Walkthroughdetektorer

Walkthroughdetektorer is a term used in software design to describe a class of interactive onboarding and guidance systems that detect user progress and trigger contextual walkthrough steps. They are designed to reduce learning time and increase feature adoption by guiding users through workflows that match their current context.

Core components of a walkthroughdetektor typically include a detection layer that collects events and state information, an orchestration engine that sequences and conditions the steps, a content library of walkthrough screens and prompts, analytics and telemetry for measuring effectiveness, privacy and consent controls, and integration adapters for various platforms and frameworks. Together these parts enable guidance to appear at appropriate moments, rather than as a static tutorial.

Operation generally involves the detector subscribing to user actions such as clicks, navigations, and feature usages, then determining the user segment or state. When criteria are met, a relevant guided tour is activated. Tours can be linear or branching, and the system often saves progress to allow resumption across sessions or after interruptions.

Common use cases include onboarding new users, revealing advanced features to experienced users, compliance or safety trainings, and facilitating troubleshooting. Benefits include improved feature discovery, higher task success rates, and reduced support loads. Limitations involve the need for instrumentation and ongoing maintenance, potential performance considerations, and the risk of being perceived as intrusive if overused. Privacy considerations and opt-out options are important, as is ensuring accessibility and localization.

See also: onboarding, in-app guidance, product tours, contextual help.