Creative split testing and Test and Learn are new measurement solutions that make it easier for businesses to test and optimize campaigns. Creative split testing allows A/B testing of different ad elements like formats, visuals, headlines, and calls to action, with each person seeing only one version for accurate results. This helps identify best practices specific to a business, improving long-term campaign performance and driving greater impact.
TikTok's Symphony suite, powered by generative AI, enables businesses to create TikTok-ready videos at scale. Key features include video generation from text or assets, image generation, avatar videos, and multilingual translation. Integration with Dreamina Seedance 2.0 improves product consistency and motion in videos. Available to all TikTok for Business users, outputs are labeled as AI-generated. Ad ops decision-makers can leverage Symphony to streamline ad creation, reduce manual fixes, and scale campaigns efficiently.
Mobile marketing teams are scrutinizing whether AI improves creative output or just increases volume. Key insights: inadequate A/B testing (top advertisers run 50+ variations/week); evolving Creative Director role toward strategy and taste; and the contested 'human-made' label in AI-generated assets. Actionable focus: intentional testing, platform-native creative, and building compound systems over resetting campaigns.
Install Facebook pixel, align campaign objective with goals, define target audience, optimize for business outcomes, and use automatic placements to maximize Facebook ad results.
In 2025, AI agents will automate ad production and UA, reducing personnel needs. Privacy concerns persist despite Google's cookie reversal, driving contextual targeting and new identifiers. Advertisers will explore CTV and in-app inventory via cost-per-outcome deals. M&A activity ramps up, with deal volume up 118% YoY. AI-generated creative becomes crucial as targeting narrows, enabling scalable, varied ad creatives.
Mobile video demands fast, clear branding and messaging within seconds. PockeTVCs optimize TV assets by front-loading brand, using graphics, and shorter durations for better mobile performance.
Mobile performance marketing succeeded by building a signal infrastructure—independent attribution, fraud protection, and structured postbacks—that fed optimization-grade data to ad platforms. Web measurement has lagged, relying on fragmented, platform-reported metrics. As AI-driven campaign optimization becomes standard, bad signals amplify errors. AppsFlyer’s Web Performance Measurement brings mobile-grade signals to web: independent attribution, server-to-server postbacks, cross-platform closed loops, and unified cost/revenue measurement. For ad ops decision-makers, this means one truth source, actionable optimization signals across networks, and complete omnichannel ROAS visibility—enabling AI to compound advantage, not error.
Early campaign metrics can mislead because they capture high-intent users first, while long-term performance depends on broader audiences and delayed monetization. Learning phases, monetization lag, and incomplete data make early ROAS unreliable. Ad ops teams should evaluate multiple completed cohorts and align optimization windows with conversion events to distinguish genuine trends from initial volatility. Sustainable scaling requires balancing early signals with patience for meaningful patterns to emerge.
At MAU 2026, the industry agreed that attention, not production, is the bottleneck. Cross-platform web-to-app attribution is now achievable with AppsFlyer's mobile-grade measurement extending to web, giving ad ops a unified view. AI is in production, with Square's team shipping six live workflows. Web-to-app is the most efficient top-of-funnel for app businesses, and retention overtakes acquisition. Ad ops must prioritize clean signal layers and incrementality testing over single-metric attribution.
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