Moloco近日宣布全球推出全新一代AI驱动的重定向模型,该模型现已对所有客户开放。早期测试数据显示,相比现有方案,新模型能带来高达15%的ROAS提升和12%的CPA降低,显著增强广告主在存量用户运营上的增量提效能力。
随着应用广告生态成熟,重定向在增长策略中的地位日益突出。当前重定向转化增速是用户获取(UA)的10倍,而成本效率是UA的5倍,带来更强的ROAS表现。在Moloco平台上,重定向用户的ARPU比UA用户高出3倍。然而用户留存仍是痛点:77%的用户在安装后3天内流失,非游戏类应用30日卸载率高达48%-61%。
新模型的核心升级包括更短的学习周期,使广告活动更快达到最优效果;增强的定向能力,能更精准识别和触达高意向的流失用户;以及支持多种投放目标,涵盖漏斗上层(如app open)到深层(如ROAS、CPA)指标。Moloco产品管理负责人Jean-Luc Nahon表示,头部游戏客户在重定向上的投入已是其他客户的3倍,验证了模型带来的实际商业价值。
Moloco提供统一的程序化广告平台,整合UA与重定向营销,实现全漏斗端到端管理。从用户拉新到广告变现,营销者可以一站式优化投放策略。具体案例中,某交易应用将首次存款的CPA降低50%,某游戏工作室则实现了4倍ROAS提升和3.5倍CPA下降。
Moloco强调,重定向已从可选项变为最大化LTV和营销效率的必选项。营销者应尽快采用新一代AI模型,以应对日益激烈的应用竞争,实现降本增效与长期增长。
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.
Aura Remarketing re-engages inactive app users via native on-device notifications, targeting high-value segments like in-app purchasers. It diversifies UA strategy by reactivating lapsed users (90% churn within 30 days). Key targeting: user type, demographics, device, download recency, engagement, and post-install behavior. Requires a performance link, redirect link, user criteria, bid, and KPIs. Currently supports notifications; future placements include Game Spotlight. No additional privacy steps needed.
Consumer app ad revenue is growing rapidly, projected to surpass gaming by 2026. Key challenges include user reaction to ads and internal team alignment. Solutions involve constant A/B testing, open-minded cross-team communication, and balancing ad frequency with user experience. Subscription tiers and ad formats like rewarded interstitials, banners, and in-line ads offer strong revenue opportunities. Blocking sensitive ad categories and using big networks with strict vetting are crucial. Gamification can boost engagement and ad placements.
Omnichannel analytics unifies customer behavior and campaign performance across mobile, web, CTV, and AI search into one identity, one attribution model, and one ROAS number. The core problem: a single customer seen on three surfaces becomes three users, inflating performance and corrupting attribution, LTV, and retention. Stitching channel reports into one dashboard is not unification—each channel keeps its own attribution logic, so conversions get double-counted and upper-funnel spend looks unproductive. For ad ops leaders, the takeaway is that identity resolution (deterministic plus probabilistic, privacy-safe) must happen at the data layer before any dashboard exists. Platform choice hinges on surface coverage, identity resolution, compliance, incrementality testing, and migration support.
AppLovin explains its AI-driven advertising platform, Axon 2, which has quadrupled ad spend to a ~$10B run rate. The engine uses five data buckets—no hidden data—and relies on sophisticated models with a reinforcement loop. For decision-makers, key insights: Axon drives incremental revenue, not cannibalization; compliance with ATT and no persistent IDs; web attribution uses first-party cookies; and the rapid learning loop adapts to any vertical. The article emphasizes data minimalism and world-class tech as the competitive moat.
Mintegral launches IAP ROAS optimization for precise in-app purchase targeting. The feature supports D0 and D7 windows, AI-powered bidding, and hybrid goals. Results show improved user acquisition scale and ROAS. Setup requires data integration, realistic goals, and careful optimization during learning phases (5-7 days for D0, 15-20 for D7). Best practices include limiting ROAS target changes to twice weekly with ±10% adjustments.
The article outlines five innovative strategies for sports betting apps to boost user acquisition and retention in the 2025 NFL season. Key insights include using tailored, time-limited ad creatives to leverage FOMO, optimizing UGC campaigns with niche influencers, implementing daily engagement systems like FanDuel's Daily Shuffle to improve LTV, introducing social features such as betting groups to foster community and competition, and maintaining flexible ad spend with diversified formats. These approaches move beyond generic bonuses to drive sustained engagement and conversions.
在归因分析(attribution)仍是投放效果衡量核心的同时,越来越多品牌开始在归因之上叠加独立的增量测量方案,以判断某一渠道究竟是在驱动新增增长,还是仅仅收割了原本就会发生的转化;Moloco 宣布与 Haus 达成合作,为投放移动应用...
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