Proactive chatbots set the stage for success. They reveal their capabilities upfront, guiding users towards successful outcomes, and are essential for effective chatbot design.
Cut through the LLM hype! Learn the 4 practical ways to use AI in chatbots: extraction, classification, transformation, and generation. Understand their strengths and risks for building better conversational apps.
Ensuring proper communication is critical — don’t let a chatbot fail to chat! Bots must strike a balance between confirming user information and proceeding with a reasonable assumption of correctness. Explicit and implicit confirmations are the primary tools to achieve this balance.
Like any software project, building a chatbot requires careful planning. While all software projects fall along the Waterfall-Agile spectrum. I believe chatbot projects should lean closer to the Agile end, emphasizing rapid prototyping and iteration over extensive upfront planning. This post draws on my experience with numerous chatbot projects and outlines what successful teams have done at the start.
You never get a second chance to make a first impression. Chatbots are no different, and the first interaction with users sets the tone for the entire user experience. When crafting this initial message, I recommend to keep the 3 C’s in mind.