LogRocket Launches Galileo, A Machine Learning-Based Solution to Automatically Surface Most Important Issues to Improve Digital Experience. Galileo uses machine learning algorithms that have been trained on billions of real user sessions with nearly one trillion interactions and hundreds of thousands of manually triaged issues from years of real-world data to assist you in finding the signal in the noise. It provides the context you need to rapidly address the most pressing issues as well as the information you need about the digital experience. After being integrated into your application, Galileo keeps track of hundreds of user interactions per session and alerts you to simple problems that have been shown to have adverse effects in critical areas. Additionally, it evaluates each issue’s potential business impact, such as if it would affect 10% or 0.01% of users or result in user attrition.
Use cases examples
- With the aid of LogRocket Galileo, Copa Airlines could identify and resolve pricey problems with their online booking system that hindered customers from making reservations.
- Cox Automotive utilizes LogRocket Galileo to make sure it focuses on problems and improvements that will improve the user experience the most.
Systems get noisier as more data is added every day. Engineers frequently receive hundreds of false-positive alarms, have to manually identify the issues producing them, and struggle to determine whether a problem genuinely has a large and widespread user impact. Product teams might see a decline in their conversion rate, a decline in activation, or a decline in their NPS scores, but there may not be an obvious connection as to the cause. Due to all of this, critical issues are missed for days or even weeks, resulting in millions of dollars in lost income or dissatisfied users.
By highlighting the greatest chances to enhance business outcomes, Galileo cuts through this noise and assists the entire software team in ensuring exceptional digital experiences.
Prathvik is ML/AI Research content intern at MarktechPost, he is a 3rd year undergraduate at IIT Kharagpur. He has a keen interest in Machine learning and data science.He is enthusiastic in learning about the applications of Machine learning in different fields of study.
