2025年,AI代理将深刻改变广告技术行业。开发者利用Replit等工具快速构建应用与游戏,而XMP等媒介购买平台通过AI实时优化预算分配。用户获取(UA)经理可借助AI代理自动匹配需求与供应商,缩短销售周期;客户服务中,AI代理能根据具体问题定制响应,大幅提升效率。长期来看,AI将把创建十亿美元公司所需的人员从万名降至五千甚至五百,释放人力资源用于战略工作,改善利润率。
隐私保护成为2025年的焦点。消费者数据权利意识增强,尽管谷歌放弃淘汰第三方cookie,但其他浏览器已导致约40%的开放网络无法通过cookie寻址。这催生了隐私优先的定向方式,如匿名标识符或上下文定向,但数字广告从业者必须将隐私与合规置于2025年活动规划的核心。
广告主正拓展新渠道以应对隐私限制。互联电视(CTV)因消费者转向流媒体而获得更多媒体预算;电子商务广告主开始进入应用内及手游广告,尽管传统上此类广告的eCPM高达50-100美元,但成效付费模式降低了风险,使广告主愿意为下载及首次购买等成果支付20美元。
广告技术并购在2025年将加速。2024年Q3交易量同比增长118%,Outbrain以10亿美元收购Teads,Omnicom以135亿美元收购Interpublic,LoopMe收购ChartBoost以规避20-30%的交易所费用。行业信心恢复,预计将有更多IPO和收购,如SDK平台收购移动网页公司,或移动SDK网络收购CTV平台。
创意在定向受限的背景下愈发重要。AI解决了时间、人才和工具三大传统挑战:生成式AI可快速产出10、50甚至100个变体并进行测试,其新颖性和独特性本身就能吸引用户。2025年,AI生成的创意内容将大规模应用,成为广告主的核心竞争手段。
这篇文章在年底盘点时点发布,为广告投放从业者梳理了2025年关键趋势。值得关注的是,M&A活跃度回升(Q3交易量同比增118%)反映了行业信心恢复,尤其是Outbrain收购Teads等案例可能重塑竞争格局。此外,隐私合规从“威胁论”转向常态,40%开放网络无法通过cookie定位,促使UA经理必须将隐私优先纳入策略,而非被动应对。
AI Agent落地将降低初测新产品的交易成本,但实操中需警惕渠道适配性。整体而言,文章精准捕捉了从“技术驱动”到“规则+创意双轮驱动”的行业拐点。
Cross-platform measurement resolves the common problem of fragmented, device-level reporting that inflates ROAS and misallocates budgets. By unifying customer identity across web, mobile, CTV, and other surfaces, marketers gain a single view of LTV and attribution. AppsFlyer provides this via CUID stitching and Product Line grouping, enabling real-time, deduplicated insights without manual BI work. Key benefits include accurate cross-platform ROAS, elimination of duplicate attribution, and reliable data for AI-driven optimization.
One person built, shipped, and marketed a mobile game in 14 days using AI tools, achieving 5,563 installs at $0.39 eCPI on $2,200 spend. MCPs (Model Context Protocol) were critical for agentic workflows. The AI agent CLAW managed ad campaigns via AppsFlyer MCP and BigQuery. Data Locker streamed raw data for analysis. Key takeaway: vendors must offer MCPs for fast, agentic data access; measurement stack (Data Locker, ROI 360, Creative Optimization) is essential for solo teams; human+AI beats AI alone.
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.
Customer lifetime value (LTV) is a critical long-term metric for app success, but most marketers measure it per-device, understating true value by 2-5x. Cross-platform LTV stitches together web, app, CTV, and more, attributing all revenue back to the original acquisition campaign. Key drivers include retention (5% increase boosts profits up to 95%), purchase frequency, average order value, and acquisition quality. To improve LTV, focus on retention, cross-platform adoption, and optimizing acquisition by predicted LTV rather than CPI.
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.
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.
Non-gaming marketers like e-commerce, fintech, and subscription services are increasingly turning to mobile advertising, driven by rising costs on walled gardens. They are shifting from CPI to outcome-based models (e.g., ROAS, CPA), leveraging ML to find quality users beyond contextual placements. Key takeaways: ad platforms must enable direct revenue attribution, faster feedback loops, and product-first creative to serve these advertisers. The era of growth at any cost is giving way to quality-focused, intentional scaling.
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.
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本文指出,随着Cookie受限和确定性身份可靠性下降,广告业正从基于上下文的精准定向转向基于概率的预测系统。关键优势在于通过SDK直接获取供应、降低延迟,并利用机器学习实现实时优化。实践意义是,具备预测能力的平台能突破传统内容场景,以更低成...