Google今日宣布正式开源其营销组合模型(MMM)产品Meridian,向所有营销人员和数据科学家开放。该产品基于与数百个全球品牌的测试反馈优化而成,旨在提供更透明、创新且可执行的预算分配方法。
Meridian突破了传统MMM在绩效媒体测量上的局限,尤其针对搜索广告和AI驱动活动。它通过贝叶斯因果推断融合先验知识与实际数据,揭示营销的真实增量效果。例如,其中集成的MMM数据平台不仅提供Google媒体的核心数据(曝光、点击、花费),还新增Google Query Volume等维度,帮助广告主更准确评估搜索广告的实际驱动效果。
产品还支持深度定制:作为开源框架,用户可检查代码与模型逻辑,调整参数以适应特定业务。在预算决策方面,Meridian能基于销售、网站访问、利润、转化等KPI分析历史表现并运行多种优化场景。其创新之处在于将视频广告的“覆盖(Reach)”与“频次(Frequency)”纳入模型,而非仅依赖曝光量,从而更精准反映视频投资对业务的影响。此外,Meridian可无缝整合各渠道的增量实验结果作为先验,校准模型使其贴合真实业务目标。
为加速推广,Google同步启动合作伙伴计划,精选代理机构和测量供应商如Analytic Edge,这些公司已接受Meridian最佳实践培训。合作伙伴将协助广告主实施模型、优化投资并提供定制化测量支持。Analytic Edge创始人Santosh Nair指出,Meridian的技术创新(如评估搜索对消费旅程的间接影响、细分YouTube的Reach与Frequency)以及与Google Marketing Data Platform的集成,将帮助广告主更深入理解渠道间交互并优化策略。
总体而言,Meridian的开源标志着MMM领域向更现代、可衡量增量效能的演进,尤其适合当前多渠道、隐私优先的市场环境。品牌如Finder已从中获益,从自建线性回归模型转向敏捷的行业解决方案,并通过洞察验证了YouTube在标准转化追踪之外的额外价值。
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.
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.
Influencer marketing drives app growth by building trust and authenticity beyond traditional UA. Budgeting should start with target markets, CPM benchmarks, and a 25% uplift in daily organic installs. Choose creators based on data: audience demographics, recent views, and content alignment. Measure performance with granular attribution links (e.g., AppsFlyer OneLink) to track installs, conversions, and ROI. Avoid vanity metrics; focus on CVR, retention, and long-tail effects. Start with small campaigns to gather benchmarks before scaling.
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.
Preload campaigns are critical for UA in 2025, offering early brand presence, higher trust, and cost-efficient growth. Key benefits include increased visibility, engagement, and LTV. Practitioners should leverage advanced segmentation, automated recommendations, predictive analytics, extended attribution windows, and incrementality testing. Partnerships with OEMs and platforms like Appnext, Aura, AVOW, Digital Turbine, and InMobi can drive significant results, as seen with Magalu's 100k+ monthly installs and 4x ROAS.
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.
AppLovin CEO Adam Foroughi refutes a short report questioning its e-commerce ad business and pixel practices. He highlights rapid growth to a billion-dollar run rate, noting 80% of sales occur within 24 hours, proving incrementality. The pixel is standard, comparable to Meta and Google, and Shopify auto-appends data similarly. Foroughi emphasizes that the ad models are young but improving fast, and the web ad market offers massive opportunity. He urges investors to dig deeper and use AI tools to verify claims. The response underscores AppLovin's commitment to innovation and execution.
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.
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