Behavior analysis is a type of data analysis that tries to understand how and why people behave that way. Behavior analysis measures how consumers relate to digital applications (e-commerce, mobile, social media, gaming, IoT). Data such as demographics or past activities are collected to generate insights and predict future trends. The principles of behavior analysis are applied not only to the behavior of people, but also to the interactions and dynamics between processes, machines, equipment, and even macroeconomic trends.
Behavioral analytics combines typical event tracking with audience segmentation to associate users with triggered events and map customer journeys, using the large amount of raw data collected by the analytics platform.
Behavior Analysis is an important subset of business analytics that helps us understand how and — why — consumers and apps behave this way. It is particularly prevalent in e-commerce, online gaming, web, mobile and IoT applications — and provides the data needed to improve the customer journey towards transformation.
Behavior analytics measure data such as navigation paths, clicks, social media interactions, and purchase/cart abandonment. A/B testing is an example of using analytics to make data-driven decisions.
Augmented reality can be defined as a technology that enriches the real world environment with digital data. The basic principle of operation is the addition of digital content such as computer-generated audio, images, graphics, GPS data on top of the real world image that the user sees.
Predictive analysis, a type or extension of predictive analysis, is used to recommend or predict certain actions when certain information states are reached or conditions are met.
Large Language Models (LLMs) are artificial intelligence models trained with millions of parameters that can perform language understanding and generation from large amounts of textual data. These models are considered a revolutionary step forward, especially in the field of natural language processing (NLP).
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