Definitions of the customer service quality assurance, automation, conversation intelligence, coaching and CX metrics terms that matter, explained simply. Each entry links to a full definition.
Automated & agentic QA
How quality assurance is being automated, and how to evaluate AI agents.
Auto QA, short for automated quality assurance, is the practice of scoring customer service conversations against a quality scorecard automatically, using software instead of a human reviewer.
Agentic QA is the use of autonomous AI agents to evaluate the quality of customer service conversations automatically.
Agentic AI is artificial intelligence that acts autonomously toward a goal, taking a series of steps and making decisions on its own without a human prompting each action.
An AI agent is autonomous software that handles customer interactions from start to finish, understanding the request, taking the needed actions, and resolving it without a human driving each step.
Ticket auto-scoring is the automatic grading of support tickets against a quality scorecard by software, rather than by a reviewer reading each one by hand.
LLM-as-a-judge is the practice of using a large language model to evaluate the quality of text or conversations against a set of criteria.
100% QA coverage, also called full-coverage QA, is the practice of scoring every customer service conversation against a quality scorecard rather than a small sample.
AI-powered quality assurance is quality assurance that uses artificial intelligence to score customer service conversations automatically against a quality scorecard.
Conversation intelligence
Understanding what happens across every customer conversation, at scale.
Conversation intelligence is software that automatically analyzes customer conversations across chat, email and voice to surface quality, sentiment, topics and coaching insights at scale.
Speech analytics is the automated transcription and analysis of voice calls, examining the words spoken, sentiment, silence and talk patterns to surface insight at scale.
Text analytics is the automated analysis of written text, such as support tickets, chats and emails, to extract topics, sentiment and intent at scale.
Sentiment analysis is the automated detection of the emotional tone of a conversation, classifying it as positive, negative or neutral from text or speech.
Conversation analytics is the analysis of customer conversations at scale to surface the topics, trends, quality and outcomes hidden inside them.
Voice of the customer, or VoC, is the practice of capturing and analyzing customer feedback and needs across every channel, then feeding it back into decisions.
Interaction analytics is the analysis of customer interactions across channels, including voice, chat and email, to surface quality, sentiment and trends.
Real-time agent assist is software that guides a support agent live during a conversation, offering suggested responses, next-best steps and relevant knowledge as the interaction unfolds.
Quality assurance
The building blocks of a customer service QA program.
Quality monitoring is the ongoing practice of reviewing customer service conversations against a defined set of standards to measure how well agents are performing and where to improve.
QA calibration is the process of having multiple reviewers score the same customer service conversation and then compare their results, so everyone applies the quality scorecard the same way.
A QA rubric is the structured set of criteria used to score a customer service conversation, defining exactly what is evaluated and how much each criterion counts toward the total.
A quality monitoring form is the structured scorecard a reviewer uses to evaluate a single customer service conversation against agreed criteria.
A QA analyst is the person in a customer service team responsible for reviewing conversations against a quality scorecard and turning what they find into feedback and improvement.
Coaching
Turning quality data into better agent performance.
Agent coaching is the ongoing process of helping customer service agents improve their performance through specific, individualized feedback.
A coaching framework is a repeatable structure that guides how a manager runs a coaching conversation.
CX metrics
The customer service metrics that measure quality, satisfaction and effort.
CSAT, or Customer Satisfaction Score, is a metric that measures how satisfied a customer is with a specific interaction, product, or service.
NPS, or Net Promoter Score, is a metric that measures customer loyalty by asking how likely someone is to recommend a company on a scale of 0 to 10.
CES, or Customer Effort Score, is a metric that measures how much effort a customer had to put in to get their issue resolved or their request handled.
First Contact Resolution (FCR) is the percentage of customer issues that are fully resolved in a single interaction, with no follow-up, callback, or repeat contact needed.
Average Handle Time (AHT) is the average total time an agent spends on a single customer contact, including talk time, hold time, and after-call work.
First Response Time (FRT) is the amount of time between a customer reaching out and receiving the first human reply to their request.
CSAT, NPS and CES are three customer experience metrics that answer different questions.
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