Kevel, a pioneer in API-first ad serving, has launched Kai (Kevel Artificial Intelligence), a cutting-edge suite of AI and machine learning technologies aimed at transforming the retail media industry. Integrated into the Retail Media Cloud™ platform, Kai is designed to optimize performance, increase relevancy, and enhance profitability for retail media networks through its innovative features: Forecast and Custom Relevancy.
Forecast leverages advanced machine learning to simulate and predict inventory and campaign performance, offering a more accurate projection by considering contextual and user audience targeting parameters alongside pacing factors. This departure from traditional methods that rely solely on historical data marks a significant leap forward in campaign planning and optimization.
Custom Relevancy introduces a 'bring your own model' approach, allowing retailers to integrate their proprietary AI/ML algorithms into Kevel's Ad Server. This feature empowers retailers to apply their unique insights and models to determine ad relevance, customizing the ad stack to meet specific network performance needs.
The development of Kai was led by Kevel's distinguished AI/ML research team, including CTO Tim Ewald and experts Paul DeGrandis, Richard Carter, and Paulo Cunha. Their collaboration has resulted in a suite that significantly advances ad serving and audience segmentation capabilities for retail media.
Paulo Cunha, Retail Media Cloud GM at Kevel, highlighted the innovative nature of Forecast, noting its ability to provide advertisers with precise future performance insights and enable retailers to maximize inventory yield. Tim Ewald, CTO, emphasized the transformative potential of Custom Relevancy, which allows retailers to influence ad serving with their AI-driven optimizations, enhancing the user experience on a per-user basis.
Kai also integrates existing Kevel features like ad decisioning and pacing, which utilize a mix of historical data, user behavior, context, and relevancy scoring to improve ad performance. This comprehensive approach underscores Kevel's commitment to delivering a holistic solution for retail media networks.
The launch of Kai is timely, as the retail media sector evolves rapidly, with more companies aiming to develop their ad platforms to compete with giants like Amazon. Kevel's innovative technology positions it as a crucial enabler for retailers, marketplaces, and e-commerce companies looking to launch advanced ad formats and targeting segments, both online and in-store, with closed-loop attribution.
As retail media continues to expand, solutions like Kai are expected to be instrumental in helping retailers optimize their ad inventory and offer greater value to advertisers. The ability to deliver highly targeted and relevant ads through advanced AI and machine learning models could revolutionize retail media campaigns, potentially altering the digital advertising landscape for retailers and brands.
With Kai, Kevel is not only meeting current market demands but also paving the way for future innovations in retail media technology. Richard Carter, Principal Data Scientist at Kevel, hinted at more groundbreaking features in development, signaling Kevel's ongoing leadership in driving advancements that could redefine digital asset monetization and advertiser engagement in the retail sector.
