Kevel Unveils Kai: A Game-Changer for Retail Media Networks

By Advos

TL;DR

Gain a competitive advantage with Kevel's new AI feature set, Kai, for performance optimization and maximized share of advertiser budgets.

Kevel's AI suite, Kai, uses machine learning to forecast inventory and campaign performance, and allows for custom relevancy targeting.

Kevel's Kai AI feature set aims to make retail media networks more profitable, relevant, and efficient for both advertisers and retailers.

Kevel's new AI feature set, Kai, introduces unique features like Forecast and Custom Relevancy, showcasing the power of machine learning.

Found this article helpful?

Share it with your network and spread the knowledge!

Kevel Unveils Kai: A Game-Changer for Retail Media Networks

Kevel, an API-first ad serving company, has launched its latest innovative feature set, Kai (Kevel Artificial Intelligence). This suite of AI and machine learning technologies aims to elevate performance optimization, relevance, profitability, and revenue for retail media networks. Kai is integrated into Kevel's Retail Media Cloud™, a SaaS platform designed for building retail media networks with ad serving capabilities that optimize advertiser budgets.

The development of Kai was overseen by Kevel’s AI/ML research group, led by CTO Tim Ewald, Sr. Director of Research and W3C member Paul DeGrandis, Principal Data Scientist Richard Carter, PhD, and Retail Media Cloud™ GM and Velocidi founder Paulo Cunha. The group brings decades of combined experience in AI, which has culminated in creating this advanced suite of AI features aimed at enhancing ad serving and audience segmentation for a superior retail media experience.

Among the new features that Kai introduces are Forecast and Custom Relevancy. Kevel Forecast employs machine learning simulations to predict inventory and campaign performance for both current and future campaigns, providing insights that traditional tools, which rely solely on historical data, cannot. This unique approach considers all contextual and user audience targeting and pacing parameters in conjunction with other running or future ads, allowing advertisers to gain a clearer view of their future performance and enabling retailers to maximize their inventory yield.

Retail Media Cloud GM Paulo Cunha elaborated on the innovation:

Curated from News Direct

blockchain registration record for this content
Advos

Advos

@advos