Systems and methods relating to generating simulated interactions for training contact center agents

A system for generating a customer bot and using the customer bot to train agents in a contact center, the system comprising:

• a bot generating module;
• an automated training module;
• at least one processor;
• and
• at least one memory comprising a plurality of instructions stored therein that, in response to execution by the at least one processor, causes the system to perform, via the bot generating module, a first process that generates the customer bot and a second process, via an automated training module, that uses the customer bot to train the agents;
• wherein the first process comprises the steps of:
• gathering conversation data, the conversation data comprising data derived from natural language conversations occurring in the contact center during interactions between the agents and customers;
• mining intents from the conversation data, wherein each mined intent comprises an intent label and a set of utterances associated with the intent label, the intent label identifying an issue found to be recurring within the interactions of the conversation data, and the set of utterances comprising utterances used to raise, discuss, or resolve the issue, wherein the utterances of the set of utterances comprise statements or phrases made by both the customers and agents;
• selecting one or more mined intents of the mined intents, the one or more mined intents selected based on a relatedness to an interaction type found within the interactions;
• constructing, from sets of utterances of the selected one or more mined intents, a dialog engine simulating the interaction type, the dialog engine defining a dialog flow for navigating the one or more issues associated with the selected one or more mined intents, the dialog flow including both customer-side statements and agent-side statements;
• generating the customer bot with the dialog engine, the customer bot being configured in accordance with the customer-side statements of the dialog flow so to mimic a customer;
• uploading the customer bot to the automated training module for use thereby to train the agents pursuant to the second process;
• and
• periodically repeating the previous steps of the first process so that the customer bot uploaded to the automated training module is updated with conversation data that has been gathered since a previous time of repeating the steps of the first process;
• wherein the second process comprises the steps of:
• monitoring for one or more triggering events that determine whether a first agent of the agents should receive training related to the interaction type;
• in response to detecting the one or more triggering events, initiating the training by initiating a virtual communication to a user device of the first agent;
• connecting the virtual communication to the customer bot in response to establishing a communication connection with the user device;
• conducting a simulated interaction of the interaction type by determining a scenario as a function of an evaluation of a performance of the first agent with respect to the interaction type in one or more previous interactions prior to the determination of the scenario and transmitting one or more customer-statements generated by the customer bot in accordance with the determined scenario to the first agent and receiving one or more statements made by the first agent in response thereto;
• analyzing the one or more statements received from the first agent to derive a performance assessment of the first agent.