Chatbots Cheat Sheet 2026

The 30 highest-yield Chatbots facts, distilled from real exam questions. Print it, save it as a PDF, or study it here — free, no sign-up.

1. Which approach combines retrieval of documents with generation for accurate answers? → RAG (Retrieval-Augmented Generation)
2. Why is continuous testing important for chatbots after launch? → To catch errors and improve responses as usage grows
3. Which metric measures the share of conversations the bot resolves without a human? → Containment (deflection) rate
4. Which type of chatbot follows predefined decision-tree paths rather than learning? → Rule-based chatbot
5. What is a 'quick reply' button in chatbot UI design? → A pre-defined response option users can tap to speed up interaction
6. What role does a 'message broker' play in high-scale chatbot architectures? → Decoupling message intake from processing to ensure reliability under high traffic loads
7. What is 'sentiment analysis' used for in chatbots? → Detecting the emotional tone of a user's message
8. What is the primary business driver for deploying customer service chatbots in US enterprises? → Reducing support costs by automating high-volume, repetitive inquiries at scale
9. What is a 'context' in a chatbot conversation? → Information remembered to keep the dialogue coherent
10. Which best describes a chatbot 'persona'? → The consistent personality and tone the bot presents
11. What is 'error recovery' in chatbot design? → Providing helpful guidance when a user's input cannot be understood
12. What is 'A/B testing' used for in chatbot optimization? → Comparing two versions of a bot response to determine which drives better user outcomes
13. What role does an API play in chatbot functionality? → It connects the chatbot to external services and data
14. What is a 'slot' in slot-filling chatbot design? → A required piece of information the bot must collect
15. Joseph Weizenbaum defined ELIZA as the first _______-based chat program. → NLP
16. In chatbot design, what is an 'intent'? → The goal or purpose behind a user's message
17. Do all chatbots utilize artificial intelligence (AI) as a foundation? → False
18. What is 'sentiment analysis' used for in chatbot platforms? → Detecting the emotional tone of user messages to adapt bot responses accordingly
19. What is 'training data' for a chatbot? → The examples used to teach the model how to respond
20. Which chatbot type can understand context and free-form language best? → AI-powered conversational chatbot
21. Which messaging concept lets a chatbot remember earlier parts of a conversation? → Context
22. Which is a common channel where chatbots are deployed? → Messaging apps and websites
23. Why should chatbots always disclose that they are bots when directly asked? → It builds trust and is required by FTC guidelines in the US
24. What does 'average handling time' (AHT) measure when applied to chatbot performance? → The average duration of a complete chatbot conversation from start to resolution
25. Which compliance standard is most relevant for chatbots that handle credit card payment information? → PCI DSS (Payment Card Industry Data Security Standard)
26. What is the purpose of an 'NLU engine' in a chatbot architecture? → To parse user text into structured intents and entities the bot logic can act on
27. What is 'intent recognition' in NLP-powered chatbots? → Identifying the goal or purpose behind a user's message
28. What is an 'intent' in chatbot design? → The goal a user wants to achieve with a message
29. What is the benefit of giving a chatbot 'guardrails'? → To restrict unsafe or off-topic responses
30. What is a 'multi-turn' conversation in chatbots? → An exchange spanning several back-and-forth messages