TOPIC
With third-party cookies on the way out and stricter privacy regulations, marketers are rethinking how they measure and attribute success. Traditional tracking is getting harder, yet demonstrating ROI remains a top priority. How can marketers adapt attribution models when faced with data gaps? How can marketing teams leverage AI and machine learning to predict customer behavior or campaign outcomes? How can leaders elevate their team’s data literacy and ensure that employees at all levels can interpret and act on analytics insights?
Themes
With traditional tracking methods evolving, marketers are turning to new platforms, technologies, and AI-driven tools to measure and optimize campaigns. Which tools and platforms are proving most reliable for cookieless tracking and attribution? What practical steps can marketing teams take to implement these tools effectively across their organizations? How can marketing teams integrate multiple tools and technologies to create a cohesive, end-to-end analytics strategy?
As privacy regulations tighten and third-party cookies disappear, marketers must find ways to collect, analyze, and act on data without compromising customer trust. What are the most effective first-party and zero-party data strategies to replace traditional tracking methods? How can marketing teams balance personalization with privacy to maintain customer engagement? What metrics and KPIs best demonstrate ROI when data collection is limited by privacy constraints?
As brands gather more customer data, it’s critical to respect privacy while still delivering relevant, impactful experiences. Marketers must strike the right balance. How can organizations create ethical frameworks for data use without limiting marketing effectiveness? What strategies ensure transparency and build trust while still enabling personalization? How can marketing teams educate stakeholders and employees about ethical decision-making in analytics?