广告营销工具
SEOSEO付费获客付费获客程序化广告网站变现程序化App 获客App 变现网站变现关键词研究搜索意图App 获客ROASCPAApp 变现CPCLTV联盟营销eCPMRPM零售媒体营销归因转化追踪创意情报MMPHeader BiddingDSPSSPRTB广告可见率填充率ASOSKAdNetworkARPDAU激励视频广告聚合联盟营销创意测试A/B 测试再营销相似受众广告优化品牌安全供应路径
SEOSEO付费获客付费获客程序化广告网站变现程序化App 获客App 变现网站变现关键词研究搜索意图App 获客ROASCPAApp 变现CPCLTV联盟营销eCPMRPM零售媒体营销归因转化追踪创意情报MMPHeader BiddingDSPSSPRTB广告可见率填充率ASOSKAdNetworkARPDAU激励视频广告聚合联盟营销创意测试A/B 测试再营销相似受众广告优化品牌安全供应路径

App 用户获取

Moloco

付费

机器学习驱动的移动广告平台,帮助 App 开发者高效获取优质用户,以 ROAS 为核心目标,数据私有安全。

上线移动UA机器学习ROAS数据安全

主要用途

Moloco Ads is a programmatic user-acquisition platform that trains a custom machine-learning model on each advertiser's own conversion events rather than relying on shared lookalike audiences. You feed it post-install signals such as purchases, subscriptions, or in-app actions, and Moloco combines those with contextual and real-time auction signals to predict which impressions across the open mobile app ecosystem are worth bidding on. It then automates bidding and budget allocation toward your chosen goal, whether that is installs, downstream events, revenue, or a return-on-ad-spend target. The platform is aimed at apps that already generate meaningful event volume and understand their unit economics, giving them programmatic reach into non-self-attributing inventory while keeping visibility into business outcomes.

所在链路

Moloco fits the launch and optimization stages of mobile UA, complementing self-attributing networks by reaching open-exchange inventory with first-party-trained models.

核心功能

  • Custom prediction models trained on the advertiser's first-party conversion data
  • Automated bidding and budget allocation across open programmatic inventory
  • Optimization toward installs, in-app events, revenue, or ROAS targets
  • Contextual and real-time auction signals layered onto first-party data
  • MMP integration for attribution and downstream event measurement
  • Performance reporting that ties spend to business outcomes, not just installs

适合谁用

  • Apps with high event volume seeking programmatic UA beyond walled gardens
  • Performance marketers optimizing to revenue or ROAS rather than installs
  • Teams that want machine-learning scale while retaining outcome visibility

新手提示

  1. Model quality depends on the volume and cleanliness of the conversion events you send, so instrument your in-app events accurately before scaling spend.
  2. Give campaigns a learning window before judging results; the prediction models need enough conversions to stabilize bidding.
  3. Connect a supported mobile measurement partner early, since attribution and event passback are what feed Moloco's optimization loop.
访问官方网站

更多工具: App 用户获取