Using AI to Detect When Your Campaign Needs a Refresh
Discover how artificial intelligence can help you anticipate performance decline and optimize advertising campaigns before KPIs start to drop in the masterclass “Proactive Optimization: Using AI to Detect When Your Campaign Needs a Refresh,” led by Dmytro Kyiashko, Software Developer in Test and AI systems testing expert with over 10 years of experience in IT.
During this session, Dmytro will demonstrate how AI-driven analysis can identify early warning signals such as creative fatigue, audience saturation, and efficiency loss, and how these signals can guide timely decisions on creative rotation, budget reallocation, and bidding strategy adjustments. The focus will be on moving from manual, reactive monitoring to predictive, AI-assisted optimization across modern advertising platforms.
Participants will learn how AI models analyze multiple performance metrics in combination, uncover hidden dependencies between indicators, and notify teams when campaigns require validation, refresh, or pausing to prevent inefficient spend. The masterclass will feature practical frameworks and real-world cases illustrating how proactive optimization improves control, scalability, and return on ad spend.
Whether your goal is to reduce wasted budget, improve ROAS, or build a more resilient performance marketing process, this masterclass will provide actionable insights and applied approaches to using AI for smarter campaign management.
Date: November 3rd 2023 Time: 12:00 (UTC-5) Location: Online (link will be sent to those who have registered for the masterclass)
Masterclass by Dmytro Kyiashko, AI systems testing expert
Dmytro Kyiashko brings a strong engineering perspective to the topic of campaign optimization, combining hands-on experience in system quality assurance with a deep understanding of how complex, data-driven platforms behave at scale. Over more than a decade in IT, he has worked extensively on building and leading engineering teams, designing testing strategies, and validating high-load systems where accuracy and timing are critical.
His recent work has focused on evaluating AI-based systems used in decision-making environments, particularly those where delayed or incorrect signals can lead to financial inefficiency. This background allows Dmytro to approach advertising optimization not from a marketing theory standpoint, but from the perspective of system behavior, signal reliability, and risk control.
In addition to his engineering practice, Dmytro has contributed as an expert juror at UAtech Venture Night (Web Summit Vancouver), assessing technology startups in front of international investors and technical leaders. He is also the author of a research paper on testing challenges in multimodal AI-agent-based systems and has been recognized for reviewing academic work at international scientific conferences.
Masterclass Program: “Proactive Optimization: Using AI to Detect When Your Campaign Needs a Refresh”
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