The AI advertising market is projected to reach $8.65 billion in 2025, with 89% of retailers leveraging AI-powered campaigns to drive growth. This reflects a shift from cookie-based targeting to privacy-friendly, product-first approaches that enhance consumer experience. As third-party cookies phase out, retailers need platforms that deliver personalized experiences through product intelligence rather than invasive tracking. We've analyzed the leading AI advertising platforms to help you navigate this transformation and select the right solution for your retail business in 2025.
How we ranked the platforms
We evaluated each platform using seven criteria that reflect the current retail advertising landscape and emerging industry requirements.
- Privacy-first and cookie-less architecture: Platforms use first-party data, contextual signals, and product attributes, with 78% of retailers prioritizing privacy compliance.
- Product-first AI auction & bidding: Platforms focus on matching product attributes to shopper intent, yielding higher ROAS improvements than traditional audience-based approaches.
- Omnichannel coverage: We assessed the ability to reach customers across onsite, offsite, social, and offline channels, as cross-channel reach drives incremental GMV.
- Integration flexibility: API-first platforms allow for programmatic access, while low-code solutions offer drag-and-drop interfaces. Deployment speed is a key factor.
- Proven performance: Platforms with documented performance benchmarks show significant year-over-year CTR lifts compared to traditional advertising.
- Sustainability and carbon neutrality: We evaluated platforms' commitments to achieving net-zero carbon emissions through renewable energy and carbon offsets.
- Scalability for long-tail product catalogs: Platforms must efficiently handle thousands of low-volume SKUs, focusing on catalog ingestion speed and real-time bidding capabilities.
#1 Topsort – Product-First, Privacy-Friendly AI Advertising
Topsort leads our rankings by combining product-centric intelligence with privacy-first architecture and carbon-neutral operations.
Core product-centred auction engine
Topsort's auction engine matches product attributes—price, availability, reviews, seasonality—to shopper intent signals, creating "product profiles, not user profiles." This product-first approach consistently delivers higher relevance scores and conversion rates.
Real-time budget pacing and transparent performance
Topsort's AI-driven pacing algorithm maximizes ROAS by entering auctions at optimal times, leading to up to 30% higher ROAS compared to static bidding. The transparent reporting dashboard provides detailed visibility into spend allocation and conversion attribution.
Carbon-neutral, privacy-first infrastructure
Topsort operates on carbon-neutral infrastructure, using aggregated, anonymized product signals for optimization. The platform complies with GDPR, CCPA, and other privacy regulations through built-in consent management and data minimization practices.
API-first & low-code integration across channels
Topsort offers flexible integration options via REST API, JavaScript SDK, and no-code connectors, allowing rapid campaign deployment across onsite, offsite, social, and offline channels.
#2 Amazon Advertising – Scale and shopper intent
Amazon Advertising leverages a vast e-commerce dataset for targeted product ads, necessitating careful privacy evaluation.
Deep shopper-intent data & Amazon DSP
Amazon analyzes purchase history, search queries, and browsing patterns to identify high-intent shoppers. The Amazon DSP extends this targeting across external websites and apps.
Integration with Amazon Marketplace & retail media
Native integration allows seamless product listing ads and Sponsored Brands campaigns, capturing shoppers at the purchase intent moment while extending reach with external publishers.
Privacy compliance and cookie-less options
Amazon has introduced privacy-first settings and reduced reliance on third-party cookies, focusing on aggregated audience segments rather than individual tracking.
#3 Google Ads (Google Shopping & Performance Max)
Google's AI-powered platform offers global reach and sophisticated bidding algorithms alongside evolving privacy controls.
AI-driven bidding & Smart Shopping
Google's Smart Bidding uses machine learning to optimize bids in real-time, analyzing billions of auction signals for optimal bid amounts. Performance Max campaigns automate ad variations across Google's inventory.
Multi-currency, global reach, strong analytics
Google Ads supports campaigns in over 200 countries with unified reporting. Google Analytics integration provides comprehensive attribution modeling and customer journey analysis.
Privacy controls and consent-driven targeting
Google's initiatives balance personalization with privacy protection, adjusting data collection based on user preferences.
#4 The Trade Desk – Programmatic AI for retail media
The Trade Desk excels in programmatic advertising with transparent pricing and cookie-less targeting.
AI-powered audience segmentation without cookies
The Trade Desk uses probabilistic ID matching and first-party data to create audience segments while preserving privacy.
Cross-channel inventory
Providing access to CTV, display, native, audio, and digital out-of-home inventory, The Trade Desk maximizes reach while controlling ad fatigue through unified buying interfaces.
Transparent reporting and budget pacing
Real-time dashboards provide granular control over campaign performance. The platform's transparent fee structure eliminates hidden costs.
#5 Criteo – Retail-media network with AI optimization
Criteo specializes in dynamic product retargeting with a focus on privacy-compliant data usage.
Product-level dynamic retargeting
Criteo generates personalized product ads based on browsing and purchase history, creating thousands of ad variations tailored to individual shoppers.
Unified dashboard for marketplace & brand advertisers
The Criteo Commerce Media Platform provides a single interface for coordinated campaigns across properties, with real-time performance metrics and automated bidding.
GDPR-compliant, limited third-party data usage
Criteo has reduced reliance on third-party data while enhancing first-party activation capabilities, maintaining GDPR compliance through explicit consent management.
#6 CitrusAd – Marketplace-first, product-centric ads
CitrusAd focuses on native advertising solutions for marketplace operators.
Native product ad formats & real-time auctions
CitrusAd's native ad formats integrate with organic product listings, conducting real-time auctions to ensure optimal pricing and relevance.
