Dialoguedriven

Dialoguedriven is a term used in user experience, human–computer interaction, and interactive media to describe a design philosophy in which a conversational dialogue acts as the primary mechanism for user task completion and information retrieval. In a dialoguedriven system, the interface invites or requires user utterances and system responses to guide goals, actions, and feedback, rather than relying solely on menus or forms.

The term is informal and lacks a single standardized definition. It appears in UX literature, game design discussions, and AI research to emphasize conversation as the main interaction driver. It is commonly applied to chatbots, voice assistants, interactive fiction, education technologies, and customer support platforms.

Key characteristics include maintaining a structured dialogue state, using intent recognition and slot filling, and prioritizing clarifying questions to resolve user goals. Dialoguedriven designs address turn-taking, context management, graceful error handling, and accessibility considerations such as readability and inclusive language.

Benefits often include intuitive task flows, perceived responsiveness, and potential reductions in cognitive load. Challenges involve designing natural conversations, handling ambiguity, keeping context across turns, protecting privacy, and ensuring consistency across devices and channels.

Evaluation typically relies on task success rates, time to goal, user satisfaction, dialogue length, and error rates. Analysts may use usability testing, A/B experiments, and dialogue analytics to measure fluency, coherence, and user trust in the system.

Related topics include dialogue systems, conversational design, interactive fiction, and user experience research.