Marketplaces Become Media Companies
Amazon transformed itself from the world’s largest online marketplace into a $56.2 billion advertising business in 2024—growing revenue by 20% year-over-year. The company proved something crucial: access to rich first-party commerce data plus owned media inventory generates higher margins than retail itself.
This shift signals a structural change in global advertising. As cookies phase out, privacy regulations tighten, and performance marketers demand verifiable ROI, retailers and marketplaces emerge as new power players in digital media. Their advantage lies in something traditional ad networks can’t easily replicate.
Granular first-party data: Real purchase histories, not just clicks or browsing signals.
Closed-loop attribution: The ability to connect ad exposure directly to transactions in-platform or even in-store.
Commerce-adjacent surfaces: From sponsored listings on search pages to video and display ads on streaming or partner sites, all tied back to buying intent.
Retail media in the U.S. is expected to grow 20% in 2025, compared to 4.3% for the total ad market. This convergence of commerce, content, and advertising redefines how brands spend their budgets. Marketers increasingly see retail media as a performance channel—where ad dollars translate into measurable sales rather than impressions alone.
Other marketplaces face a clear implication: you’re sitting on a media platform in the making. The same data powering your marketplace logistics and personalization also holds the key to unlocking new high-margin revenue streams and improved outcomes for your merchants and partners.
Building a true media platform isn’t as simple as adding sponsored listings. It requires technology for data unification and ad-serving infrastructure, measurement through privacy-safe attribution models that advertisers trust, and governance protecting consumer trust and preventing channel conflict with merchants.
Amazon’s Edge in Digital Advertising
Amazon’s rise in digital advertising wasn’t an accident. It built an advertising ecosystem uniquely tied to commerce intent and measurable outcomes. Three pillars make this work.
First-Party Purchase Data Creates Closed-Loop Attribution
Amazon became the third-largest retail ad network behind Google and Meta. Unlike traditional ad networks relying on third-party cookies or anonymized browsing signals, Amazon’s advertising engine runs on rich, first-party data—every search, click, and purchase happening within its marketplace.
This data advantage lets Amazon do what few others can: connect ad exposure directly to sales outcomes.
When users click on a sponsored product in search or see a video ad on Prime Video and later complete a purchase on Amazon, the platform ties that conversion back to the original ad impression.
This closed-loop attribution proves particularly valuable in a post-cookie, privacy-regulated era. Marketers want clear evidence that their spend drives incremental revenue.
Platforms like Criteo made strides in retail media attribution, but Amazon’s unmatched scale of buyer behavior data—spanning hundreds of millions of shoppers—remains its ultimate advantage.
Integrated Commerce Across Multiple Properties
Amazon’s edge isn’t just data. It’s the integration of commerce intent with diverse media inventory—allowing advertisers to follow a customer’s journey across discovery, research, and purchase.
Key touchpoints include on-site search and product pages where sponsored listings appear when purchase intent is highest. Display ads within the marketplace reach shoppers while they browse relevant categories. Streaming and entertainment platforms—Prime Video’s ad-supported tier, Amazon Freevee, and Twitch—provide high-reach video inventory connected to commerce audiences.
This combination of media reach and commerce adjacency is increasingly critical. Amazon is one of few players offering both upper-funnel storytelling and bottom-funnel conversion opportunities within one ecosystem.
Ad Formats Built for Purchase Intent
Traditional digital ads often focus on impressions and awareness. Amazon’s formats drive shopping actions directly.
Sponsored Product Listings appear in search results or on product detail pages, matching the shopper’s query and buying mindset.
Sponsored Brands and Display Ads allow storytelling while maintaining strong connections to relevant products.
Retail Video Ads showcase product benefits in short, shoppable videos that often lead directly to a purchase page.
Behind the scenes, Amazon’s measurement tools prioritize incrementality—tracking not just clicks but the actual lift in purchases attributable to the ad spend.
This focus on purchase intent and attributable conversions gives advertisers confidence to shift budgets from less measurable channels.
Amazon’s success shows the future of advertising lies at the intersection of commerce, audience data, and closed-loop measurement. Other marketplaces—regional e-commerce platforms, grocery delivery apps, or niche B2B procurement networks—can replicate parts of this model by building strong first-party data pipelines, integrating media inventory with high-intent commerce touchpoints, and prioritizing ad formats and metrics tied to actual business outcomes.
Amazon didn’t just add ads to its marketplace. It built a media-commerce engine that improves both shopper experience and advertiser ROI.
What Other Platforms Can Learn
Amazon’s advertising success stems from how the company structured its ecosystem to turn commerce signals into measurable media value. These lessons offer a roadmap for other marketplaces and media tech players to capture similar value and future-proof their platforms.
Build a First-Party Data Engine
Amazon’s edge comes from its direct relationship with shoppers. Platforms aspiring to become media players need to treat their commerce or user interaction data as a strategic asset, not just operational information.
