Enhancing customer experience with virtual agents and chatbots
A defining feature of modern virtual agents and chatbots is their ability for continuous learning and adaptation, powered by advanced ML algorithms. This attribute ensures that they not only respond to customer inquiries but also evolve from each interaction, becoming more nuanced and effective over time. Next, we will address key aspects of virtual agents and chatbots, including the mechanics of continuous learning, feedback loops and data analysis, training, real-time performance adjustments, and integration of human feedback.
The mechanics of continuous learning
Virtual agents and chatbots are built on ML models that thrive on data. Each customer interaction is an opportunity for these models to learn and improve. For instance, when a chatbot successfully resolves a customer’s query, this outcome feeds back into the system, teaching the model about effective responses. Conversely, if a query is escalated...
