2025年零售媒体网络(RMN)将优先发展AI驱动的个性化,以解决广告疲劳和相关性下降问题。根据Harris poll,59%的购物者频繁看到相同广告,导致负面体验。利用零售商第一方数据的机器学习引擎可实现精准触达,Moloco数据显示个性化广告可将产品发现率提升10-15倍,显著提高用户参与度和转化率。
站点内广告成为2025年复兴重点,零售商重返自有平台优化广告体验。MA+C Retail Media调查显示,品牌优先将增量预算投入站点内搜索、展示和视频格式。AI实时预测将辅助广告形式融入购物旅程,根据购物车或历史购买推荐互补产品,提升整体体验而非侵扰用户。
绩效导向的广告购买模型如CPO和tROAS将成为衡量RMN成功的关键。经济不确定性促使广告主要求可量化的投放结果,推动RMN发展复杂归因能力。技术厂商利用ML自动优化目标指标,使零售商能匹配Meta Advantage+或Google Performance Max的效能水平。
区域渠道增长呈现差异:美国线下零售媒体支出预计2028年达10亿美元,数字格式(QR码、视频等)推动跨渠道投放;欧洲RMN早在店内广告布局,现强化站点内规模;亚太地区品牌预算加速流入零售媒体,数字商务成熟度提升。同时,自有渠道如邮件和推送将继续增长,而Offsite因利润率压力受限;CTV广告与零售媒体融合,拓展全漏斗营销。
RMN领导者需投资销售与GTM能力,将媒体业务从增量收入升级为核心职能。亚马逊等平台超三分之二运营收入来自广告,促使零售商组建专业团队并升级技术栈。自助服务平台的兴起,借鉴市场广告模式,使中小零售商能高效触达成千上万广告主,通过AI自动化减少人工服务,实现长尾规模化增长。最终,成功的RMN将兼具ML驱动的个性化和精简广告运营,将第一方数据转化为可衡量的ROI,驱动长期盈利。
Retailers building retail media networks (RMNs) can learn from Google, Meta, and Amazon by leveraging first-party data, machine learning, self-service automation, and outcomes-based performance. Key insights include using purchase intent signals and loyalty data for personalization, investing in AI for targeting and optimization, automating campaign management to scale advertiser participation, and moving to outcome-based pricing like closed-loop attribution. These strategies transform RMNs into high-margin ad platforms that deliver value for brands and shoppers.
Digital retail maturity shifts focus from downloads to omnichannel experiences, engagement, and ecosystems. Key data: 8.7B app downloads, 400B web visits, mobile 59% of web visits in Q1 2026. Competitive advantage comes from quick commerce, loyalty, content-led discovery, and connected in-store. For ad ops, prioritize engagement and frequency over acquisition; mobile is dominant; ecosystem expansion is critical.
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.
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.
This guide helps app marketers select a Mobile Measurement Partner (MMP) by covering essential features like privacy-first measurement, unified attribution, fraud protection, and advanced analytics. It emphasizes choosing an MMP that integrates easily, scales with business growth, and provides reliable data for optimizing marketing ROI across teams.
Retail media networks (RMNs) offer outcome-based advertising (e.g., 400% ROAS) using first-party data and ML, crucial amid tariff-driven economic uncertainty. Global ad spend growth slows to 5.8% in 2025, but digital and retail media thrive (18% YoY growth) due to transactional proximity and closed-loop attribution. Moloco's ML enables real-time optimization at campaign/SKU level, delivering 3x higher ROAS than legacy models. Advertisers demand certainty; RMNs that pivot from impression/CPC to outcome-based models will capture shifting budgets.
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.
Moloco's Audience Targeting Suite enhances retail media by blending purchase and intent data for precise targeting. Key features include Smart Targeting with AI/ML for automated optimization, Custom Audience Targeting via event/item/time rules, and Predefined Targeting for first-party data activation. Audience Administration tools control access to premium segments. Retailers benefit from increased ROAS, data governance, and revenue from CDP investments. Advertisers gain flexible, high-performing campaigns with closed-loop attribution.
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