AppsFlyerBreak up with Firebase before it breaks you: Practical migration guide
Summary
Firebase Dynamic Links (FDL) deprecation requires migration before August 25, 2025. This presents challenges for ad ops teams reliant on deep linking for campaigns, referrals, and measurement. Key insights include: First, understand your app's update cycle and current FDL usage—identify which user flows (onboarding, referral, paid campaigns) rely on deep links, how links are generated (manual, API, in-app), and how performance is measured (attribution, engagement).
Define requirements for cross-platform support, deferred deep linking, branded domains, campaign measurement, and volume estimates. Choose among three alternatives: niche deep-linking providers (e.g., Branch), DIY solutions (full control but high maintenance), or mobile measurement partners (e.g., AppsFlyer) that combine attribution and deep linking. Migration steps: configure new deep linking (Universal Links, App Links, SDK integration), map FDL use cases to new system, translate link parameters (handle 1:1 mapping, unsupported features, granularity differences), implement redirects from old FDL domains (if possible, using custom domains or proxy servers), update app code with new SDK and maintain backward compatibility.
Execute phased migration starting with low-risk, low-traffic links, then test extensively across platforms, OS versions, install types (fresh, update, re-engagement), and link channels (web, email, SMS, QR codes). This migration is an opportunity to clean up underperforming flows and optimize user engagement. Actionable takeaway: Proactive planning, phased execution, and thorough testing ensure a smooth transition and can improve app performance and user retention.
You Might Also Like
AppsFlyerUnlock the value of web-to-app
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.
AppsFlyerWinning big with influencers: A comprehensive guide for app marketers
Influencer marketing drives app growth by building trust and authenticity beyond traditional UA. Budgeting should start with target markets, CPM benchmarks, and a 25% uplift in daily organic installs. Choose creators based on data: audience demographics, recent views, and content alignment. Measure performance with granular attribution links (e.g., AppsFlyer OneLink) to track installs, conversions, and ROI. Avoid vanity metrics; focus on CVR, retention, and long-tail effects. Start with small campaigns to gather benchmarks before scaling.
AdjustHow are LLMs transforming mobile user acquisition? | Adjust
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.
AdjustWWDC25: AdAttributionKit, SKAN, iOS 26, and more | Adjust
Apple's WWDC25 announced significant AdAttributionKit updates, including support for multiple overlapping re-engagement conversions with conversion tags, customizable attribution windows per ad network, configurable cooldown periods to avoid misattribution, and new geography data (country codes) in postbacks for high-volume campaigns. Testing capabilities are enhanced via developer mode. These changes give advertisers more control over attribution rules and insights, improving campaign optimization and measurement accuracy across iOS 26 and beyond.
AdjustHow AI is transforming personalization in mobile marketing | Adjust
AI personalization is now essential for mobile marketing, with 71% of consumers expecting tailored experiences. This article outlines how AI enhances audience intelligence, creative personalization via DCO and GenAI, engagement timing, and measurement. Marketers should start small with focused A/B tests, prioritize user value, and collaborate across UA, CRM, and product. Key challenges include privacy, overpersonalization, and model bias. Adjust's Growth Copilot offers AI-driven analytics to streamline decision-making.
AppsFlyerCross-channel marketing analytics: how it works in 2026
Cross-channel marketing analytics isn't about putting Meta, Google, and TikTok numbers side by side—they often double-count the same customer journey. Fragmented identity is the real culprit; without a first-party Customer User ID, attribution measures platform credit, not customer value. The article explains that deduplicating conversions across mobile, web, and CTV can lift attributed revenue by 30–60% and improve ROAS by 20%. It walks through attribution models, warns against platform-native analytics, and advises using an independent MMP for true cross-channel measurement. Ad ops takeaway: fix identity resolution first, because AI-driven optimization and budget allocation depend on trustworthy, deduplicated data.
AdjustMarketing mix modeling (MMM) for mobile marketers | Adjust
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.
MolocoInside Moloco's CARA: the AI that compounds
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.
More from AppsFlyer
Cross-channel marketing analytics: how it works in 2026
Cross-channel marketing analytics isn't about putting Meta, Google, and TikTok numbers side by side—they often double-co...
How an eCommerce Loyalty Platform Cut Time-to-Purchase by 66%
A leading eCommerce loyalty platform integrated AppsFlyer's deep linking and audience segmentation with Braze's engageme...
Five marketing lessons from football’s biggest tournament
Mobile engagement during the football tournament was fragmented, not continuous, with spikes lasting ~3 minutes around g...
Marketing attribution: what it is and how to measure it
Marketing attribution is critical for connecting spend to revenue, but platform self-reporting and last-click bias disto...
The Optimal Tech Stack for the AI Era
Ad ops decision-makers face four structural problems in marketing stacks: platform fragmentation, channel silos, funnel ...
6 reasons why mobile apps set the gold standard for omni-channel measurement
Mobile app measurement has solved the single-channel problems that plague other digital channels—independent attribution...