广告营销工具
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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

Bidease

付费

面向 App 营销的程序化移动 DSP,结合机器学习竞价与自动化素材,专注买量与再营销并优化深层应用内事件。

上线移动DSP程序化买量再营销

主要用途

Bidease operates as a self-serve and managed programmatic DSP that buys mobile inventory through real-time bidding on the open exchanges rather than relying solely on closed ad networks. Marketers set campaign goals around installs or post-install events, and the platform's machine-learning models predict user value and adjust bids on each impression to hit cost-per-action targets. A built-in creative studio generates and rotates playable, video, and banner formats, while deep-funnel optimization ties spend to revenue and retention signals. Bidease integrates with mobile measurement partners for attribution, supports SKAdNetwork and privacy-preserving measurement on iOS, and runs both acquisition and retargeting campaigns. It fits performance app teams that want exchange-level reach, transparency, and creative iteration outside the walled gardens.

所在链路

Bidease sits at the launch and optimization stage of mobile UA, complementing self-attributing networks with open-exchange programmatic buying measured through your MMP.

核心功能

  • Real-time bidding across mobile open exchanges and SSPs
  • Machine-learning bid models optimizing toward in-app events
  • Built-in creative studio for playable, video, and banner ads
  • Deep-funnel optimization tied to revenue and retention
  • MMP integrations plus SKAdNetwork and privacy-safe measurement
  • Separate user acquisition and retargeting campaign types

适合谁用

  • Performance app teams seeking programmatic reach beyond ad networks
  • UA managers optimizing toward post-install events and ROAS
  • Apps that need ongoing creative testing at exchange scale

新手提示

  1. Connect your mobile measurement partner first; Bidease optimizes on the post-install events it receives back via postbacks.
  2. Expect a learning period while the bidding models gather conversions, so avoid changing targets daily early in a campaign.
  3. On iOS, plan for SKAdNetwork limits and aggregated data rather than user-level reporting when judging results.
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