Best practices and user experience guidelines for building conversational interface using kAIron

By Revathi Ganesan
Updated on Apr 15 2024

There are a number of best practices and user experience guidelines that can be followed when building a conversational interface using Kairon. Here are a few:

  1. Starting with a clear goal:
    Before you begin building the interface, have a clear idea of what you want the user to accomplish. This will help you make design decisions that are aligned with the user’s needs.
  1. Keep it simple:
    The interface should be easy to understand and use, with minimal steps required to accomplish the user’s goal. Avoid using jargon or technical terms that may be confusing to the user.
  2. Use natural language:
    Design the interface to understand and respond to the user in a way that feels natural, using common language and sentence structures. This will help the user feel more comfortable interacting with the interface.
  3. Provide clear feedback:
    Let the user know when the interface has understood their input and when it is processing their request. Also, give clear error messages or guidance when the user input is not clear or not valid.
  4. Be flexible:
    Allow the user to correct or change their input, and offer alternative ways to achieve the same goal.
  5. Test and iterate:
    User testing is a critical step in the development process, as it allows you to validate your assumptions and identify areas for improvement. Iterate on the design based on user feedback until you have a polished, user-friendly interface.
  6. Use of pre-built intents and entities, which can greatly simplify the building process.
  7. Leverage analytics and monitoring feature to measure the performance of your conversational interface.

kAIron is a one-stop platform that follows all these guidelines and provides with the best interface compared to others. It is a Conversational Digital Transformation platform with the simplest interface.

kAIron focuses on technology that handles data pre-processing. These include developing knowledge graphs that can be used to generate questions, answers, and intents, as well as question augmentation automatically and leveraging relevant information for the agents in real time.

It also handles bot maintenance and post-processing, such as analytics and follow-up communications. Another amazing feature is that you can customize your bot to meet your specific requirements.

It’s also worth noting that Kairon might have its own documentation and guidelines for building conversational interfaces on top of best practices for general conversational AI.