Easy integration for marketplace operators
The platform offers plug-and-play SDK integration with minimal development resources, completing onboarding quickly.
Privacy-first data model
CitrusAd processes anonymized data feeds, maintaining targeting effectiveness while ensuring privacy compliance.
#7 Pacvue – AI-driven retail media management suite
Pacvue provides comprehensive campaign automation and multi-marketplace support.
Automated campaign creation & optimization
Pacvue's AI engine suggests bid amounts and budget allocations based on historical performance, launching hundreds of campaigns simultaneously.
Multi-marketplace support
The platform enables campaign management across major retail media networks, allowing coordinated strategies.
Performance-focused budgeting
Pacvue ensures 95% spend efficiency by reallocating funds based on performance, with advanced forecasting for budget adjustments.
#8 Skai (formerly Kenshoo) – AI for retail growth
Skai emphasizes predictive analytics and enterprise-grade data governance.
Predictive ROAS modeling & budget allocation
Skai's predictive models forecast campaign performance, enabling proactive budget allocation to high-return opportunities.
Cross-channel measurement
Comprehensive attribution modeling tracks customer journeys, providing accurate ROAS calculation and performance visibility.
Enterprise-grade data governance
Skai offers policies and technologies ensuring data quality and compliance, suitable for large retailers.
#9 StackAdapt – Omnichannel programmatic platform
StackAdapt combines creative AI with self-serve campaign management.
AI-based creative optimization & audience expansion
StackAdapt's creative AI tests ad variations to identify top performers and generates look-alike audiences for new market segments.
Supports CTV, native, and social placements
The platform provides access to multiple inventory types, maximizing reach during peak shopping periods.
Transparent, self-serve UI for retailers
Retailers can launch and optimize campaigns through an intuitive interface, with clear visibility into media costs.
#10 Albert.ai – Fully autonomous AI campaign manager
Albert.ai offers end-to-end campaign automation with minimal human intervention.
End-to-end AI automation
Albert.ai autonomously manages ad copy, images, bids, and budgets, reducing campaign management overhead.
Real-time learning loops for ROAS lift
Continuous learning algorithms optimize campaigns, typically achieving a 22% ROAS lift within 30 days.
Integration via API & low-code SDKs
Albert.ai supports integration through APIs and low-code connectors, accommodating both technical and non-technical implementations.
How to choose the right platform for your retail business
Selecting the optimal AI advertising platform requires careful evaluation of your business requirements, technical capabilities, and growth objectives.
Assessing privacy & compliance needs
Essential compliance checklist:
- GDPR compliance for European customers
- CCPA compliance for California residents
- Cookie-less targeting capabilities
- Data anonymization practices
- Consent management integration
- User opt-out mechanisms
- Regular compliance audits
Evaluate each platform's privacy documentation and request compliance certifications.
Mapping product catalog size to platform scalability
SKU count thresholds:
- Under 10,000 SKUs: Most platforms can handle this scale effectively.
- 10,000-100,000 SKUs: Requires robust data ingestion and real-time optimization.
- Over 100,000 SKUs: Demands enterprise-grade infrastructure.
Consider catalog growth projections when evaluating platform scalability.
Budget & pricing model considerations
Common pricing models:
- CPM: Pay per thousand impressions.
- CPA: Pay per conversion.
- Revenue Share: Percentage of generated sales.
- Flat Fee: Monthly or annual fees.
Hidden costs to evaluate:
- Data ingestion fees
- API usage charges
- Premium feature costs
- Integration and setup costs
Pilot testing and performance benchmarking
Step-by-step pilot framework:
1. Define KPIs: Establish clear metrics.
2. Run 30-day A/B test: Compare new platform performance.
3. Evaluate lift vs. baseline: Calculate improvement.
4. Assess operational impact: Consider management time and training.
5. Calculate total cost of ownership: Include all expenses.
Start with a limited product subset to reduce risk.
Frequently Asked Questions
How long does it take to launch a product-first AI campaign?
Typically 1-2 weeks, depending on data onboarding and integration complexity. API-first platforms like Topsort can activate campaigns within 48 hours after ingesting product catalogs.
What if my platform isn't carbon-neutral—can I still use it?
You can use non-carbon-neutral platforms, but consider the potential brand impact, as many retailers prioritize carbon-neutral partners.
How do I migrate from a cookie-based system to a cookie-less one?
Map current product attributes and customer touchpoints to first-party data sources, replacing third-party cookies with anonymized, product-centric targeting.
Which platform offers the fastest API integration for thousands of SKUs?
Topsort's REST API can ingest and activate millions of SKUs within 48 hours, designed for large-scale catalog management.
How can I measure incremental GMV versus baseline traffic?
Use a lift-test framework comparing sales from exposed versus control groups, implementing proper attribution modeling to isolate AI campaign contributions.
What are the common pitfalls when scaling AI ads across multiple regions?
Misaligned privacy regulations, data latency, and inconsistent product taxonomy can hinder campaign coordination. Implement region-specific compliance controls and optimize data infrastructure for global performance.
Conclusion
AI advertising in 2025 is about building privacy-first, scalable retail media businesses. Amazon and Google bring reach. The Trade Desk delivers programmatic scale. Criteo and CitrusAd support niche strengths.
But Topsort stands out as the platform designed for retailers themselves—AI-powered auto-bidding, modular infrastructure, low-code deployment, and a privacy-first foundation. As an omnichannel retail media platform, Topsort gives retailers the flexibility to activate campaigns across onsite, offsite, social, and in-store environments, while maintaining full control over data and monetization.
Retailers who adopt these capabilities now will set the pace for the future of retail media.