Contextual Assistance
What is Contextual Assistance?
Contextual Assistance is an AI design pattern where systems proactively offer help based on user context and behavior, without waiting to be asked. Instead of interrupting workflows with generic tips, this pattern analyzes what users are doing right now and suggests relevant actions at the perfect moment. It's most effective for repetitive tasks, complex applications, and situations where AI can learn from patterns to predict needs. Examples include Gmail's Smart Compose finishing your sentences, search autocomplete guessing your query, and Notion suggesting relevant pages as you type.
Problem
Users need guidance but often don't know what or when to ask. Traditional help interrupts workflows.
Solution
Design intelligent assistance that proactively offers relevant help, suggestions, or information based on user context and behavior. Anticipate needs rather than waiting for explicit requests.
Real-World Examples
Implementation
AI Design Prompt
Guidelines & Considerations
Implementation Guidelines
Make assistance subtle and non-intrusive; don't interrupt the user's flow
Provide clear indications that suggestions are AI-generated
Allow users to easily accept, modify, or dismiss suggestions
Gradually improve suggestions based on user feedback and acceptance patterns
Offer ways to access more detailed help when contextual assistance isn't sufficient
Design Considerations
Balance between proactive help and avoiding unnecessary interruptions
Consider privacy implications of analyzing user behavior to provide contextual help
Ensure the system doesn't make assumptions that could frustrate users if incorrect
Provide transparency about why certain suggestions are being made
Include settings to adjust the frequency and type of assistance