Retail Media Networks: The Ultimate 2025 Guide

In just a few years, retail media networks (RMNs) evolved from a niche experiment into a multibillion-dollar digital advertising channel. Brands are pouring ad budgets into retail networks because they promise something traditional channels often can’t: ads shown to shoppers at the digital point of purchase. 

But with great opportunity comes great complexity. 

Marketing ops and analytics teams are now drowning in data silos from each platform, each with its own reporting dashboards and metrics. 

The result? Fragmented insights, inconsistent KPIs, and hours wasted consolidating reports instead of optimizing campaigns. 

This guide will arm you with a deep understanding of retail media networks and a roadmap to navigate them. We’ll break down what RMNs are, why they’re booming, the challenges they pose for data-driven marketers, and how to unify your retail media data to drive better decisions. 

What Are Retail Media Networks (RMNs)?

The retailer leverages its first-party data, including purchase history, browsing behavior, and loyalty programs, to help brands target customers in a privacy-compliant way. 

This creates a win-win situation: retailers unlock a new revenue stream—selling ad placements, and brands get to show ads to high-intent shoppers at or near the point of purchase.

Examples of retail media networks: 

• Amazon Ads: The pioneer in retail media, letting brands bid on sponsored products, display ads, and video placements across Amazon’s e-commerce ecosystem.
• Walmart Connect: Walmart’s ad network that blends in-store, online, and offsite placements powered by its shopper data.
• Target Roundel: Target’s network focusing on integrated campaigns across Target.com, in-store, and partner channels.
• Kroger Precision Marketing: Grocery-focused network leveraging loyalty card and in-store purchase data for precision targeting.
• Instacart Ads: Provides brands with sponsored product listings and display ads on the leading grocery delivery app.
• 7-Eleven Gulp Media: Even convenience stores offer digital and in-store ad inventory tied to frequent shopper data.
• Home Depot Retail Media+: Enables brands to reach DIY and home improvement audiences through site, app, and offsite ads.
• Sephora Media Collective: Beauty-focused network using customer profiles and loyalty program insights for hyper-personalized ads.

Retail media spans several channels and formats, which we can categorize into on-site, off-site, and in-store.

As the table above shows, RMNs aren’t limited to website banner ads. 

Retailers are offering omnichannel ad opportunities: a brand can buy sponsored product placement on the retailer’s site and run ads on external sites retargeting those same shoppers, and even show an ad on a smart fridge or in-store display when the shopper visits a physical store. 

This omnipresence is what makes retail media so powerful: it blends online and offline, and retailers act as both publisher and ad network.

Crucially, all these channels feed back into the retailer’s closed-loop measurement. For example, if a shopper clicks a Pampers ad on Walmart’s website and later purchases that product in-store or online, Walmart can attribute that sale to the ad. This closed-loop attribution is a major draw for advertisers.

Why Retail Media Networks Are Booming in 2025

Retail media isn’t just growing, it’s exploding. In 2025, brands consider RMNs a must-have in their marketing mix. Here’s why this channel has taken off.

1. First-Party Data Goldmine: The fuel behind this boom is retailers’ first-party data. With third-party cookies on the decline, advertisers crave alternative ways to target and measure performance. Retailers provide enormous amounts of purchase and behavior data on logged-in customers. This data allows precision targeting (for example. showing a coffee ad to someone who bought a coffee maker last month) and measurement of actual sales, all in a privacy-safe way.
   
2. High ROI and Short Funnel: Shoppers reached through RMNs are often already in “buy mode,” which leads to higher conversion rates. In one survey, 96% of brands reported achieving their desired brand impact, and 63% said they exceeded KPI expectations. The path from seeing an ad to making a purchase is often just a few clicks on the same site, creating a very short funnel. These tangible results, such as measurable ROAS and lifts in category sales, are prompting finance and marketing leaders to allocate more budget to retail media.
3. Walled Gardens Dominated by Amazon (for now): It’s impossible to discuss RMNs without acknowledging Amazon’s dominance. Amazon Ads accounts for roughly 75% of all U.S. retail media ad spend, essentially making Amazon the “Google of retail media.” This dominance is due to Amazon’s sheer scale and rich data (around 60% of online product searches start on Amazon). For marketers, Amazon is table stakes, but the next 10-20 networks collectively represent a significant opportunity too.
   
