AI Chatbot Metrics to Track Better UX

Companies are rapidly using Chatbots today to encourage excellent customer interactions. The result of advanced technology is an AI Chatbot, which is quickly proving to be the future of marketing. Nevertheless, Chatbot formation and deployment are not enough. Monitoring the bot’s efficiency using precise metrics is crucial.

Recent research by Botanalytics found that only one interaction engages about 40 percent of people communicating with an AI Chatbot. Therefore, to provide a quality user experience, there is a need to optimize the Chatbot. If we monitor the performance of these Chatbots using unique metrics, we see much vulnerability they are susceptible to.

Due to their conversational nature, conventional metrics can not be used for assessing the success of a Chatbot. Bot analytics organizations have come up with some metrics that are acceptable to assess their performance.

Most Useful AI Chatbot Metrics

  • Number of users
  • Active and engaging sessions
  • Retention metric
  • Confusion triggers
  • Conversation steps


The above-mentioned Chatbot metrics help developers achieve the primary objective of a Chatbot, which is to provide users with the best possible experience. Using appropriate metrics to track the performance of the bot will prove to be an extremely informative experience. They will also increase the usability of the bot, thus allowing companies to extend their scope and tap into a new audience base.