The UI of Chatbots: Part 3 Core design principles

Core design principles

Whichever interface you choose for your chatbot, the core principles of good information design must be considered if it’s to be a success. The key ones are clarity and consistency, contextual relevance, progressive disclosure, accessibility, and user control and transparency.

Clarity and consistency

The chatbot should be clear and consistent. Clarity means users should immediately understand how to interact with the chatbot. Consistency means aligning the chatbot design with overall application design and patterns.

Contextual relevance

Contextual relevance means providing assistance based on user’s current task.

Progressive disclosure

Progressive disclosure is a design pattern that presents information gradually to users, showing only what’s necessary at each stage of an interaction. Think of it like peeling an onion – you reveal one layer at a time rather than overwhelming users with everything at once. It reduces cognitive load, prevents decision paralysis, makes complex tasks manageable, and improves completion rates.

The key principles of progressive disclosure in chatbot UI are:

1. Start simple
2. Drill down gradually
3. Show advanced options later

This image shows an example of progressive disclosure:

Accessibility

The chatbot should be usable by individuals with disabilities, such as providing voice commands for visually impaired users or compatibility with screen readers. In addition, you might want your chatbot to be able to handle multiple languages, dialects, and varying levels of literacy.

User control and transparency

Users should have the ability to control when the chatbot appears. Too frequent or unsolicited pop-ups can be intrusive and annoying.

Clear purpose

Ensure the chatbot has a specific role, such as troubleshooting, offering hints, or directing users to the correct resources. A broad, unclear chatbot can frustrate users.

User testing and feedback loops

Continuous user feedback is vital. Conduct regular usability tests to understand how users interact with the chatbot and refine it accordingly. This way you can measure the effectiveness and identify the success metrics for the project.

See also

Part 4: How it might affect what you write

Part 2: Balancing assistance approaches

Using Generative AI in Technical Writing