Retail Media Networks Are Reshaping Ecommerce: How Brands Can Harness Amazon, Walmart and Target’s First‑Party Data for Success

Introduction

Ecommerce marketing is undergoing a profound shift. While search and social advertising have long dominated media budgets, a powerful new channel has emerged: retail media networks (RMNs). These platforms—operated by giants like Amazon, Walmart, Target and Kroger—allow brands to advertise directly on retailer websites and apps, tapping into rich first‑party data and capturing consumers at the point of purchase. According to the latest digital marketing news, retail media networks are responsible for a significant portion of digital ad spend, with projections estimating $179.5 billion globally by the end of 2025.

This article explores why retail media networks have become one of the hottest topics over the past four weeks, how they differ from traditional advertising channels, and what practical steps marketers should take to succeed in this rapidly evolving space. We will examine the unique advantages of first‑party data, the role of AI and automation in RMNs, best practices for campaign execution and measurement, and potential challenges to consider.

Why Retail Media Networks Are Booming

The rise of first‑party data

One of the driving forces behind the growth of RMNs is the industry‑wide shift toward privacy and first‑party data. With third‑party cookies on the brink of deprecation and regulations like the General Data Protection Regulation (GDPR) and the California Privacy Rights Act (CPRA) limiting tracking, brands are seeking reliable ways to target and measure audiences. Retailers have a treasure trove of data from billions of transactions, loyalty programs and logged‑in user sessions. They know what customers buy, when they buy and how often they buy.

By advertising through RMNs, brands can leverage this data to serve personalized ads at pivotal moments. Unlike third‑party data, which is often aggregated and inferred, first‑party data offers a more accurate and consent‑based view of consumer behavior.

Full‑funnel, AI‑enhanced ecosystems

Retail media networks have evolved from simple banner placements into full‑funnel, AI‑enhanced ecosystems. They integrate on‑site sponsored product listings, off‑site display ads, streaming video and even connected TV (CTV) inventory. Advanced machine‑learning algorithms help determine which ad to show a specific customer based on purchase history, browsing patterns and demographic data.

This shift toward AI‑driven personalization mirrors broader marketing trends. Agentic personalization frameworks—where machine learning dynamically tailors content across multiple channels—are being applied to retail media. As a result, RMNs can deliver relevant ads while reducing wasted impressions and improving return on ad spend (ROAS).

Retailers as media companies

The explosive growth of RMNs is turning retailers into bona fide media companies. In July 2025 Walmart announced that its advertising business, Walmart Connect, had grown 30 % year over year. Amazon’s advertising services—once a tiny line item—now generate tens of billions of dollars annually. Target’s Roundel, Kroger’s Precision Marketing and Lowe’s One Roof Media Network all report strong double‑digit growth.

Retailers are drawn to advertising because it boosts margins and monetizes data. Brands, in turn, are attracted by the ability to influence shoppers right before purchase. This symbiotic relationship is reshaping the marketing landscape.

Comparing Retail Media to Traditional Channels

Traditional digital advertising relies heavily on search and social platforms. Google and Meta have long dominated digital ad spend, but their audiences are often in earlier stages of the buying journey. Retail media, on the other hand, targets shoppers with high purchase intent. Here’s how RMNs compare:

Intent – Search ads capture consumers actively looking for information, while social ads build awareness. RMNs intercept customers at the transactional moment, meaning that clicks and impressions are more likely to translate into sales.
Data quality – Retailer data is based on actual purchase history and browsing behavior. This is superior to inferred intent from third‑party cookies or general interest categories.
Measurement – RMNs allow closed‑loop attribution. Brands can track whether an ad view resulted in a sale, offering more precise measurement than channels where purchases may occur on separate sites or offline.
Competition – While competition on search is fierce for popular keywords, retail media auctions may offer opportunities for brands to gain visibility within specific categories, particularly emerging brands.

Major Retail Media Networks and Their Offerings

Amazon Ads

Amazon operates the largest retail media network. Its suite includes Sponsored Products (cost‑per‑click ads appearing in search results and product detail pages), Sponsored Brands (headline ads that feature brand logos and multiple products), and Sponsored Display (display ads across Amazon and third‑party sites). Amazon also provides access to its streaming platform, Amazon Prime Video, and Fire TV inventory.

