移动行业正经历从早期浏览器时代到当前碎片化时代的第五次变革。根据Moloco在MAU 2025上的分享,用户注意力已明显从少数超级平台转向大量垂直化、社区驱动的独立应用。数据显示,用户仅有32%的应用内时间花在Meta和Google平台上,其余时间分布在约300万个应用中,形成所谓的“独立应用生态”。
这一生态蕴藏着巨大广告机会。Moloco分析表明,独立应用生态的全球日活跃用户规模可达20亿,与TikTok和Instagram的总和相当。然而,许多营销人员仍难以衡量其中的增量效果,或未能使团队策略跟上用户注意力迁移的步伐。
与归因平台Singular的联合研究验证了该生态的ROI潜力。将广告预算扩展至独立应用的广告主,30日ROAS显著提升:全品类广告主平均提升48%,金融、教育、健康等消费类应用提升116%,购物类应用提升214%。数据显示,拥抱全频谱移动机会的广告主在新格局中收益最大。
面对碎片化挑战,AI驱动的广告技术成为解题关键。正如Google和Meta曾利用AI实现大规模精准匹配,当下广告主也可借助同类技术在独立应用生态中优化用户获取和投放策略,实现增量提效。
最后,文章呼吁移动营销人员利用自身对移动生态的深刻理解,以数据赋能组织,推动公司层面战略更新,从而在当前的移动时刻中占据先机。
Web-to-app strategies boost conversions by 77% and achieve 13.6% average paying user rate. Brands like adidas saw 2.4x higher ROAS from deep-linked users, while AirAsia improved bookings by 19%. Key challenges include measurement gaps, siloed teams, and onboarding friction. Solutions involve Google Ads Web-to-App Install and Web to App Connect with AppsFlyer Smart Banners and deep linking. Actionable steps: set tracking, import conversions, activate smart bidding, and deep link users.
LLMs like ChatGPT and Gemini are reshaping mobile app discovery, with traditional search volume expected to decline 25% by 2026. These AI platforms act as answer engines, delivering direct app recommendations to users. For ad ops, this shift requires optimizing for LLM visibility through structured content and reputation management. While native ad formats are in early testing on platforms like Perplexity and Gemini, early adoption can secure high-intent placements. Marketers should track AI-driven traffic and align discovery strategies across ASO, SEO, and LLMs to stay competitive in an AI-first environment.
AI personalization is now essential for mobile marketing, with 71% of consumers expecting tailored experiences. This article outlines how AI enhances audience intelligence, creative personalization via DCO and GenAI, engagement timing, and measurement. Marketers should start small with focused A/B tests, prioritize user value, and collaborate across UA, CRM, and product. Key challenges include privacy, overpersonalization, and model bias. Adjust's Growth Copilot offers AI-driven analytics to streamline decision-making.
Mobile app measurement has solved the single-channel problems that plague other digital channels—independent attribution (neutral third-party verification), privacy regulation (survived iOS 14.5 with new methods), signal governance (provenance, chain of custody), fraud detection (15% fraudulent installs, 275% fake installs in some channels), and cross-platform fragmentation. These capabilities, built under duress, now form the foundation for omnichannel measurement. Ad ops must apply mobile-grade rigor per channel first, then connect via CUID, unified attribution logic, and real-time data governance to build a trusted cross-platform framework.
The article argues that mobile apps are crucial for business growth, with 96% of consumers owning smartphones and mobile commerce accounting for nearly 70% of retail e-commerce. It highlights strategies like intuitive UX, AR features, loyalty programs, and app-exclusive discounts to boost retention and acquisition. Brands like Starbucks, McDonald's, and Nike successfully leverage apps for customer engagement and first-party data collection. Mobile ad spend in the US is expected to reach $228 billion in 2025, emphasizing the need for app-centric marketing. Retail media networks also offer new revenue streams through targeted advertising.
Marketing attribution is critical for connecting spend to revenue, but platform self-reporting and last-click bias distort budget decisions. Single-touch models (first/last-click) are simple but miss the full journey; multi-touch models (position-based, data-driven) are more accurate but require robust data. Mobile attribution is particularly challenging due to ATT, SKAdNetwork, and cross-platform gaps, necessitating a mobile measurement partner (MMP) for independent, deduplicated measurement. Clean attribution data is essential for AI-driven optimization—bad signals lead to bad decisions. Starting with position-based attribution and incrementality testing provides a practical foundation.
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.
India's mobile app market hit record revenue of $345M in Q2 2026, with non-gaming up 50% YoY. For ad ops, key opportunities lie in short drama apps (Story TV tripled ad spend), AI subscriptions, and ad-supported games like arrow puzzles, which generate over 11% of global ad revenue from India. Gaming revenue grew 10% YoY, outperforming global decline. Hypercasual game ad revenue rose 180% QoQ. India is transitioning from an acquisition market to a monetization powerhouse, offering scalable ad inventory across entertainment, local commerce, and casual gaming.
Moloco宣布推出代理商合作计划,旨在帮助代理商通过Moloco Ads为客户实现可衡量的绩效增长,首期已吸引全球超过十几家创始合作伙伴。该计划提供教育、专属支持及与产品团队更紧密的协作,助力代理商在移动应用广告和Performance ...
Moloco公开其广告AI系统CARA的技术架构,旨在解决开放互联网效果广告中身份碎片化、信号稀疏和实时竞价等挑战,通过六个技术域的复合设计实现持续学习与优化。2025年,CARA经实验验证的65项模型改进为广告主降低CPI 14%、降低C...
本文通过Moloco与BCG的AI Disruption Index研究,揭示AI正快速重塑数字发现格局,信息型web流量大幅下滑,而交易型相对稳健。数据显示,新闻、教育、健康健身等网站流量同比分别下降26%、22%和16%,但app端活跃...
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文章指出,游戏应用从第一天起就将变现视为基础设施,通过广告和IAP的混合模式实现全用户群变现,而非游戏应用仍依赖零散的广告策略,仅变现少数用户。关键数据显示,游戏贡献了应用商店60%的收入,混合变现模式的LTV比单一模式高50%以上。行业启...