Marianna Budnikova

In the tech industry, engineers typically focus on engineering metrics like reliability, performance, test coverage, and success rates when evaluating product health. Meanwhile, VPs of engineering and product are often more concerned with business-oriented metrics such as AAR (Average Annual Return) and MAU/DAU (Monthly Active Users/Daily Active Users). This narrow focus from both business and engineering perspectives can be limiting. In this talk, Marianna will explore how senior and staff software engineers can bridge this gap by integrating engineering and business metrics into automated scorecards. She will demonstrate how to leverage machine learning to predict the future trajectory of product health scores and introduce data analysis techniques that enable teams to self-correct before user churn escalates due to declining product quality, ensuring a more comprehensive and proactive approach to maintaining healthy and user-focused products.