Create data pipelines. Collect and harmonize customer signals—searches, purchases, content interactions—across web, app, and offline touchpoints.
Resolve identities properly. Use identity graphs to link first-party data with second-party partner data in a privacy-compliant way. This ensures advertisers can target known audiences without relying on third-party cookies.
Manage consent carefully. Implement strong consent management so customers understand and control how their data gets used—a critical requirement under GDPR, CCPA, and similar laws.
Offer Closed-Loop Measurement
Marketers no longer want to spend on reach or clicks alone. They want proof of incremental business impact. Amazon’s advantage lies in connecting ad exposure with actual purchase outcomes.
Track multiple touchpoints. Credit all meaningful touchpoints across the customer journey—from first ad view to purchase—for a granular understanding of influence.
Model marketing mix. Combine historical data and statistical models to assess channel contributions, even when direct attribution isn’t possible for upper-funnel media.
Run experiments. Use A/B tests and holdout groups to validate model assumptions and provide evidence for incremental lift.
A hybrid of multi-touch attribution, marketing mix modeling, and experimentation delivers both precision and strategic context. This helps CMOs make smarter, ROI-focused budget decisions.
Create Native Ad Placements
Amazon excels by embedding ads at natural decision-making points in the customer journey—moments when intent is highest.
For other platforms, this could mean sponsored listings on search results and category pages—ads that feel like product discovery rather than interruptions. In-checkout or post-purchase placements work well—ad messages on confirmation pages, receipts, or loyalty emails when customers are receptive to complementary offers.
Contextual relevance matters. Place ads within the platform’s natural experience—product carousels or in-app messages—improving engagement without degrading user experience.
Use Smart Technology for Targeting and Pricing
Amazon’s final advantage is machine learning at scale, continuously optimizing ad targeting by matching ads with the right audience segments based on real-time signals and historical behavior. Dynamic bidding adjusts bids in milliseconds to maximize ROI for advertisers while improving yield for platforms. Inventory yield optimization ensures the highest-value ad shows in each placement by predicting conversion likelihood.
Platforms must think like integrated media-commerce businesses. This means harnessing first-party data responsibly, providing transparent, performance-linked measurement, embedding ads seamlessly into customer journeys, and leveraging smart technology to scale targeting and monetization efficiently.
The convergence of these pillars can transform a traditional marketplace into a high-margin media platform—improving outcomes for both advertisers and end-users.
Building Your Commerce Media Stack
To compete with Amazon’s ad engine, a marketplace or retail platform needs more than inventory to sell. It requires a full-fledged commerce-media stack—unifying data, identity, measurement, and monetization to deliver value for merchants and advertisers.
Data Foundation Layer
Your media platform is only as strong as the data it ingests and governs.
Core inputs include:
- First-party signals: search queries, product views, cart events, transaction data, return and refund patterns
- Point-of-sale feeds: in-store sales, loyalty programs, geolocation check-ins
- Partner data: selected second-party collaborations like brand databases or logistics partners
Data collection must be privacy-first and auditable—including explicit user consent, secure data clean rooms, and regional compliance with GDPR and other laws.
Platforms must think like data companies first—enabling seamless, privacy-compliant ingestion that fuels audience insights and measurement.
Identity and Audience Layer
Retail media thrives on knowing who’s buying what—but in a privacy-safe way.
Identity strategy includes:
- Pseudonymous IDs that respect privacy while linking user journeys across web, app, and offline point-of-sale
- Deterministic linking where explicit consent is given—loyalty ID, verified email or phone
- Probabilistic signals in a privacy-preserving clean room for look-alike modeling
Continuously reconcile IDs across sources to maintain a live, consent-honoring audience graph.
A unified, privacy-safe audience graph is the linchpin for personalized advertising and attribution.
Measurement and Attribution Layer
Advertisers won’t invest without evidence of impact.
Unified measurement approach:
- Multi-touch attribution for real-time, digital path analysis
- Experimental holdouts for testing incremental lift—separating correlation from true causation
- Marketing mix modeling for long-term budget optimization across channels
Provide always-on incrementality dashboards so advertisers see what budget truly moves the needle.
Reliable ROI reporting—not just last-click metrics—is critical for sustained advertiser trust and budget growth.
Ad-Serving and Monetization Layer
Once data and identity foundations are in place, operationalize inventory and yield.
Ad products include:
- Sponsored product auctions integrated into search results and category pages
- Display and video placements on high-intent surfaces—product detail pages, carts, checkout
- Dynamic creative optimization for personalization based on context and intent
Demand connectivity: Enable advertisers to access inventory through standard connections, maintaining control of yield and ad quality.
Yield management: Use smart bid and pricing algorithms to optimize revenue while preserving user experience.
