Bots with the customers into three categories. Self service conversation – the user successfully gets the queries answered by the bot agent transfer conversation – the conversation is transferred to a live agent drop-offs – the conversation is not. Completed and ended abruptly (due to technical error/user did not respond/bot could not identify the intent) the containment metrics allows. The users to get a detailed break-up of the conversations over a specific time period. These metrics can be used to get insights about the trends of self-service, drop-offs. And agent transfer conversations. Containment metrics also provide detail on the level of bot engagement.
As a part of the engagement analysis
Dashboard we can see the percentage of the. Total conversation with respect to the duration of the conversation, no. Of messages exchanged, and also the no. Of tasks completed. Moreover, the parameters can be further customized (using the horizontal slider) for deeper analysis. Containment metrcis gif (1) containment metrics Jamaica Business Email List feature of kore.Ai virtual assistant platform ver 8.0 containment metrics come in handy for quick analysis of the successful implementation of the virtual assistants. This users who wish to showcase the progress of a. Conversational ai project and analyze the improvements in the va’s performance.
Natural language processing
The new version enables users to have better control. While customizing the machine learning (ml) models. At the time of training the virtual assistants, the users can configure the hyperparameters to customize the natural language processing (nlp) models. They have the option to choose the type of neural networks (cnn/ word embeddings/ lstm etc Fjlists depending upon the bot tasks. Thus choosing the right type of algorithm. Specific to the use cases will further improve. The accuracy of the bots and enable them to tailor their response according to the conversation. The developers are also given an option to choose. Between the n-gram approach.
