Zefr Expands Pre-Impression Content Avoidance for Meta Feed and Reels, Now Globally Available

Today (13th February, 2025), Zefr announced the expansion of its pre-impression content avoidance controls on Meta, which allows advertisers to refine their content adjacencies while maintaining scale across their Meta activities, with full transparency into where their ads were served. This expansion is now globally available for all Zefr clients as part of its Zefr Max product, which maximises protection and performance in social platforms.

Building on Meta’s Expanded Controls

This expanded capability builds upon Meta’s first-party Inventory Filters, which help advertisers maintain brand suitability on the platform. Zefr’s new pre-impression content avoidance controls introduce custom advertiser brand suitability through customizable blocklists and real-time optimisations.

How It Works

Zefr’s pre-impression solution uses Zefr’s AI and human-in-the-loop process, which has been patented for walled garden effectiveness, to accurately classify content for pre-impression blocking and post-bid transparency. Advertisers can customize exclusions by risk level, or create custom block lists for real-time events and brand-specific concerns.

Transparency and Measurable Impact

Advertisers benefit from real-time transparency dashboards, enabling detailed visibility into performance metrics and blocked content lists, as well as providing explainability for Zefr’s AI decisioning. Zefr’s AI continuously refines exclusions, ensuring ongoing optimisation and alignment with campaign goals.

A Future-Proof Approach to Brand Suitability

Zefr remains committed to helping advertisers navigate the complexities of online content adjacency. As social media continuously evolves, Zefr’s partnership with Meta better ensures that brands are always equipped with cutting-edge tools to stay protected and aligned with their values.

To learn more about Zefr’s Risk Optimisation capabilities for Meta, contact ai@zefr.com or visit

zefr.com/zefrmaxdemo.