Strengths – Massive audience of Prime members; robust data; sophisticated targeting; automatic optimization using machine learning.
Considerations – High competition in saturated categories; stringent creative guidelines; need for strong product pages (content, imagery and reviews) to maximize conversions.

Walmart Connect

Walmart Connect allows brands to buy on‑site placements (Search In‑Grid, Buy Box placements and carousels), off‑site programmatic display and in‑store advertising via TV walls and self‑checkout screens. Walmart leverages its in‑store and online purchase data to build detailed shopper profiles.

Strengths – Reach across brick‑and‑mortar and online shoppers; cross‑channel measurement; potential for local targeting based on store locations.
Considerations – Ad tech stack still maturing; limited tools compared with Amazon; requires coordination with Walmart’s merchandising and supply‑chain teams.

Target Roundel

Target’s Roundel offers on‑site sponsored products, digital display, CTV, audio, and social advertising through partnerships. It positions itself as a media company with the tagline “Results that matter.” Roundel uses data from its loyalty program (Target Circle) to deliver personalized ads.

Strengths – High‑quality data from a loyal shopper base; creative services to help brands develop campaigns; integration with streaming platform Peacock for CTV.
Considerations – Smaller scale compared with Amazon and Walmart; category restrictions (e.g., regulated products like alcohol require additional approvals).

Kroger Precision Marketing

Kroger Precision Marketing (KPM) is known for its 84 Million households worth of shopper data. It uses advanced analytics to predict purchase intent and offers on‑site ads, off‑site programmatic, and advanced measurement such as household‑level sales impact. KPM integrates with The Trade Desk to provide programmatic access to its audiences across the open web.

Instacart Ads

Instacart, the grocery delivery service, has also joined the retail media boom. It offers Featured Product Ads (FPAs) within its app, as well as display ads and promotions in email newsletters. With the shift toward online grocery shopping, Instacart allows brands to target consumers as they fill their carts.

Setting Up a Retail Media Campaign

1. Define clear objectives

Retail media can support different stages of the funnel, from awareness to conversion. Decide whether you want to increase brand visibility, drive product trials, boost repeat purchases or defend share of shelf from competitors. Align objectives with specific metrics—impressions, click‑through rate (CTR), cost per sale, return on ad spend (ROAS), etc.

2. Optimize product content and logistics

Ads are only effective if the product detail pages (PDPs) and supply chain are ready:

High‑quality content – Ensure titles, descriptions and images are optimized with relevant keywords and compelling copy. Avoid keyword stuffing; search engines and retailer algorithms favor clarity and customer benefits. This resonates with broader trends in SEO, where brands must focus on intent‑driven, multimedia‑rich content and structured data.
Inventory management – Check that products are in stock and that logistics can keep up with increased demand. A surge in sales without adequate supply can lead to negative reviews and lost ranking.
Ratings and reviews – Encourage satisfied customers to leave reviews. Products with higher ratings tend to perform better in sponsored placements.

3. Choose the right ad format

Select ad types that match your goals:

Promotions and deals to highlight discounts and seasonal offers.Many networks allow sequential messaging—for example, starting with a video ad and retargeting viewers with a sponsored product. Use these capabilities to nurture shoppers through the funnel.

4. Leverage AI and automation

Retail media platforms offer automated bidding and optimization. Use machine learning tools provided by the network to adjust bids based on predicted conversion likelihood. At the same time, maintain human oversight to ensure that AI decisions align with brand values and regulatory guidelines. Transparency tools like SODA (Semantic Output Debugging Assistant) are being developed to help advertisers understand why AI chooses certain phrases or calls‑to‑action.

5. Test and iterate

As with all digital advertising, A/B testing is essential. Experiment with different titles, images, pricing promotions and landing pages. Segment campaigns by audience (e.g., new vs. repeat customers) and location (e.g., Pacific Northwest vs. Midwest). Use the network’s analytics dashboards to measure performance.

