True or false: When building and optimizing chatbots, you will need to work with both qualitative and quantitative data.

True. Optimizing chatbots requires both qualitative and quantitative data. Quantitative data, such as conversation volume, completion rates, and error rates, provides measurable insights into chatbot performance and identifies areas for improvement. For example, a low completion rate for a specific task indicates a problem. Qualitative data, gathered from user feedback, transcripts of conversations, and sentiment analysis, offers deeper understanding into why users are struggling or what their unmet needs are. This helps refine chatbot responses, improve natural language understanding, and enhance the overall user experience. Without both types of data, optimization efforts would be incomplete, as quantitative data tells you what is happening, while qualitative data tells you why.