Executive Briefing: Sunday 20 September

Meta is mandating greater reliance on its AI for ad placements, reshaping campaign control for marketers. Simultaneously, new privacy regulations in New Jersey introduce significant data collector registration fees and an outright ban on selling sensitive data, demanding immediate re-evaluation of data sharing practices. In retail, AI-driven product matching is emerging as a critical tool to combat choice friction and boost e-commerce conversions. Meta Mandates Automated Ad Placements Meta is removing advertisers' ability to exclude individual placements at the ad set level on Facebook and Instagram, pushing for greater adoption of Advantage+ Placements. This change is rolling out universally for most accounts, compelling marketers to rely on Meta's algorithm to decide where ads appear for optimal delivery. While account-level controls for excluding networks (like Audience Network) remain, the shift reduces granular control for the majority of advertisers. Categorised industries such as enterprise healthcare and financial services retain more placement options due to compliance requirements, but others are encouraged to embrace Meta's AI, which the company claims consistently yields better results and higher-quality leads than manual selection. New Jersey Introduces Data Collector Registration New Jersey's new A5328 law creates a unique "data collector" category, requiring companies that sell or license personal data to a data broker to register. This includes brands with direct customer relationships, with registration fees ranging from $5,000 to $1.5 million annually based on user data volume. Critically, the law also imposes an outright ban on selling sensitive data—including precise geolocation, health, or financial information—with no consent exception, impacting existing data sharing agreements and monetization strategies. Marketers operating in the state must assess their MarTech stacks against data broker registries and re-evaluate practices to avoid significant compliance costs and legal risks. AI-Guided Discovery Boosts E-commerce Conversion New AI tools like GuidelyPro.AI are emerging to address "choice friction" in e-commerce, where extensive product catalogues overwhelm shoppers and lead to bounces. This product match engine for Shopify and WooCommerce stores uses short, guided flows of three to five steps to ask relevant questions, match answers to live inventory, and return a tailored shortlist with explanations. By transforming product discovery into a conversation, the platform aims to increase engagement, add-to-cart rates, conversion, and average order value. Analytics track attributed revenue within a session-based window after interaction, offering a tangible solution for merchants struggling with conversion leaks in preference-led or complex product categories. Quality Over Quantity Critical Amidst Social Media Saturation The social media landscape is reaching a saturation point, with over 5.5 billion global users and declining engagement rates highlighting audience overwhelm. The rapid pace of trend culture and a flood of AI-generated "slop" content contribute to this challenge, making it impossible for consumers to engage with all they see. As human screen attention spans have dropped significantly, marketers are pressured to produce more content across more platforms, often exacerbating the noise. This environment necessitates a strategic pivot from creating content for content's sake to focusing on high-quality, relevant content that genuinely earns audience attention and cuts through the unprecedented volume.