained 385% ROAS during peak season despite aggressive scaling
- Generated £245,000 revenue in Q4 (vs £168,000 previous year)
Creative Refresh
- Added seasonal headlines (Christmas gifts, Valentine’s Day)
- Created 6 new product videos showcasing gift packaging
- Performance Max automatically promoted top-performing assets
Audience Expansion
- Added lookalike audiences based on high-value customers
- Tested new interest categories (corporate gifting, luxury travel)
- Discovered untapped audience segment: business professionals buying gifts
Competitive Monitoring
- Monthly auction insights analysis to track competitor activity
- Identified when competitors increased budgets during peak seasons
- Adjusted bidding strategy to maintain position without overspending
Lessons Learned
📚 What Worked
- Margin-based segmentation: Single biggest driver of ROAS improvement
- Simple video content: iPhone videos performed as well as professional production
- Patient learning phase: Letting Google’s AI learn without interference
- Channel diversity: YouTube delivered 18% of conversions (entirely incremental)
- First-party data: Customer lists accelerated performance
⚠️ What Didn’t Work Initially
- Generic headlines: Initial batch was too product-focused; benefit-driven headlines performed better
- Overly conservative ROAS targets: Started with 450% target for high-margin products; lowering to 350% unlocked more volume profitably
- Limited audience signals: Week 1 used only website visitors; adding customer list data improved performance by 20%
Why This Case Study Matters
This isn’t a “lucky result” or one-off success. The strategies used here apply to any e-commerce business with:
- Product catalogue with varying margins
- Desire to expand beyond Shopping into Display and YouTube
- Need for automated budget management across products
- Seasonal demand fluctuations
- Competitive market requiring smart positioning
The key is strategic segmentation and expert management—not just “turning on Performance Max and hoping for the best.”
Could Your Business Achieve Similar Results?
If you’re running Google Ads for e-commerce and want to scale profitably with Performance Max, let’s talk. I’ll review your current setup and show you exactly what’s possible.
✓ 20+ Years Google Ads Experience
✓ UK-Based & UK-Focused
✓ Performance Max Specialist
✓ 400% Average ROAS