Topic
Every post on the Index about privacy.
Jeff doubts that IAB Tech Lab's Trusted Server Framework answers Apple's Safari restrictions, since it still builds a trail on one person. He says the web has moved away from user-level tracking for years, and advises measuring what spend changed in aggregate.
Jeff argues that moving identity infrastructure server-side is just the latest circumvention of browser and walled-garden limits on user-level tracking. Teams that already moved to aggregate measurement are unaffected, while those rebuilding the old model gain only false confidence.
Jeff argues that server-side frameworks only move the collection point and don't change what marketers are permitted to see. With walled gardens blocking access and most of the journey already untrackable, he says measurement should shift to outcomes and aggregated data.
Jeff argues that Apple's latest announcement finishes off user-level tracking, following years of cookie deprecation and iOS changes. With most of the user journey now untraceable, he says marketers should stop chasing individuals and adopt aggregated data.
Jeff argues that using location data for targeting exposes marketers to privacy and national security risks, citing reports of U.S. troops being targeted. He says the belief that more data improves targeting is false, and context balances personalization with privacy better.
Jeff argues that marketers should stop chasing new platforms and instead master privacy-first data strategies. He says data is a privilege, that companies fail by ignoring this, and that adapting to tighter access matters more than strength.
Jeff argues that AI can produce valuable insights only when teams rebuild their attribution models rather than cling to legacy systems. He says AI platforms support real-time decisions and that privacy-first models are essential for compliance and trust.
Jeff argues that AI chatbots are changing how attribution works, with real-time insights and privacy-first models becoming essential. He warns that teams relying on legacy systems lose agility and should invest in real-time capabilities.
Jeff argues that AI is a transformation in marketing, not just a tool. He says real-time, privacy-compliant platforms offer a competitive edge, and that teams relying on yesterday's metrics will lose agility to competitors who adopt AI first.
Jeff argues that privacy rules are reshaping attribution and that marketers who keep outdated models will lose agility. He urges investing in AI-driven platforms that respect privacy while delivering real-time, precise attribution.