Liftoff has launched Cortex, a next-generation machine learning platform that leverages neural network technology to analyze larger datasets, improving decision-making and ROI for advertisers. Key advancements include processing 10x more training data, enabling 10x faster experimentation cycles, and achieving 6x faster model training. This results in more accurate predictions, quicker product releases, and better adaptation to market changes.
Partners like Playlinks and Bigo Live report improved ROAS, lower CPI, and higher user retention. Cortex is now widely used by Liftoff advertisers, with further innovations like SKAdNetwork models planned for late 2024.
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.
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.
Cross-platform measurement resolves the common problem of fragmented, device-level reporting that inflates ROAS and misallocates budgets. By unifying customer identity across web, mobile, CTV, and other surfaces, marketers gain a single view of LTV and attribution. AppsFlyer provides this via CUID stitching and Product Line grouping, enabling real-time, deduplicated insights without manual BI work. Key benefits include accurate cross-platform ROAS, elimination of duplicate attribution, and reliable data for AI-driven optimization.
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.
In-app bidding is increasingly preferred over waterfall due to efficiency, with around 80% of publishers now using it. It reduces latency, manual work, and improves ARPDAU by enabling simultaneous bids from all buyers. ML models in platforms like Moloco optimize bids in real-time, while waterfalls allow manual pricing control but risk inefficiency and reduced advertiser interest.
The article outlines five key mobile app market predictions for 2025, emphasizing AI/ML maturation, consumer-driven data control, the limitations of GenAI for measurement, growth of alternative app stores, and increased M&A activity. Ad ops decision-makers should prepare for scaled AI adoption, adopt multiple measurement frameworks to navigate privacy regulations, leverage ML models for privacy-compliant insights, explore emerging app distribution channels, and consider strategic acquisitions for market expansion.
Next-gen campaign optimization combines attribution, incrementality testing, and MMM for holistic insights. AI-driven tools like pLTV and deep linking automate analysis, reduce waste, and improve ROI. This scalable, privacy-compliant approach future-proofs marketing success.
Non-gaming apps can reduce CAC by advertising on gaming platforms, reaching 3.3 billion monthly players. Creative formats like playable and rewarded video ads boost conversions. Key challenges include identifying high-value users and allocating sufficient budget for algorithm optimization. Successful examples include Buddy AI and food delivery apps.
World Cup data from Liftoff's SSP shows ad impressions in sports scoring apps nearly doubled (+90%) and unique audience ...
In-app mobile advertising is held back by three myths: low-quality inventory, intrusive ad formats, and reliance on Big ...
Treating DSPs as interchangeable commoditizes ad buying. In reality, models differ sharply: two DSPs can view the same i...
Mobile marketing teams are scrutinizing whether AI improves creative output or just increases volume. Key insights: inad...
The 2026 Finance & Crypto App Performance Benchmark reveals a 47% increase in UA spend and 2.15x re-engagement spend in ...
The article highlights three key consumer app trends for 2026: social features becoming retention drivers (e.g., Spotify...