The article compares in-app bidding and waterfall approaches for app publishers, highlighting that in-app bidding is gaining traction with about 80% of publishers using it.
Waterfall requires manual pricing and sequential network calls, leading to latency and inefficiency, whereas bidding allows all buyers to bid simultaneously, driven by machine learning models that optimize in real-time.
This reduces latency, improves ARPDAU, and frees up resources for other growth areas.
However, some publishers stick with waterfalls for control over pricing, especially for brand advertisers with different KPIs.
Yet, poorly configured waterfalls can limit effectiveness and deter performance-based advertisers.
In-app bidding provides cleaner data with single bid requests, enabling better ML model training and smarter bidding.
Moloco’s platform exemplifies this cycle: better performance leads to more learnings, smarter models, and increased ad spend, benefiting both advertisers and publishers.
The shift towards bidding is expected to grow as more networks adopt it.
First-party data, collected directly from users with consent, is crucial for marketers due to privacy regulations limiting third-party data. It enables accurate personalization, compliance, and cost savings. Key steps include ethical collection, maintaining clean data, and using it internally for product/marketing optimization and externally via commerce media networks.
MolocoThe open internet offers incremental growth opportunities beyond walled gardens. Supply path optimization is complex, with intermediaries inflating costs. Moloco's in-app bidding SDK creates a direct publisher-marketer path, eliminating fees to improve ROI. It enhances ML predictions with high-quality signals, giving marketers better transparency and control over ad rendering for improved engagement.
AdjustA/B testing on Google Play and App Store optimizes app listings. Google tests icons, descriptions, graphics; Apple tests icons, screenshots, videos. Both improve conversion and retention but have limitations like single-variable focus and lack of post-install data. Adjust enhances analysis with attribution and analytics.
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.
MolocoHitapps, a mobile game developer, uses in-app advertising and hybrid monetization to balance revenue and user experience. Early adoption of Moloco SDK boosted ARPDAU by 5-15%. Key challenges include privacy changes (ATT, iOS updates, Google's Privacy Sandbox) and loss of control in mediation. Hitapps evaluates partners based on demand quality, ease of integration, and ARPDAU uplift.
MolocoRetail media networks (RMNs) are rapidly growing but face myths about fragmentation and demand sourcing. Many consider building an SSP to attract demand, but this approach fails to scale. SSPs don't improve inventory performance, shift risk to advertisers, and risk commoditizing inventory. RMNs should instead leverage their unique first-party data and machine learning to drive relevance and performance, following models like Amazon, Meta, and Google to achieve sustainable growth.
MolocoThe Moloco SDK is a new solution for app publishers to maximize revenue by accessing Moloco's global advertisers directly. It is a certified bidding partner for AppLovin's MAX and Unity's LevelPlay. The SDK benefits both marketers (improved ROI, better performance, transparency) and publishers (direct demand, ML technology, creative control). Partners praise its high eCPMs and performance.
UnityTo avoid cannibalizing subscriptions, apps should prime users for ads, use user-initiated formats like rewarded videos, and segment users by region or device to target ads to low-conversion users.
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