本文系统性地指导应用营销者如何将网红营销整合到增长策略中,强调其超越传统效果营销的真实性价值。文章指出,网红不仅能带来安装量,还能建立信任并提升品牌回忆,是同时支撑用户获取(UA)和再营销的战略杠杆。
在预算制定方面,文章提供了四步法:首先定义目标市场并计算CPM基准(如YouTube英文受众CPM区间),其次设定安装目标(建议DOI提升25%),然后通过悲观/中等/乐观三种情景规划最低所需观看量,最后根据目标CPM和所需观看量算出预算。同时,比较了手动搜索、自助平台、多频道网络和网红营销机构的优劣势。
选择网红时,文章强调数据驱动而非直觉,需评估受众人口统计、近期平均观看量、内容垂直、CPM、过往表现、竞品合作、内容风格和品牌安全性。YouTube因高参与度和转化率被视为首选平台,建议交付物包括45-60秒内前25%位置的整合、转化链接和QR码。
活动管理方面,文章介绍了付费模式(固定费用和基于CPM的绩效模式),并强调长期合作需基于首次表现。创意简报应简短直接,给予创作者自由度,同时避免政治、宗教等敏感内容。
测量归因是核心挑战,因多数转化来自自然流量。文章推荐AppsFlyer OneLink实现跨平台、跨设备的无缝归因,避免用户体验受损。最终,文章提醒绩效因应用类型、受众、季节等因素而异,不应与传统UA渠道直接对比CPM或CVR。
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.
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.
The mobile advertising industry is optimistic heading into 2025, with 80% of marketers expecting the year to be as strong or stronger than 2024. Non-gaming apps are driving growth, with downloads up 12% YoY and IAP revenue increasing 20%+. Marketers are prioritizing profitability and ROAS, with over half reporting more aggressive KPIs. Generative AI is already benefiting creative production and optimization. iOS re-engagement remains underleveraged, and most marketers are still adapting to SKAN. Budgets are increasing, with a focus on ad networks and self-attributing networks.
Ad metrics are essential for optimizing campaigns in a market with rising costs (CPL up 25%, CPC up 10%). Key metrics include impressions, CPM, CTR, CPC, ROAS, CPA, and LTV. Mobile ads require unique metrics like app installs, retention, and stickiness. Best practices: align metrics with campaign goals, choose channels wisely, and partner with an MMP. Future trends include privacy-preserving measurement and AI-driven optimization.
This guide demystifies mobile marketing acronyms for ad ops. Key pricing models include CPM for awareness, CPC for traffic, CPI for installs, and CPE for engagement. Mintegral's Target CPE and Target ROAS optimize for conversions and ROI. Platforms like DSP, SSP, and RTB automate buying and selling. Attribution relies on MMPs, SKAN, and MMM. Metrics such as MAU, DAU, LTV, and ARPU track performance. Monetization models (IAA, IAP, hybrid) and ASO/CTV are also covered. Actionable takeaway: choose pricing and tracking based on campaign goals.
Karthik Kannan distills deep linking into a practical 4R framework: Remember, Reach, Retrieve, Route. For ad ops teams, the key insight is that campaign context must survive the click-to-app journey. Adjust TrueLink captures link parameters on click; the user is then guided into the app via Universal Links, Android App Links, URI schemes, app stores, or web-to-app flows. On SDK init, the app session is matched and attributed to the click, then link data is passed to the app for routing. Decision-makers should ensure deep link paths, campaign parameters, attribution matching, and fallback journeys are tested to protect measurement and user experience.
Mintegral's retargeting platform re-engages dormant users via CPI, CPE, and ROAS bidding models. Key insights: retargeted users convert 50% more often than first-time visitors and are 3x more likely to engage, with over 50% completing actions within a week. The platform supports both gaming and non-gaming apps, offers 60%+ match rate, and integrates seamlessly with UA campaigns for lifecycle optimization.
Marketing mix modeling (MMM) is re-emerging as a privacy-compliant complement to attribution, helping mobile marketers evaluate the impact of media spend, pricing, ASO, and promotions on installs and revenue. Unlike traditional media mix modeling, MMM includes non-media levers. Combined with incrementality testing and predictive analytics, MMM provides a high-level view of performance without relying on user-level data, making it essential for modern measurement stacks.
AppsFlyer 同时打通 AI 流量的付费与自然两侧归因:付费侧通过 ChatGPT Ads 集成经 OpenAI Conversions API 回传,自然侧将原有搜索归因扩展至 AEO,覆盖 8 个 AI 引擎与 13 个传统搜索引...
真正的跨渠道营销分析并非把Meta与Google的报表并列展示,而是通过统一的身份识别(CUID)将同一客户贯通各渠道,在归因前解决重复计数问题,否则只是渠道聚合而非跨渠道分析。据AppsFlyer数据,统一归因能帮助品牌实现30%以上的归...
本文通过澳大利亚电商忠诚度平台的案例,展示了AppsFlyer与Braze集成如何将深度链接、行为归因和个性化编排融为一体,实现从安装到首次购买时间缩短66%的显著成效。关键数据包括推送收入提升500%、邮件和内容卡片收入增长50-80%,...
足球顶级赛事揭示了移动营销的五个关键教训:注意力呈3分钟爆发式碎片化,而非持续第二屏;购买行为与注意力不同步,中场休息是转化高峰;全球赛事不等于全球行为,本地法规、基础设施、生活习惯塑造差异;情感参与度比观众规模更能驱动互动,胜负难料的比赛...
营销归因是确定哪些渠道和广告活动真正驱动转化的关键,缺乏独立测量层会导致预算决策被last-click偏差扭曲,使真正有效的渠道被削减。多触点归因模型(如位置模型)比单触点更准确,但需要更多数据支持;AppsFlyer的归因方案可恢复30-...
文章指出AI时代营销技术栈的核心问题在于测量层与激活层脱节,四个结构性缺陷(平台碎片化、渠道孤岛、漏斗盲区、测量-激活断层)导致信号失真与决策偏差。关键洞察是传统营销云以激活为中心,但AI优化依赖独立、一致的信号层,AppsFlyer通过跨...