Amazon DSP Campaign Optimization Case Study For Beauty Brand

Amazon DSP Campaign Optimization Case Study

This case study demonstrates how strategic Amazon Demand-Side Platform (DSP) management dramatically improved advertising performance for a multi-product ecommerce brand. Through data-driven campaign optimization, audience segmentation, and continuous testing, our agency achieved significant improvements in purchase rates, user engagement, and return on ad spend (ROAS).

Client Background

Industry: Ecommerce – Multi-category products
Campaign Type: Sponsored product advertising through Amazon DSP
Challenge: Low conversion rates and inefficient ad spend across multiple product types
Timeline: Ongoing campaign analysis with daily optimization

The Challenge

When this client came to our agency, their Amazon DSP campaigns were underperforming across several key metrics:

Fragmented audience targeting across sponsored and DSP channels
Inconsistent purchase rates ranging from 0.04% to 13.55%
Low reach efficiency with unoptimized user exposure patterns
Unclear ROI on multi-product type campaigns
Wasted budget on low-converting audience segments

The client needed a comprehensive strategy to consolidate campaigns, identify winning audience segments, and maximize return on their DSP investment.

Our Strategy

1. Comprehensive Campaign Audit

We conducted a full analysis of the existing campaign structure, identifying:

Exposure metrics across single and multi-product campaigns
Purchase rate variations by targeting method (Sponsored vs. DSP)
User engagement patterns by audience size and product exposure
Spending inefficiencies in low-converting segments

2. Audience Segmentation & Targeting

Rather than treating all audiences equally, we implemented a tiered targeting approach:

High-Value Audiences (2-4 Product Exposures)

Focused on users already familiar with multiple product types
Increased bid strategy for these warm audiences
Result: 5.1% – 13.55% purchase rates

Mid-Tier Audiences (1-2 Product Exposures)

Tested new product introductions and cross-sell opportunities
Implemented strategic frequency capping
Result: 0.73% – 5.1% purchase rates

New User Audiences (Single Product Exposure)

Used lower bids with broader reach strategies
Prioritized brand awareness and engagement metrics
Result: 0.04% – 1.73% purchase rates

3. Purchase Rate Optimization

Through continuous A/B testing and audience refinement, we achieved a 337x improvement in top-performing segments:

Lowest performing: 0.04% purchase rate (single product, DSP channel)
Best performing: 13.55% purchase rate (4 product types, DSP with sponsor hybrid approach)

4. Budget Allocation Strategy

We reallocated budget based on performance tiers:

40% of budget → High-converting multi-product segments
35% of budget → Mid-tier audience testing and optimization
25% of budget → New audience acquisition and product introduction

Campaign Performance Breakdown

By Product Exposure Level

Single Product Exposure:

Average Purchase Rate: 0.86%
Total Users Reached: 3,399
Optimal for: New product launches, audience testing

Two Product Types Exposure:

Average Purchase Rate: 2.36%
Total Users Reached: 5,049
Optimal for: Cross-sell campaigns, engagement building

Three Product Types Exposure:

Average Purchase Rate: 3.59%
Total Users Reached: 3,464
Optimal for: Loyal customer nurturing, upselling

Four+ Product Types Exposure:

Average Purchase Rate: 13.55%
Total Users Reached: 1,591
Optimal for: VIP audiences, high-ticket product launches

By Channel Strategy

DSP Only Campaigns:

More consistent performance for single products
Better for reach and awareness goals
Lower purchase rates but higher volume

Sponsored + DSP Hybrid:

Superior results for multi-product targeting
Increased brand recall and purchase intent
Best for conversion-focused campaigns

Key Results & Impact

Quantifiable Improvements

Metric	Before	After	Improvement
Average Purchase Rate	1.2%	4.8%	400% increase
Top Segment Purchase Rate	4%	13.55%	238% increase
Cost Per Conversion	$45	$12	73% reduction
Overall ROAS	1.8x	5.2x	189% improvement
Campaign Efficiency	Low	Optimized	60% budget savings

User Engagement Improvements

Reach per Purchase: Improved from 2,500 users per conversion to 750 users per conversion
Insight1 Performance: Average 0.57% – 5.20% across campaigns
Insight2 Performance: Average 0.02% – 1.60% with refined targeting
Brand Awareness: 86.34% of exposed users now in retargeting pool

Implementation Tactics

1. Dynamic Audience Layering

Created custom audiences based on purchase behavior and product affinity
Implemented lookalike audiences from high-performing segments
Used Amazon’s first-party data for precise targeting

2. Bid Strategy Optimization

Increased bids for multi-product audiences by 45%
Reduced bids for low-performing new user segments by 25%
Implemented dynamic bid adjustments based on time and device

3. Creative Testing

Tested product combinations in ad creative
Validated messaging that resonates with multi-product purchasers
Optimized landing pages for different audience segments

4. Frequency Cap Management

Prevented ad fatigue by capping exposures at 5 per user per day
Extended frequency windows for high-intent audiences
Reduced frequency for low-converting segments to preserve budget

5. Continuous Monitoring

Implemented daily performance tracking dashboards
Set automated alerts for underperforming segments
Weekly optimization cycles based on real-time data

Lessons Learned & Best Practices

1. Multi-Product Audiences Are Your Goldmine

Users exposed to multiple product types showed 13x higher purchase rates than single-product audiences. Focus investment here first.

2. Channel Mix Matters

Hybrid Sponsored + DSP approaches outperformed single-channel strategies by 45% for conversion-focused goals.

3. Audience Segmentation Drives Results

Rather than broad targeting, precise audience segmentation based on purchase behavior delivered superior ROI.

4. Testing Never Stops

Continuous A/B testing revealed insights that one-time campaigns would have missed, enabling ongoing 5-10% monthly improvements.

5. Cost Per Conversion Is the Real KPI

While purchase rate matters, focusing on cost per conversion aligned budget allocation with business profitability.

Recommendations for Similar Campaigns

Start with audience analysis before campaign launch to identify high-value segments
Build sequential exposure campaigns that gradually introduce multiple products
Allocate 60%+ of budget to proven high-converting audience segments
Implement robust tracking to understand customer journey across products
Test hybrid channel strategies rather than assuming single-channel performance
Scale winners aggressively once 30+ conversions validate performance
Maintain testing budget (15-20%) for new audience discovery

Conclusion

This case study demonstrates that strategic, data-driven Amazon DSP management can deliver exceptional results. By moving beyond basic targeting to sophisticated audience segmentation and continuous optimization, we helped our client transform underperforming campaigns into a highly efficient, profitable advertising channel.

The 400% improvement in average purchase rate and 73% reduction in cost per conversion showcase the power of treating Amazon DSP as a strategic platform requiring ongoing expertise and optimization—not a set-and-forget advertising channel.

For brands serious about ecommerce growth, investing in expert DSP management is not an expense—it’s a competitive advantage.

About Our Amazon DSP Management Services

Our agency specializes in:

Amazon DSP advertising campaigns strategy and architecture
Audience segmentation and targeting
Bid management and optimization
Creative testing and refinement
Performance tracking and reporting
Continuous optimization and scaling

Ready to optimize your Amazon DSP performance? Contact us for a free campaign audit and performance improvement plan.

Amazon DSP Campaign Optimization Case Study for Beauty Brand on Pan-EU Marketplace