4. Budget Reallocation & New Advertisers: The surge in retail media spend is coming both from new budgets and shifted budgets. According to industry research, 75% of advertisers planned to increase retail media investments in 2025, often by reallocating dollars from other channels. Additionally, RMNs are attracting non-endemic advertisers (brands that don’t sell products at that retailer). For example, financial services or automotive companies are now buying ads on retail sites to reach those retailers’ audiences. Retailers like Walmart and Home Depot have begun offering off-site and CTV options specifically to court these non-endemic advertisers. This expansion opens the door to even more ad dollars flowing into the retail media ecosystem.
5. New Formats: Initially, retail media was mostly on-site banners and sponsored listings. By 2025, it’s far more diverse. Off-site retail media is the fastest-growing piece. Retailers partner with DSPs or media platforms to extend their audience targeting to the open web, social media, and streaming TV. In-store retail media is also rising: although it’s currently a small slice, it’s expected to jump in the next few years as retailers install more digital screens and tracking tech in physical stores. The omnichannel approach of RMNs is a unique advantage over other ad channels, and retailers are investing to grow it.

However, capturing this opportunity is easier said than done, especially when you’re advertising across a dozen different retail networks. 

Next, let’s examine the key challenges that come with the RMN gold rush.

Key Challenges of Retail Media Networks for Enterprises

Despite the numerous benefits, retail media networks present major challenges for marketing operations and analytics teams, particularly in large enterprises. 

As the industry matures, advertisers are loudly voicing pain points around data fragmentation, measurement, and scalability. Here are the primary hurdles and what’s at stake.

1. Fragmented Platforms, Siloed Data

Every retail media network is essentially a walled garden. An advertiser running campaigns on five different RMNs might have to log into five separate platforms to pull reports. Data is fragmented across platforms, each with its own naming conventions and analytics. 

For example, Amazon might report “Total Sales” for a campaign, Walmart Connect reports Gross Merchandise Value, and a grocery RMN reports only in-store vs online sales , making apples-to-apples comparison difficult.

The fragmentation isn’t just inconvenient; it’s a barrier to insight. 

Marketers end up spending countless hours manually exporting CSV files and merging spreadsheets to get a consolidated view. It’s not unusual for ops teams to spend 20-40% of their week on reporting busywork in this environment. Worse, any manual data wrangling invites errors — one missed file or a formatting mistake can skew the entire analysis.

From an analytics leader’s perspective, this siloed data means no single source of truth. You can’t easily answer questions like “Which retail partner delivered the highest ROAS last quarter?” or “What is our total retail media spend vs. revenue across all retailers?” without a heavy data integration effort.

2. Measuring ROI and Attribution Across Networks

Measuring the ROI of retail media campaigns should be straightforward, after all, these networks often report direct sales attributed to ads. 

The challenge is that each network measures ROI in its own silo. If you spend $100K on Amazon Ads and $100K on Target Roundel, you’ll get two separate ROAS figures, one from Amazon (for Amazon sales) and one from Target (for Target sales). 

But how do those add up in terms of incremental revenue to your business? 

And how do you avoid double-counting if the same customer saw your ad on multiple platforms?

This is essentially an attribution problem. Within one retailer, you have closed-loop attribution, often last-click or last-touch within that ecosystem. Across retailers and channels, attribution becomes fuzzy. 

Say a customer sees a sponsored product on Walmart.com and a week later searches on Amazon and buys the product there – Walmart’s platform might not count it as a sale at all since purchase happened on Amazon, and Amazon will count it but without knowing of the prior ad touchpoint. 

From the brand’s perspective, both ads influenced the sale. Without a unified view, you might overvalue Amazon and undervalue Walmart in that scenario.

Moreover, many RMN purchases are also influenced by other marketing channels. Enterprise marketers need a holistic attribution model, whether multi-touch attribution (MTA) or marketing mix modeling (MMM) that includes retail media as part of the customer journey. 

3. Operational Complexity and Tech Overhead

Running campaigns on even one retail media platform can be complex, now imagine 5 or 10. Each network has its own UI, ad formats, pacing rules, and learning curve. 

For a marketing operations team, supporting numerous RMNs means operational overload: multiple sets of creatives, different campaign structures, separate optimization tactics. 

This complexity extends to the analytics and IT side as well. Integrating with each RMN’s API and maintaining those pipelines can strain technical teams, especially since retailer APIs vary widely in maturity. Some networks might not even have a robust API, forcing reliance on file uploads or vendor-specific tools. 

Additionally, the lack of standardization across RMNs means analytics teams often have to create custom logic for each data source. Something as simple as a product category or campaign name might be structured differently in each dataset. 

