The article emphasizes the growing importance of user acquisition (UA) for non-gaming apps, which face challenges due to longer LTV maturation. With users spending nearly 5 hours daily on mobile devices and 90% of that time in apps, the competition is fierce. Notably, non-gaming app usage now surpasses gaming in the US, creating unique opportunities.
Success requires a tailored approach: Phase 1 involves creating engaging creatives, setting up MMPs, benchmarking CPIs, and aligning goals. Phase 2 launches campaigns with dedicated budgets for machine learning to reach target audiences, passing post-install data for accurate attribution. Phase 3 automates optimization towards down-funnel conversions and KPIs.
Key data includes 90% of US homes with CTV, and examples like Brigit (2X subscription rate) and Yemeksepeti (54% increase in first-time orders). AppDiscovery's managed service leverages proprietary ML to scale user acquisition and meet ROAS goals.
ChatGPT transforms marketing by accelerating research, ideation, and content creation. It aids in market analysis, competitor research, feature brainstorming, and ASO optimization. Marketers can leverage it for efficiency while maintaining strategic oversight.
Sensor Tower's Churn Analysis tracks new, retained, and resurrected users to understand mobile app churn. Different categories have varying churn rates, e.g., social media apps like Instagram have low churn, while retail apps like Etsy have higher churn. This tool helps optimize user retention strategies.
Sensor Tower's Power User data measures days used per month, revealing app stickiness. The metric shows crypto apps' declining engagement, Netflix's SVOD loyalty, Duolingo's growing stickiness, and Instagram's daily dominance, offering insights into user behavior and monetization.
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.
Mobile game studios are expanding to PC and console platforms to boost revenue and reach new audiences. This shift is driven by higher ARPU on consoles, privacy regulations, and market saturation on mobile. Cross-platform measurement solutions are essential for tracking user flows and optimizing performance marketing across devices.
Paid user acquisition via social, search, programmatic, and influencer ads drives app growth. AppDiscovery simplifies campaigns with ML optimization, CPI-based CTV ads, and creative support from SparkLabs, helping hit KPIs efficiently. Key insight: leverage automation and data-driven targeting for profitable, scalable UA.
The open internet presents unique challenges for performance advertising: fragmented identity, closed first-price auctions, and non-stationary supply. Moloco's CARA compound architecture tackles this with six integrated technical domains—Campaign Automation, Supply, Ad Recommendations, Bidding, Creative, and Signals—running on a unified ML infrastructure. Key insights for ad ops: the system continuously learns from every interaction, uses knowledge distillation to serve real-time predictions under 10ms latency, and validates improvements through rigorous live experiments. In 2025, 65 validated model updates reduced CPA by 17% and improved ROAS by 27%. The key takeaway: compound AI architectures that connect prediction, bidding, creative, and data can unlock measurable performance gains beyond walled gardens.
User testing reveals the gap between designer intent and user experience, uncovering silent churn causes like unclear onboarding or passive ad chains. Analytics show what happens; user testing explains why. Small tests (5-8 participants) can identify friction points, and improving retention by 10% can significantly boost revenue without changing monetization. For ad ops, this means better user engagement reduces wasted ad spend and increases lifetime value.
The blog highlights the strategic rationale for a TikTok merger, emphasizing the performance advertising gap where TikTo...
The article examines how identifiers like those from Google and Facebook flow across e-commerce sites via standard integ...
AppLovin explains its AI-driven advertising platform, Axon 2, which has quadrupled ad spend to a ~$10B run rate. The eng...
AppLovin CEO Adam Foroughi refutes a short report questioning its e-commerce ad business and pixel practices. He highlig...
User acquisition on a budget is achievable through a mix of organic and low-cost paid strategies. Key tactics include op...
Performance issues like crashes and slow load times directly reduce user retention and LTV. With 60% of users uninstalli...