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Fragmentation and New Entrants in Retail Media: Ten Challenges and Ten Ways mediarithmics can Help
Retail media

Fragmentation and New Entrants in Retail Media: Ten Challenges and Ten Ways mediarithmics can Help

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mediarithmics Team
February 17, 2025

Fragmentation and New Entrants in Retail Media: Ten Challenges and Ten Ways mediarithmics can Help

Retail media is on track to surpass $160 billion in ad spending by 2025, outpacing TV advertising. Yet, fragmentation and an influx of new entrants are creating major challenges for advertisers and Retail Media Networks (RMNs) alike. Find out how mediarithmics can help.

The Growing Complexity of Retail Media

Retail media is experiencing unprecedented growth, with global ad spending projected to surpass $160 billion by 2025, even overtaking TV advertising. However, this boom has brought a wave of new entrants and increased fragmentation, creating challenges for advertisers, retailers and media networks alike.

While industry giants like Amazon (and Walmart in the US) dominate retail media spending, smaller Retail Media Networks (RMNs) must fight for survival in an increasingly crowded and complex landscape. Advertisers demand standardisation, transparency, and measurable ROI, yet many RMNs struggle to deliver.

In this article, we outline the ten biggest challenges facing RMNs today and explore how a holistic Customer Data Platform (CDP) like mediarithmics, which integrates Data Management Platform (DMP) capabilities, can help RMNs overcome these hurdles and thrive in an evolving marketplace.

Ten Challenges Facing Retail Media Networks

1. Market Dominance of the giants

Retail media networks are losing out to the giants on all fronts: Losing performance budgets to Google and Meta performance and, even in retail media, Amazon accounts for more than half of the European market. In the US, Amazon and Walmart account for more than 84% of the market.

  • mediarithmics helps RMNs monetise first-party data, enabling them to offer advertisers the same level of precision targeting as the retail giants. Furthermore, by providing enhanced measurement and attribution, retail media networks can also compete more effectively with giants like Google and Meta. 

2. Increasing Competition from New Entrants

As new sectors like banking, telecoms and travel enter the space, competition is increasing, which could fragment adspend further.

  • With advanced audience segmentation and predictive analytics, RMNs can create high-value audience segments, alongside targeting and measurement, significantly increasing their appeal to advertisers despite competition.

3. Lack of Standardisation in Measurement and Attribution

Advertisers are frustrated by the inconsistent metrics across different RMNs, making it difficult to compare performance and justify investments in smaller networks.

  • mediarithmics provides cross-platform attribution models and data clean rooms, allowing advertisers to compare RMN performance accurately and ensuring transparency while protecting privacy.

4. Advertiser Demand for Cross-Channel Integration

Brands want a seamless advertising experience across multiple touchpoints—from e-commerce to in-store and Connected TV (CTV)—but most RMNs lack true omnichannel capabilities.

  • The mediarithmics platform unifies data across CTV, e-commerce, mobile, and in-store, allowing brands to execute fully integrated omnichannel campaigns.

5. The Complexity of In-Store Retail Media

While in-store retail media is growing rapidly, high infrastructure costs (e.g., digital screens, measurement tools) make it difficult for RMNs to scale this channel effectively.

  • mediarithmics enables real-time data processing to link in-store ad exposure with online and offline sales, improving attribution and ROI tracking for in-store campaigns.

6. Difficulty in Attracting Non-Endemic Advertisers

Retailers are looking to non-endemic brands (e.g., financial services, automotive) for growth, but many lack the data sophistication to convince these advertisers of retail media’s full-funnel potential.

  • By using AI-driven audience modelling, mediarithmics helps RMNs create custom audience packages, making retail media more attractive to financial services, travel, and automotive brands.

7. Retailers Operating in Isolated Walled Gardens

Many RMNs keep their first-party data siloed, preventing advertisers from integrating campaigns across different platforms and making it harder to compete with broader digital advertising ecosystems.

  • With secure data collaboration via clean rooms, advertisers can integrate RMN data with other ad platforms breaking down the silos and increasing the value of retail media campaigns.

8. Struggles with Cookieless Targeting and Privacy Regulations

As third-party cookies phase out, RMNs face challenges in audience tracking and attribution, requiring alternative targeting strategies.

  • mediarithmics offers privacy-compliant targeting solutions, including contextual advertising, first-party data enrichment and cookieless tracking, ensuring RMNs remain competitive.

9. Pressure to Deliver Performance-Based Advertising (CPC, CPA Models)

Brands are shifting towards cost-per-click (CPC) and cost-per-acquisition (CPA) models, but many RMNs lack real-time performance tracking to compete with digital ad platforms like Google and Meta.

  • The platform provides real-time bidding and optimisation tools, allowing RMNs to offer CPC, CPA, and ROAS-driven advertising models that meet advertiser expectations.

10. The Need to Build Strong RMN Brands

Agencies and advertisers can easily differentiate traditional media players (ITV vs. Channel 4, The Guardian vs. Daily Mail), but many RMNs lack clear positioning and brand identity in the market.

  • mediarithmics empowers RMNs to develop clear B2B positioning, providing data-driven insights that showcase their unique audience, the value of their customer base and media capabilities.

The Future of Retail Media: Consolidation or Innovation?

The fragmentation of retail media will push smaller RMNs to either consolidate or innovate. Those that fail to integrate data, optimise measurement, and enhance targeting capabilities will struggle against dominant players.

However, RMNs that embrace a unified, data-driven approach—leveraging platforms like mediarithmics—can unlock new growth opportunities, attract premium advertisers, and deliver measurable, high-performance media solutions. 

Using a clean rooms approach, mediarithmics facilitates data collaboration with multiple retail media networks. By helping to remove the barriers to working with multiple RMNs, we help advertisers to allocate a greater share of adspend across a range of RMNs (rather than simply allocating spend to the giants).

As retail media continues to evolve, the ability to seamlessly connect commerce and media, personalise at scale, and prove ROI will determine which RMNs thrive—and which fade away.