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.
European finance app installs hit 960M in 2025 but grew only 0.4%. BNPL apps grew 40% while crypto fell 35%, signaling a shift to utility. Neobanks win acquisition; traditional banks win retention (1.5-2x Day 30 rates). Web-to-app drives 41.8% of conversions but most brands can't measure the handoff. Nearly 1 in 2 investment app installs in Western Europe is fraudulent, distorting CPI and ROAS. Winning brands prioritize engagement, fraud detection, and cross-platform measurement.
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.
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.
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