App User Acquisition
Moloco
Moloco Ads is Moloco's machine-learning advertising platform for performance marketers acquiring users across the independent mobile app ecosystem. It uses an advertiser's first-party conversion data with contextual and auction signals to train custom prediction models, automate bidding and budget allocation, and optimize campaigns toward installs, actions, revenue, or return targets across global in-app inventory. It is best for apps with sufficient event volume and clear economics that want programmatic scale while retaining visibility into campaign performance and business outcomes.
What it does
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.
Where it fits
Moloco fits the launch and optimization stages of mobile UA, complementing self-attributing networks by reaching open-exchange inventory with first-party-trained models.
Core features
- 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
Best for
- 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
Beginner notes
- Model quality depends on the volume and cleanliness of the conversion events you send, so instrument your in-app events accurately before scaling spend.
- Give campaigns a learning window before judging results; the prediction models need enough conversions to stabilize bidding.
- Connect a supported mobile measurement partner early, since attribution and event passback are what feed Moloco's optimization loop.