Liftoff is transforming its presence at MAU 2025 in Las Vegas by replacing traditional booths with curated bungalow experiences. The agenda includes four main events: 1) App-y Oasis offering massages, drinks, and AppRefinery consultations on mobile marketing trends; 2) Donut Speak speakeasy kickoff party with gourmet donuts, live music, and surprises; 3) Women in Mobile KPI-n It Real rooftop event featuring relaxation activities and fireside chats with industry partners; 4) Teeing Up Tech golf-themed networking party with AppsFlyer, TikTok, and Xsolla. All events emphasize networking, relaxation, and industry insights.
Web-to-app strategies boost conversions by 77% and achieve 13.6% average paying user rate. Brands like adidas saw 2.4x higher ROAS from deep-linked users, while AirAsia improved bookings by 19%. Key challenges include measurement gaps, siloed teams, and onboarding friction. Solutions involve Google Ads Web-to-App Install and Web to App Connect with AppsFlyer Smart Banners and deep linking. Actionable steps: set tracking, import conversions, activate smart bidding, and deep link users.
LLMs like ChatGPT and Gemini are reshaping mobile app discovery, with traditional search volume expected to decline 25% by 2026. These AI platforms act as answer engines, delivering direct app recommendations to users. For ad ops, this shift requires optimizing for LLM visibility through structured content and reputation management. While native ad formats are in early testing on platforms like Perplexity and Gemini, early adoption can secure high-intent placements. Marketers should track AI-driven traffic and align discovery strategies across ASO, SEO, and LLMs to stay competitive in an AI-first environment.
At MAU 2025, Adjust highlighted its new Growth Copilot AI solution, aimed at helping mobile marketers turn data into actionable insights for smarter growth. The event featured key sessions on AI-driven campaign optimization and real-time decision-making. Networking events with partners like Reddit, Sensor Tower, and AppLovin fostered industry connections. For ad ops decision-makers, the key takeaway is leveraging AI to accelerate performance and scale resources efficiently.
Mobile app measurement has solved the single-channel problems that plague other digital channels—independent attribution (neutral third-party verification), privacy regulation (survived iOS 14.5 with new methods), signal governance (provenance, chain of custody), fraud detection (15% fraudulent installs, 275% fake installs in some channels), and cross-platform fragmentation. These capabilities, built under duress, now form the foundation for omnichannel measurement. Ad ops must apply mobile-grade rigor per channel first, then connect via CUID, unified attribution logic, and real-time data governance to build a trusted cross-platform framework.
TikTok For Business is courting new advertisers with a tiered credit promotion: spend $100/$500/$1,500 and receive equivalent ad credits, with the top tier adding 1:1 expert support. For ad ops decision-makers, the surrounding content underscores a strategic shift: marketers should embrace marketing mix modeling (MMM) rather than last-touch ROAS, leverage full-funnel AI automation, and use seasonal/industry playbooks (beauty, fashion, sports) to align creative with intent. Key takeaway: combine offer-based trial with longer-horizon measurement and structured content planning to maximize TikTok ad efficiency.
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.
Marketing mix modeling (MMM) is re-emerging as a privacy-compliant complement to attribution, helping mobile marketers evaluate the impact of media spend, pricing, ASO, and promotions on installs and revenue. Unlike traditional media mix modeling, MMM includes non-media levers. Combined with incrementality testing and predictive analytics, MMM provides a high-level view of performance without relying on user-level data, making it essential for modern measurement stacks.
India's mobile app market hit record revenue of $345M in Q2 2026, with non-gaming up 50% YoY. For ad ops, key opportunities lie in short drama apps (Story TV tripled ad spend), AI subscriptions, and ad-supported games like arrow puzzles, which generate over 11% of global ad revenue from India. Gaming revenue grew 10% YoY, outperforming global decline. Hypercasual game ad revenue rose 180% QoQ. India is transitioning from an acquisition market to a monetization powerhouse, offering scalable ad inventory across entertainment, local commerce, and casual gaming.
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