Google's Commerce Media solutions expand reach and leverage Google AI for improved performance, with transparency and control. The latest beta updates include Roundel, the first retail media network to enable online, app, and offline sales data measurement in Performance Max via Search Ads 360. Google Ads now supports Search, Shopping, and Demand Gen campaigns.
Improved self-service options allow retailers like Shopee, Rakuten, and Flipkart to share product catalogs with brands. Additionally, commerce and retail media are brought to YouTube through Display & Video 360, boosting off-site scale. A pilot for product-level measurement helps brands and retailers assess media spend effectiveness against product and category sales data.
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.
AppLovin CEO Adam Foroughi refutes a short report questioning its e-commerce ad business and pixel practices. He highlights rapid growth to a billion-dollar run rate, noting 80% of sales occur within 24 hours, proving incrementality. The pixel is standard, comparable to Meta and Google, and Shopify auto-appends data similarly. Foroughi emphasizes that the ad models are young but improving fast, and the web ad market offers massive opportunity. He urges investors to dig deeper and use AI tools to verify claims. The response underscores AppLovin's commitment to innovation and execution.
Retail media ad spend has reached $140B globally, but performance hinges on personalized customer experience, where a gap exists between retailer perception (92% believe they deliver personalization) and shopper reality (48% agree). AI-powered personalization can bridge this gap, debunking myths about data readiness, resource intensity, privacy risks, and growth ceilings. Modern AI handles imperfect data, automates campaign management, requires less PII, and enables real-time inference for higher engagement and revenue. Retailers can achieve 3-5x growth even in mature networks.
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.
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.
Digital retail maturity shifts focus from downloads to omnichannel experiences, engagement, and ecosystems. Key data: 8.7B app downloads, 400B web visits, mobile 59% of web visits in Q1 2026. Competitive advantage comes from quick commerce, loyalty, content-led discovery, and connected in-store. For ad ops, prioritize engagement and frequency over acquisition; mobile is dominant; ecosystem expansion is critical.
TikTok Automotive Ads is a catalog-based solution for vehicle promotions, offering Inventory Ads (for dealers) and Model Ads (for OEMs). Powered by Smart+, it uses data signals and creative formats like Video+Product Cards and Multi-link Carousel to match users with vehicles. Early tests show 41% lower CPA for Inventory Ads and over 40% CPA improvement for Model Ads. The solution simplifies campaign setup and leverages TikTok's large in-market audience, making it a key tool for driving measurable results in automotive advertising.
Retail media success now hinges on measuring true incremental sales, not just ROAS. 71% of advertisers prioritize incrementality, yet many rely on legacy attribution. Traditional testing methods are manual, revenue-limiting, and incompatible with AI-driven optimization. AI-native ghost bidding—using randomized controlled trials during live campaigns—cleanly separates ad-driven impact from organic behavior. Early results show iROAS from 253% to 1,609%, with up to 29% of conversions being truly incremental. Best practices include statistical rigor, clean population definitions, comprehensive conversion tracking, and regular testing. Future-proof incrementality solutions will be privacy-compliant and integrated into ad serving.
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