Unlocking App Growth on the Open Internet: Why it Matters in 2026

Summary

The article argues that the open internet—comprising millions of independent apps, ad networks, and DSPs—presents a major growth opportunity for app advertisers, yet remains underutilized. Key data points include: US consumers spend 59% of online time on the open internet, but only 48% of ad dollars go there (The Trade Desk). Walled gardens (Meta, Google, TikTok) are losing programmatic ad spend share for the first time since 2017 (EMARKETER), driven by rising costs (Facebook CPI max $5.50 vs.

ad network $4.50, per Business of Apps) and Apple's ATT framework, which complicated tracking and inflated costs. Machine learning levels the playing field, enabling real-time, automated targeting across fragmented inventories. For gaming apps, the open web offers relevant users (gamers on game inventories), contextual playable ads, and improved segmentation.

For non-gaming (e.g., e-commerce), benefits include expanded audience targeting, performance-based pricing (e.g., Target ROAS), and engaging ad formats like shoppable videos. Actionable takeaway: approach the open internet in three steps—learn the decentralized ecosystem, work with partners that provide scale (high fill rates), and integrate a mobile measurement platform for unified attribution. Mintegral's SDK-powered solution covers 100,000+ apps, offering fill-rate control and integration with major exchanges, positioning it as a key enabler for open web growth.

Analyst Note

What's notable here is the explicit acknowledgment that walled gardens are losing programmatic ad spend share for the first time since 2017—a structural shift, not a blip. The article frames the open internet as the natural next frontier, but the key implication for UA teams is that the barrier to entry (fragmentation) is now being lowered by machine learning. This matters because the privacy-driven erosion of deterministic attribution in walled gardens (ATT, signal loss) has created a measurement vacuum that open-web platforms are filling with ML-based probabilistic models.

The competitive angle: UA managers who over-rotate on Meta/Google risk rising CPIs and diminishing returns, while early movers on open-web inventories (especially in gaming and e-commerce) can capture lower-funnel users before costs equalize. The practical impact for monetization strategists is twofold: first, the shift requires rethinking tech stacks—MMPs become critical for cross-platform measurement; second, the fragmentation demands more hands-on campaign management, as no single DSP replicates walled-garden ease. Timing is favorable: with walled garden ad prices at all-time highs and ML maturity in bid optimization, the open internet's 'diversity of users' is now addressable at scale.