Retail media is the fastest-growing sector of digital advertising, with spend rising over 20% year over year. However, two myths hinder RMNs: 'too many RMNs' causing fragmentation, and 'RMNs need external demand.' A common misguided solution is building a retail media SSP, which manages multiple demand sources. However, SSPs fail to scale because they don't improve existing inventory performance, lack ML-driven relevance for 1:1 personalization, and shift performance risk to advertisers.
In programmatic RTB, RMNs risk commoditizing inventory as advertisers optimize across competitors. This leads to low budget utilization and fill rates. Moreover, most revenue comes from endemic advertisers, shaping strategies around a smaller subset of demand.
SSPs were designed for a different scale than retail media, where advertisers typically focus on 10-20 key RMNs. RMNs are mini walled gardens with unique advantages: transaction-close inventory, best first-party data, and built-in brand relationships. To scale, they should follow the playbook of Amazon, Meta, and Google—using top tech and ML for relevance, simplifying demand scaling while de-risking media investment, and expanding inventory without harming organic metrics.
A purpose-built, ML-driven partner like Moloco can maximize first-party data predictive power, enabling RMNs to control their ecosystem and unlock sustainable growth.
First-party data, collected directly from users with consent, is crucial for marketers due to privacy regulations limiting third-party data. It enables accurate personalization, compliance, and cost savings. Key steps include ethical collection, maintaining clean data, and using it internally for product/marketing optimization and externally via commerce media networks.
Onsite retail media ads remain the most critical driver of RMN growth, accounting for over 80% of ad spending. They offer higher ROAS, better margins, and brand safety. Leading RMNs like Amazon and Walmart generate most media revenue from onsite. Growth can be unlocked through ML optimization, self-serve platforms, and outcomes-based campaigns, even without massive traffic increases.
Earned media is unpaid, third-party brand exposure from reviews, shares, or media mentions. It builds trust, expands reach, and boosts SEO. Marketers can leverage it via customer reviews, influencer endorsements, and UGC.
This guide helps app marketers select a Mobile Measurement Partner (MMP) by covering essential features like privacy-first measurement, unified attribution, fraud protection, and advanced analytics. It emphasizes choosing an MMP that integrates easily, scales with business growth, and provides reliable data for optimizing marketing ROI across teams.
The open internet presents unique challenges for performance advertising: fragmented identity, closed first-price auctions, and non-stationary supply. Moloco's CARA compound architecture tackles this with six integrated technical domains—Campaign Automation, Supply, Ad Recommendations, Bidding, Creative, and Signals—running on a unified ML infrastructure. Key insights for ad ops: the system continuously learns from every interaction, uses knowledge distillation to serve real-time predictions under 10ms latency, and validates improvements through rigorous live experiments. In 2025, 65 validated model updates reduced CPA by 17% and improved ROAS by 27%. The key takeaway: compound AI architectures that connect prediction, bidding, creative, and data can unlock measurable performance gains beyond walled gardens.
In-app bidding is increasingly preferred over waterfall due to efficiency, with around 80% of publishers now using it. It reduces latency, manual work, and improves ARPDAU by enabling simultaneous bids from all buyers. ML models in platforms like Moloco optimize bids in real-time, while waterfalls allow manual pricing control but risk inefficiency and reduced advertiser interest.
Cross-channel marketing analytics isn't about putting Meta, Google, and TikTok numbers side by side—they often double-count the same customer journey. Fragmented identity is the real culprit; without a first-party Customer User ID, attribution measures platform credit, not customer value. The article explains that deduplicating conversions across mobile, web, and CTV can lift attributed revenue by 30–60% and improve ROAS by 20%. It walks through attribution models, warns against platform-native analytics, and advises using an independent MMP for true cross-channel measurement. Ad ops takeaway: fix identity resolution first, because AI-driven optimization and budget allocation depend on trustworthy, deduplicated data.
Non-gaming apps can reduce CAC by advertising on gaming platforms, reaching 3.3 billion monthly players. Creative formats like playable and rewarded video ads boost conversions. Key challenges include identifying high-value users and allocating sufficient budget for algorithm optimization. Successful examples include Buddy AI and food delivery apps.
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