AppLovin’s Array, a suite for OEMs and carriers, expands its strategic partnership with Samsung to Brazil, building on existing Latin American collaborations. The core value proposition is personalized on-device app recommendations that enhance Samsung’s native app ecosystem. Colin Behr, GM of Strategic Business at AppLovin, stresses that mobile manufacturers must complement device sales with helpful app recommendations to stay competitive.
Array leverages AppLovin’s massive scale and high-performance recommendation engine to provide partners exclusive access to high-value users through on-device inventory at optimal moments for app discovery. This results in smarter recommendations and a competitive edge. As the largest independent buyer in the industry, Array uses AppLovin’s vast mobile app network and user acquisition/retention technologies to engage new users at key lifecycle points.
Benefits include improved customer satisfaction over the device lifecycle, making it a winning solution for OEMs, carriers, and end users. The article suggests that Array delivers value by tapping into AppLovin’s app ecosystem, driving app downloads and user engagement.
Subscription apps like Netflix and Spotify charge recurring fees for premium features. They offer predictable revenue, higher user loyalty, and better App Store rankings. Key models include flat-rate, tiered, and per-user pricing. Success requires value-driven pricing, free trials, and transparent practices.
Marketing attribution identifies which channels drive conversions, helping allocate budgets effectively. It uses models like single-touch (first/last click) or multi-touch (linear, time-decay) to assign credit across customer journeys. Challenges include privacy changes and tracking difficulties, but solutions like MMPs and AI can help optimize campaigns.
Karthik Kannan distills deep linking into a practical 4R framework: Remember, Reach, Retrieve, Route. For ad ops teams, the key insight is that campaign context must survive the click-to-app journey. Adjust TrueLink captures link parameters on click; the user is then guided into the app via Universal Links, Android App Links, URI schemes, app stores, or web-to-app flows. On SDK init, the app session is matched and attributed to the click, then link data is passed to the app for routing. Decision-makers should ensure deep link paths, campaign parameters, attribution matching, and fallback journeys are tested to protect measurement and user experience.
Re-engagement campaigns remain effective despite privacy regulations. Key practices include targeting large audiences (250k+ device IDs), using PSA/ghost bid testing, implementing blockout windows to avoid cannibalization, and leveraging deep linking to reduce friction. These strategies help lower UA costs and achieve aggressive CPA goals.
Japan's finance app category is outperforming, with H1 2026 installs up 8% YoY and sessions up 40%—nearly 5x the install growth and well ahead of global figures (5% and 29%). Stock trading is the standout subvertical: installs +90% YoY and average session length climbing to 11.7 minutes, driven by NISA reforms and a retail investor resurgence. Retention is improving across the full 30-day curve (D1 17% to 19%, D30 7% to 8%). For ad ops teams, the takeaway is clear: prioritize measurement depth, re-engagement, and channel-level quality over top-of-funnel volume alone.
Omnichannel analytics unifies customer behavior and campaign performance across mobile, web, CTV, and AI search into one identity, one attribution model, and one ROAS number. The core problem: a single customer seen on three surfaces becomes three users, inflating performance and corrupting attribution, LTV, and retention. Stitching channel reports into one dashboard is not unification—each channel keeps its own attribution logic, so conversions get double-counted and upper-funnel spend looks unproductive. For ad ops leaders, the takeaway is that identity resolution (deterministic plus probabilistic, privacy-safe) must happen at the data layer before any dashboard exists. Platform choice hinges on surface coverage, identity resolution, compliance, incrementality testing, and migration support.
Amplify Shanghai emphasized AI-driven ad optimization, eCPM growth, and CTV potential. Panelists highlighted data-driven strategies for monetization and user acquisition. Key takeaways: use AI for targeting, diversify focus across tiers, and leverage MAX platform's segmentation for higher ARPDAU.
Retargeting spend is rising—AppsFlyer reports $31B and 29% of app marketing spend in 2025, up from 25%—because UA costs are inflated and retention now drives LTV. For ad ops decision-makers, success requires segmenting users into active, dormant, and lapsed cohorts and tailoring campaigns rather than using generic messaging. Active users respond to offers and release notes; dormant users need incentives to return; lapsed users require balanced ads and incentives, with disengagement timing identified. A free-to-play example shows refining LTV-based targets can improve long-term ROI. Treat retention as a core LTV lever.
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