Contextual Assistance
Problem
Users often need guidance but may not know what to ask for or when to ask. Traditional help systems require users to interrupt their workflow to search for assistance.
Solution
Create intelligent assistance that proactively offers relevant help, suggestions, or information based on the user's current context, behavior patterns, and needs. The system should anticipate user requirements rather than waiting for explicit requests.
Examples in the Wild
Google Smart Compose
Predicts and suggests text completions while typing emails, based on the email context and common phrases.
Interactive Code Example
Smart Text Editor with Contextual Suggestions
This React component implements a text editor that offers contextual suggestions based on what the user is typing. It uses a debounce function to prevent too many API calls and maintains clear user control over accepting suggestions.
Toggle to code view to see the implementation details.
Implementation & 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