An ecommerce company is using a generative AI chatbot to respond to customer inquiries. The company wants to measure the financial effect of the chatbot on the company’s operations.
This metric directly relates to the financial impact of the chatbot by quantifying the cost associated with handling each customer interaction. By comparing this cost to the previous cost of handling inquiries (e.g., through human agents), the company can assess the financial efficiency and effectiveness of the chatbot.
Average handled time (AHT) is a key metric for measuring operational efficiency impact.
- It directly correlates with operational costs (labor costs, system usage, etc.)
- It shows efficiency improvements that translate to financial savings
- It's a standard contact center metric that can be compared pre- and post-chatbot implementation
- Reduction in AHT directly shows cost savings through improved efficiency
- It captures the total financial impact better than just cost per conversation, as it factors in time savings which is a major component of operational costs
Answer: C. Cost for each customer conversation
To measure the financial effect of a generative AI chatbot on an ecommerce company’s operations, you want a metric that reflects the cost impact of each interaction. “Cost for each customer conversation” captures how much the company is spending per inquiry handled by the chatbot. This lets you directly compare the chatbot’s operational expenses versus human-agent costs or other support channels.
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