The article discusses a shift in user acquisition strategy from solely relying on social media to testing various mobile ad networks due to rising costs and declining effectiveness. Key recommendations include: entering tests with an open mind, as each network differs in CPI, ROAS, and install volume; being transparent with networks about goals like 30% ROAS within 7 days; allocating sufficient budget per network (some need 500-2000 conversions for optimization); being patient, as conversion timelines vary (e.g., chat apps vs. banking apps); testing multiple creatives and formats (video, banner, playable) for AI optimization; discontinuing unsuccessful tests after a reasonable period; and not expecting ROI-positive results initially, focusing instead on learning.
The article also promotes AppLovin's AppDiscovery solution for achieving ROAS goals via machine learning.
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.
Retail media networks report ROAS using different methodologies, causing up to 63% fluctuation across networks for the same campaign. This isn't a data quality issue but a structural one. Brands using multiple networks face a fragmentation tax where each network is its own source of truth, and budget decisions based on these irreconcilable figures are misleading. Independent measurement, applying the same attribution logic across all networks, is needed to reconcile data and enable confident cross-channel decisions. The signal infrastructure for this already exists from mobile measurement.
AppsFlyer MCP connects Claude directly to live attribution data, replacing manual reporting and CSV exports. Gaming teams catch budget anomalies overnight, finance teams compress multi-hour analysis into minutes, and e-commerce teams close the gap between measurement and spend decisions. Setup takes under 60 seconds, enabling real-time queries on channels, cohorts, and ROAS. The key insight is that AI-powered analysis requires live data connections, not stale exports.
Effective creator campaigns ditch scripts, use natural hooks, apply trends strategically, and choose right communities. 47% value authenticity, 64% buy after seeing creator ads. Key: let creators speak naturally.
Non-gaming apps require specialized UA strategies focusing on high-value users. Key success factors include top-performing creatives, proper MMP setup, CPI benchmarking, and phased campaigns with machine learning optimization. AppDiscovery offers tailored UA campaigns to achieve ROAS goals. Shifting media landscape with CTV/OTT provides new opportunities.
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.
Email, SMS, and push are high-intent channels, but a structural gap between click and in-app action causes massive drop-off. CTRs of 30-40% often yield only 1-3% in-app conversion. The root cause is ESP link wrapping, which breaks deep link context and attribution. Fixing the handoff through proper deep linking can double purchase rates and unlock channel performance. Brands must treat the link as a continuation layer, not a redirect, and ensure context survives the transition.
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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