The examination of patterns and activities of users, including Non-Human Identities (NHIs), to understand interactions and improve systems.
Description
User behavior analysis refers to the systematic study of how users, including both human users and Non-Human Identities (NHIs) such as bots, algorithms, or automated systems, interact with digital platforms and services. In the context of NHIs, this analysis focuses on understanding how these entities behave in various online environments, including their patterns of engagement, preferences, and decision-making processes. Analyzing user behavior helps organizations tailor their products and services to meet the needs of their users more effectively, optimize user experiences, and enhance engagement. By examining metrics such as click-through rates, session durations, and interaction frequencies, businesses can identify trends, predict future behaviors, and implement strategies that drive user satisfaction and retention. Additionally, distinguishing between human users and NHIs is crucial for accurate data interpretation and for developing targeted approaches in marketing, cybersecurity, and user experience design.
Examples
- Analyzing how a chatbot interacts with users to improve its response accuracy.
- Studying the behavior of automated scripts that scrape data from websites to detect malicious activity.
Additional Information
- User behavior analysis is essential for enhancing AI training datasets.
- It helps in detecting anomalies that may indicate security threats or misuse of services.
References
- Entro Security Labs Releases Non-Human Identities Research Security Advisory
- 2025 State of NHI and Secrets in Cybersecurity | Entro Labs
- The case for using non-human personas in design
- Sharing by Proxy: Invisible Users in the Sharing Economy
- What kinds of users are there? Identity and identity descriptions
- Final Report - The Identities Project
- Unique on Facebook
- Personas - USABLE Tools
- Graphika Report: A Revealing Picture