Chatbot Training: Enhance Your Customer Experience through Conversational AI
Chatbot training has evolved exponentially from a simple CX platform to advancements such as sentiment analysis, NLP, and machine learning. Chatbot training improves upon key user expectations and provides a personalized, quick customer request resolution with the push of a button.
significantly improves call center metrics with their seamless knowledge, ticketing, and identity management.
The more you train your chatbot, the better it gets. It is challenging to predict customer queries and train AI-assisted chatbots. Rigorous analysis of user data will bring accuracy in predicting customer queries and significantly enhancing chatbot performance.
Expert training can empower chatbots to handle unrehearsed customer queries that used to be transferred to support agents. A good resource available with chatbot might resolve impromptu queries.
A good chatbot identifies different syntax, style, and words that vary from person to person during training modules. A chatbot should be well-versed with identifying different user’s inputs.
It is important that the chatbot is able to store, retrieve, and interpret information based on requirements within seconds to deliver efficient outputs.
Simplify day-to-day customer engagement by understanding meaningful data from complex sentences fed as input into chatbots, satisfying customers from prospecting to closing.
Allow more time for relationship building and accurately match all utterances to make the chatbot understand customer intent.
Create custom intents for different user demographics for ordering medicine by showing prescription, lab equipment review reminders, and patient charts.
Leverage analytics, analysis, record saving for large databases, and information dissemination.
Measuring Customer Engagement with Chatbot Training
Net Promoter Score
Fall Back Rate (FBR)
Goal Completion Rate (GCR)
Why Choose Maxicus?
Streamlined chatbot training through:
Analyzing the existing chatbot
Customized solutions and workflows to create/validate data
We leverage our human experts and technology-assisted platforms to segregate data with different context and sources