Chatbots Chatbot Analytics and Performance 2

Question 1

What does 'average handling time' (AHT) measure when applied to chatbot performance?

Accepted Answer

The average duration of a complete chatbot conversation from start to resolution

Answer

Server processing speed

Answer

Monthly infrastructure cost

Answer

Number of concurrent users

Question 2

Why is 'session abandonment rate' an important chatbot metric?

Accepted Answer

It shows where in the conversation flow users give up, revealing pain points in UX or NLP coverage

Answer

It measures API reliability

Answer

It tracks developer activity

Answer

It counts system reboots

Question 3

What tool is commonly used to visualize chatbot conversation flow data for analytics?

Accepted Answer

Sankey diagrams or funnel charts that show how users flow through conversation paths

Answer

Word processors

Answer

Spreadsheet pivot tables only

Answer

Network topology maps

Question 4

What is 'A/B testing' used for in chatbot optimization?

Accepted Answer

Comparing two versions of a bot response to determine which drives better user outcomes

Answer

Testing two server configurations

Answer

Alternating between two NLP providers

Answer

Splitting database traffic

Question 5

Which analytics practice helps identify the most common user intents to prioritize training improvements?

Accepted Answer

Analyzing fallback logs and intent frequency distributions to find high-volume unhandled topics

Answer

Monitoring server CPU graphs

Answer

Reviewing API error codes

Answer

Checking database index fragmentation

Question 6

What does 'CSAT score' measure in the context of chatbot analytics?

Accepted Answer

Customer Satisfaction — a user-reported rating of their chatbot experience, usually collected post-conversation

Answer

Server reliability

Answer

Conversation speed

Answer

Training data quality