How does ECI support improving chatbot performance?

The correct answer is based on the concept of iterative learning processes. ECI, or Enhanced Customer Interaction, supports improving chatbot performance by leveraging customer interactions to inform and refine the chatbot's responses and capabilities over time. As the chatbot engages in conversations, it collects data about user inquiries and reactions, which can be analyzed to identify patterns and areas for improvement.

This continuous feedback loop enables the chatbot to adapt and become more effective at handling queries, thus enhancing the overall customer experience. By learning from real-world interactions, the chatbot can adjust its algorithms, update its knowledge base, and improve its ability to understand and respond accurately to customers.

In contrast, the other options do not effectively contribute to improving chatbot performance in the same way. Providing human agents for each conversation wouldn't enhance the chatbot's capability but rather shifts burden away from it. Analyzing manual transcripts, while potentially useful, does not facilitate the real-time adaptive learning that iterative processes offer. Limiting customer interactions with chatbots would hinder their development and reduce their utility in customer service scenarios.