4. Data Governance, Privacy and Compliance

Many RMNs provide advertisers with data that could include sensitive info like customer IDs (often anonymized) or purchase details. Enterprises must ensure they handle this data in accordance with privacy regulations (GDPR, CCPA, etc.) and any contractual terms set by the retailer. Missteps could lead to breaches of contract or, worse, data leaks.

A challenge here is that each retailer may have different data sharing policies and security protocols. For example, some RMNs might allow export of order-level data to your data warehouse, while others only share aggregated metrics. Keeping track of what data can go where – and making sure it’s secure – can be daunting, especially if teams are manually downloading reports to local machines.

There’s also the matter of governance and consistency. Without controls, different teams might pull data differently or apply different filters, leading to inconsistencies. This can erode trust in the numbers. 

Manual vs. Unified Retail Media Data Management

To illustrate the impact of these solutions, here’s a quick comparison of managing retail media data in the traditional siloed way versus using a unified platform approach.

Now, with challenges understood, how can organizations actually implement such an approach? Let’s walk through a practical playbook for unifying RMN data and analytics.

5 Steps to Unify Retail Media Network Data

Implementing a unified retail media analytics strategy may sound complex, but it can be broken down into a clear roadmap. 

Below is a step-by-step playbook to help marketing ops and analytics leaders centralize and optimize their RMN data. 

Step 1: Inventory Your Retail Media Sources and KPIs 

You can’t unify what you don’t know you have.

Start by mapping out all the retail media networks your organization is using or plans to use. List each platform along with the key metrics you care about from each. 

Also note how you currently access the data (manual download, API, third-party tool). Engaging stakeholders from each team can ensure you capture the full picture. 

This inventory phase helps identify overlapping metrics and any unique KPIs per network that need translation. It also rallies everyone around the goal of unified reporting, creating internal buy-in.

Step 2: Connect and Centralize Data from All Networks 

With sources identified, set up a central data repository (cloud data warehouse or marketing data platform) and connect each retail media source to it. 

Ideally, use native API connectors to automatically fetch data on a schedule. For example, using Improvado, you would configure connectors for Amazon Ads, Walmart Connect, Target Roundel, etc., each pulling granular data into your warehouse. 

Aim to centralize all relevant data, including ad spend, impressions, clicks, conversions, and any item-level or audience data the networks provide. If some legacy or smaller networks don’t have APIs, consider using ETL tools or even semi-automated CSV imports as a stopgap, so that everything ends up in one database. 

The goal is a single repository where a query can join data from any retail network together.

Step 3: Harmonize Metrics and Dimensions

In this step, create a data model that standardizes key fields. For instance, ensure all date fields use the same format and timezone, all spend is in the same currency, and that metrics like “Views” or “Impressions” are defined uniformly across sources. Use a transformation tool or SQL to map each source’s fields to a master schema. 

Also, standardize dimension values: a common example is aligning campaign names or product IDs across platforms. If you use a naming convention for campaigns, enforce it here so that a campaign running on two networks can be tied together analytically. 

This harmonization process might be iterative; start with core metrics and refine over time. Once set up, these transformations should run automatically whenever new data flows in.

Step 4: Integrate Retail Media Data with Sales & Marketing Data

To unlock attribution and deeper insights, merge your retail media data with other data sets. This includes e-commerce sales data (from your D2C site or retailer sales reports), in-store sales data (from your ERP or retailer portals), and other marketing channels (search, social, email, etc.). By joining on common keys like date, product SKU, or campaign ID (where applicable), you can analyze how retail media interacts with the rest of your business. 

For example, blend RMN ad spend with total sales of those products to compute lift, or join with Google Analytics to see if retail media drove traffic to your site. This integration is where an advanced platform shines: Improvado not only brings in 500+ marketing sources, but also can join data and feed it into your BI tools or data warehouse of choice. 

By integrating data, you set the stage for true multi-touch attribution and for understanding cross-channel patterns like halo effects of retail media on brand searches or vice versa.

Step 5: Deploy Analytics, AI, and Insights on the Unified Data 

With clean, unified data in place, it’s time to put it to work. Develop dashboards and reports that deliver insights for different stakeholders. 

For example, a marketing ops dashboard might track spend pacing and performance across all RMNs in real-time, an analytics team might build a model to identify which factors drive ROAS variations by retailer, and an executive report might highlight high-level ROI and growth trends in retail media. 

