Analytics Value of AI in Software as a Service Idea

Software as a Service (SaaS) uses economies of scale and cloud computing infrastructure to help customers buy, use, and pay for software

Application analytics collects and analyses real-time usage and performance data for SaaS, mobile, desktop, and web applications

App performance analytics can identify app, server, and network issues and show response times and failure rates to assess app performance across the network

SaaS provides cloud-native software, but AI and ML turn SaaS app data into actionable insights

AI and ML models like regression analysis, neural networks, and decision trees anticipate future events based on historical data

Predictive analytics features are available in the majority of SaaS analytics platforms, such as Google Analytics, Microsoft Azure, and IBM Instana

SaaS machine learning models can dynamically customise the information that users see based on real-time data by leveraging user interaction data, historical trends, and customer preferences