Think of your retail media business as a marketplace in itself—with bidding dynamics, transparent pricing, and continuous optimization.
Analytics and Reporting Dashboard
Transparency builds confidence and adoption.
Closed-loop reporting: Offer advertisers full-funnel visibility—from impression and click to add-to-cart, checkout, and repeat purchase.
Performance metrics: Focus on return on ad spend, conversion lift, basket value growth, customer lifetime value—not vanity metrics.
Self-serve tools: Provide merchants with intuitive campaign dashboards, budget recommendations, and automated optimizations.
Empower merchants with the same level of insight and control they expect from top digital ad platforms.
Omnichannel Extensions
The next frontier links digital and physical touchpoints.
In-store activations:
- Drive-to-store campaigns using geo-fenced mobile ads and coupons
- Digital shelf promotions like QR-enabled product media
Connected TV and streaming: Use commerce data to target and measure streaming ad campaigns.
Omnichannel attribution: Tie online exposure to offline purchases for a true view of ROI.
In-store retail media ad spending is expected to grow about 47% in 2025. Retail media is evolving into commerce media, where both online and offline touchpoints feed a single measurement and activation loop.
Challenges You’ll Need to Solve
Becoming a media platform is as much an organizational transformation as a technological one. Platforms face several business, legal, and operational hurdles that can undermine trust with advertisers, sellers, and customers.
Data Privacy and Regulatory Risk
Commerce media relies heavily on first-party shopper data—purchase behavior, browsing patterns, loyalty IDs. Mismanaging that data can lead to legal penalties, reputational damage, and loss of customer trust.
Key challenges:
- Complex global regulations—GDPR in Europe, CCPA/CPRA in the US, DPDP in India
- Ambiguity in how shopper and advertiser data can be combined or shared
- Rising consumer expectations for data transparency and control
Solutions:
Embed privacy safeguards at every stage—from data ingestion to activation. Use clear, plain-language notices on how data is collected, stored, and used for ads. Implement strong consent management platforms giving customers fine-grained control. For data collaboration with advertisers or agencies, use secure environments ensuring data is never directly shared.
Treat privacy not as a compliance hurdle but as a differentiator that builds trust with both shoppers and advertisers.
Measurement Integrity
As budgets shift from traditional channels to commerce media, advertisers demand proof that their investment drives incremental sales, not just cannibalized conversions.
Key challenges:
- Platforms may over-attribute conversions to ads because they control both exposure and checkout data
- Without strong experimentation, it’s difficult to prove causality versus correlation
- Agencies and brands are increasingly skeptical of self-reported “lift”
Solutions:
Use multi-touch attribution for short-term path analysis, backed by marketing mix modeling for long-term budget allocation. Run ongoing holdout or ghost ad experiments to demonstrate true causal lift. Partner with third-party measurement platforms or auditors for credibility. Offer transparent dashboards that clearly separate organic sales from ad-driven ones.
Honest, validated ROI measurement is non-negotiable—platforms that win trust will win spend.
Channel Conflicts and Seller Fairness
One of the most sensitive issues in retail media is ensuring fair competition between the platform’s own brands and third-party sellers.
Key challenges:
- Perception that the platform prioritizes its own private-label brands in auctions or placement
- Large advertisers may dominate auctions, squeezing out smaller sellers
- Lack of transparency in how sponsored rankings are determined
Solutions:
Use transparent, rules-based auctions with clear quality and relevance factors. Offer standardized floor prices and bidding rules for all sellers. Publish clear guidelines on ad eligibility, ranking logic, and use of first-party data. Consider carve-outs or preferential access tiers for SMB sellers to maintain a healthy ecosystem.
Trust in the fairness of the media marketplace is as important as trust in the measurement.
Technical Debt and Integrations
Most marketplaces and retail platforms are not born as media companies. They must retrofit media capabilities on top of legacy commerce systems.
Key challenges:
- Legacy tech can be brittle and slow to integrate with modern ad tech
- Frequent need to connect with external platforms, analytics, and point-of-sale partners
- Complexity multiplies as the platform expands to omnichannel or new ad formats
Solutions:
Prioritize modular, service-oriented development so new ad products can be plugged in easily. Start with a few high-impact surfaces—sponsored search, product pages—before expanding to streaming, connected TV, or in-store screens. Build a vetted network of trusted data, measurement, and ad-serving partners to accelerate capabilities. Use scalable, event-driven data pipelines to avoid bottlenecks as ad demand grows.
A thoughtful, modular approach prevents technical debt and keeps the platform agile as both commerce and media evolve.
The promise of commerce media lies not just in new revenue streams, but in building a trusted, neutral, privacy-safe ecosystem that delivers measurable growth for all participants.
Proactively addressing these challenges positions platforms not as ad sellers but as strategic partners for both shoppers and brands—a foundation for durable competitive advantage.
