realuse

Realuse is a term used in product design, data analytics, and human-computer interaction to describe the actual usage of a product, feature, or system in real-world conditions. It distinguishes real use from intended use or laboratory testing, focusing on how people interact with a system across diverse contexts and over time. The concept emphasizes functional outcomes, user workflows, and value realization rather than theoretical capabilities.

Measurement and data: Realuse is assessed with both quantitative and qualitative methods. Quantitative data comes from usage logs, telemetry, activation and retention rates, task completion, error rates, and time-to-first-use. Qualitative methods include field observations, in-situ interviews, and diary studies that illuminate motivations, friction points, and workarounds. Privacy, consent, and data governance are central considerations when collecting real-use information.

Applications: Realuse informs product roadmaps, usability improvements, and reliability engineering by revealing how features actually perform in the wild. It supports user research by validating hypotheses about typical workflows and constraints, and it can guide accessibility and inclusivity assessments by highlighting real-world barriers.

Limitations: Real-use data can be noisy and context-dependent, making it difficult to isolate causes of observed issues. Analyses must account for sampling bias, seasonality, and changing user bases. Ethical concerns and privacy protections are essential when collecting and processing real-use data.

Origins and scope: While not a formal standard, realuse is used across disciplines to encourage attention to real-world performance and user experience beyond controlled tests. It sits at the intersection of usage analytics, user behavior research, and product development practice.