Modern platforms can add an AI layer on top of this data. Improvado’s AI Agent, for instance, allows users to ask natural language questions of the data and get immediate answers. Leverage such tools for anomaly detection and recommendations. 

The key is to establish a feedback loop: the unified data should continuously inform campaign optimizations. 

By following these steps, enterprises can transform retail media from a fragmented effort into a well-oiled, data-driven machine. It moves you from reactive campaign management to proactive optimization. 

Next, let’s cover some additional best practices and trends to consider as you refine your retail media approach.

Best Practices for Maximizing Retail Media Success

In addition to unifying data, there are several strategic best practices that can help enterprises get the most value from retail media networks. 

These practices align people, processes, and technology to the unique demands of RMNs:

• Align Retail Media with Overall Marketing Strategy: Retail media should not operate in a vacuum. Treat it as a core part of your omnichannel strategy. This means aligning messaging and creative with your broader campaigns and ensuring your retail media team (or agency) works closely with those handling other channels. Likewise, insights from one channel should inform others. Organizationally, some brands are blending their retail media and digital marketing teams to break silos. At minimum, have regular cross-channel meetings to discuss performance and opportunities so that retail media investments amplify and are amplified by other marketing efforts.
  
  
• Leverage Retailer Partnerships and Data Sharing: Many retailers offer more than just ad inventory, they provide data insights and collaboration opportunities. For instance, some RMNs share audience demographic info or category benchmarks. Whenever possible, take advantage of these. Set up quarterly business reviews with each major retail media partner to glean insights. Some retailers even allow privacy-safe data sharing for advanced analysis. If you have the capability, use these environments to run bespoke queries that can enrich your understanding.
  
  
• Focus on Creative and Relevance: With so much emphasis on data, don’t neglect the creative element. An ad that looks and feels like a helpful product recommendation will perform far better than a generic banner. Invest in creative optimization for each network. This might mean using the retailer’s templates for sponsored search ads, A/B testing different product images or titles, and customizing copy to the context. Many RMNs allow dynamic creative optimization based on their data (for instance, showing a different product to a repeat shopper vs. a new customer). Use these features if available.
  
  
• Monitor and Manage Frequency Across Channels: One emerging issue as off-site retail media grows is ad frequency. A consumer could potentially see your ad on a retailer’s site and then see a retargeting ad from the retailer’s off-site program on a news website, and also see your direct programmatic ad, all in one day. Coordinate frequency caps and budgets to avoid overexposure or ad fatigue. Some DSPs and retail media platforms are working on this, but as an interim solution, your unified data can help. Watch for overlaps in audience or spikes in impressions that seem too high relative to unique reach. Employ a frequency strategy: for example, you might decide that a customer should see at most 3 off-site RMN ads per week.
  
  
• Invest in Measurement and Incrementality Tests: Even with unified data, always seek to validate performance through incrementality testing. This could be as simple as hold-out geo tests (regions where you don’t run the retail media campaign to compare sales lift) or using retailer-offered A/B test solutions (some RMNs provide controlled experiments or ghost ads to measure true lift). Incrementality tests help confirm that the attributed sales are genuinely incremental and can reveal if one network cannibalizes another.
  
  
• Stay Agile and Embrace New Opportunities: New networks are launching, and existing ones are adding features like CTV ads, live shopping, or shoppable video. Keep a pulse on industry trends and be willing to pilot new opportunities but do so in a measured way.
  
  

By following these best practices, enterprise marketing teams can not only harness the power of retail media networks but do so in a way that is efficient, strategic, and aligned with overall business goals. The combination of solid data foundations and savvy marketing execution is what separates winners from laggards in the retail media era.

Turning Retail Media Chaos into Competitive Advantage

Retail media networks represent both a golden opportunity and a complex challenge for enterprise marketers. 

On one hand, RMNs offer unprecedented access to high-intent shoppers and a clear link between ad spend and sales. On the other, the fragmentation and technical hurdles can feel like chaos – with data and reporting scattered across countless retailer platforms. 

The winners in this new landscape will be those who turn chaos into competitive advantage by investing in the right data infrastructure and strategic processes.

By unifying retail media data, implementing robust attribution, and leveraging AI-driven insights, you transform RMNs from a patchwork of siloed campaigns into a cohesive, optimizable channel in your marketing mix. Improvado’s all-in-one marketing analytics platform is purpose-built to facilitate this transformation, unifying hundreds of sources and delivering a single source of truth that drives faster decisions and better outcomes.