Real-World Applications
Three common business scenarios highlight the capabilities needed for platforms and how Sphere Media Technologies can play a pivotal role.
Brand Wants Omnichannel Attribution
A large consumer goods brand advertises across a marketplace’s website through sponsored product listings, its own e-commerce site via video ads and search ads, and offline retail channels.
Historically, the brand relied on last-click digital attribution, which ignored in-store impact and over-valued bottom-funnel clicks.
By using a platform powered by Sphere Media, the brand gets a true unified view of performance, proving how upper-funnel channels contribute to sales across both online and physical stores.
How it works:
The platform ingests site video ad exposures and sponsored search impressions. It connects this to in-store point-of-sale data at the SKU level, fed via secure partner APIs. It links customer journeys pseudonymously using an identity graph and consented loyalty data.
The measurement layer combines multi-touch attribution for digital paths with incrementality testing to validate true sales lift. It provides return on ad spend dashboards and conversion lift reports in near real-time.
Expected results:
Increase in attributable offline sales from omnichannel campaigns. Improved budget allocation across upper- and mid-funnel channels. Higher return on ad spend by reducing underperforming placements.
The brand proves that its top-of-funnel media investments actually drive in-store lift, unlocking more budget for the platform.
Retailer Wants to Launch an Ad Network
A mid-sized retail platform with online and physical stores sees the success of Amazon and Walmart’s retail media networks. It wants to monetize its own first-party shopper data and inventory.
It must balance speed to market with the desire for long-term control and profitability.
Two-path approach:
Short-term: Partner with a white-label retail media provider to quickly launch sponsored listings and display inventory. Typical timeline: 3-4 months to go live. Revenue-share model splits earnings between retailer and provider.
Long-term: Over 12-18 months, build proprietary modules for identity resolution, attribution, and yield optimization. This reduces revenue share leakage but requires more upfront investment.
The retailer transitions from a fast-launch approach to a scalable, profitable retail media network, gradually reducing dependence on external vendors while improving margins.
Multi-Location Chain Wants Drive-to-Store Optimization
A regional grocery chain with 400 stores wants to boost in-store foot traffic and sales from nearby shoppers. It needs to ensure ad dollars aren’t wasted on broad, non-actionable impressions.
By combining location intelligence, SKU-level data, and campaign analytics, the chain can target and measure ads that actually influence store visits and purchases.
How it works:
Collect geofencing data—mobile location signals—to identify shoppers near store locations. Match this with SKU-level point-of-sale data to track conversion post-exposure. Integrate creative testing to optimize which ad formats and messages drive actual store visits.
The measurement layer uses incrementality experiments—ghost-ads, holdouts—to separate natural store traffic from ad-driven visits. It provides geo-lift reports to understand campaign effectiveness at the store level.
Expected results:
Drive-to-store lift: percentage increase in incremental visits from campaign-exposed audiences. SKU-level sales lift: net revenue impact tied to campaigns. Optimized local ad spend: reducing waste by focusing on audiences within specific catchment areas.
The chain demonstrates measurable, location-driven ROI. It improves collaboration between brand partners and stores. Budget shifts confidently to channels driving in-store conversion.
Commerce Plus Media Plus Tech Equals Growth
Retail media in the U.S. is expected to grow 20% in 2025, compared to 4.3% for the total ad market. Amazon’s $56.2 billion advertising business in 2024 demonstrates the power of first-party data, integrated media placements, and closed-loop measurement to drive high-margin revenue while improving merchant outcomes.
Platforms that wait risk ceding market share to competitors that can prove incremental lift, optimize ad spend, and personalize buyer journeys across channels.
The move is urgent. Global retail media ad spend grows at double-digit rates annually. Brands increasingly prioritize measurable ROI over reach alone. Advertiser demand for transparency and attribution intensifies. Brands want actionable insights showing how ads convert into sales, both online and in-store. Platforms without media capabilities risk losing these partnerships.
Tech-driven differentiation matters. Integrating commerce and media operations creates a sticky ecosystem, improving merchant retention, audience loyalty, and competitive defensibility.
Platforms that act now can test, learn, and scale retail media capabilities with a trusted partner. Sphere Media Technologies provides end-to-end support—from data engineering and identity resolution, to ad-serving, attribution, and analytics dashboards, to omnichannel retail media integration.
By working with Sphere Media, platform operators can unlock new revenue streams through retail and commerce media, deliver tangible ROI and lift for advertisers, and build future-ready infrastructure that balances growth, measurement, and compliance.
The next era of platform success belongs to those who embrace commerce plus media plus tech together. The time to start building that advantage is now.
Ready to build your retail media platform? Sphere Media Technologies brings expertise in first-party data strategy, closed-loop attribution, ad-serving infrastructure, and omnichannel measurement. We help marketplaces transform commerce data into high-margin media revenue. Let’s build your media strategy together.