Measuring and Optimizing Performance

Closed‑loop attribution

One of the greatest advantages of retail media is closed‑loop attribution. Because the purchase happens on the retailer’s site, you can directly connect ad exposure to sales. Key metrics include:

Return on ad spend (ROAS) – Revenue generated divided by advertising spend. A ROAS above 1 indicates profitable campaigns. Many brands target a ROAS of 3 or higher on RMNs.
Cost per sale (CPS) – Total ad spend divided by the number of orders generated. Compare this to profit margins to ensure campaigns are sustainable.
Incremental sales – Additional sales driven by advertising beyond what would have occurred organically. Some retailers provide “baseline” sales estimates to calculate incremental impact.
New‑to‑brand customers – Percentage of purchasers who have not previously bought from your brand on the platform. This metric is critical for measuring incremental reach.

Multi‑touch attribution and brand lift

For full‑funnel campaigns involving awareness and consideration, consider running brand lift studies or multi‑touch attribution models that incorporate off‑site media. For example, if you run a CTV ad on Target Roundel, measure changes in brand perception and search volume in addition to direct sales.

Cross‑platform analytics

While each retailer provides its own analytics dashboard, consolidate data using a marketing data warehouse or third‑party attribution tool. This will allow you to compare performance across Amazon, Walmart, Target and other channels. Integrate RMN data with broader marketing analytics (Google Analytics, CRM systems) to understand the full customer journey.

Advanced Strategies

Audience extension and off‑site programmatic

Many RMNs offer audience extension—allowing brands to use retailer data to target shoppers on the open web. For example, Walmart Connect and Kroger Precision Marketing both partner with The Trade Desk. Through these partnerships, you can reach shoppers on news sites, social media and streaming platforms using retailer segments (e.g., “healthy snack buyers”).

Leveraging generative AI for creative development

Generative AI tools can assist with creative ideation, copywriting and design. In August 2025, over 73 % of marketers are integrating generative AI into their workflows. Use AI to produce multiple variations of product descriptions, promotional headlines and imagery. Then test these variations in small segments and scale the best performers.

Preparing for retail search engines

As search functionality on retailer sites improves, optimizing product listings for internal search will become as important as Amazon SEO is today. Use keyword research to understand how shoppers search for your products. Include relevant attributes and benefits in product titles and bullet points. Provide structured data (e.g., nutrition facts, materials) to help algorithms match products with search queries.

Potential Challenges

Rising competition and costAs more brands jump on retail media, competition—and therefore costs—are increasing. Keep an eye on bid landscapes and adjust strategies accordingly. Protect your brand’s share of voice by bidding on your own product keywords, but also explore long‑tail keywords and emerging categories to find efficiency.

Data fragmentation

Each retail media network operates its own walled garden. Data from Amazon campaigns cannot easily be combined with Walmart or Target data. While cross‑network measurement solutions exist, they are still nascent. Brands may need to invest in custom data pipelines and dashboards to achieve a holistic view.

Dependence on retailer relationships

To unlock premium placements or special promotions, brands often need to coordinate with retailer account managers and meet specific sales thresholds. Manage these relationships proactively and ensure cross‑functional alignment between marketing, sales and supply chain teams.

Regulatory and ethical considerations

Retail media uses large volumes of consumer data. Ensure compliance with privacy regulations and adopt transparent data practices. Regulators are cracking down on misleading AI product claims, so avoid overstating the capabilities of AI‑driven ad targeting. Use tools that provide visibility into how AI models make decisions.

Conclusion

Retail media networks have moved from a niche innovation to a central pillar of ecommerce marketing. They capitalize on the power of first‑party data, reaching consumers at the moment of purchase and offering AI‑driven personalization. Projections suggest RMNs will capture $179.5 billion in ad spend by the end of 2025, signaling continued growth.

To succeed in this space, brands must optimize product content, choose the right ad formats, leverage automation responsibly, and measure performance through closed‑loop attribution. Advanced strategies like audience extension, influencer collaboration and AI‑assisted creative can further enhance results. While challenges exist—such as rising competition and data fragmentation—the opportunities are too significant to ignore. By embracing RMNs now, marketers can build a competitive advantage in the ever‑evolving world of digital commerce.Retail Media Networks Are Reshaping Ecommerce: How Brands Can Harness Amazon, Walmart and Target’s First‑Party Data for Success

Sponsored products for driving conversions in search results.

Display ads for raising awareness across websites and apps.

Video and CTV ads for storytelling and brand lift.