Author: Tanguy De Keyzer

Interaction analytics analyzes customer interactions across voice, chat and email to surface quality, sentiment and trends at scale. Here is how it works.

Voice of the customer (VoC) is capturing and analyzing customer feedback and needs across channels. Here is how conversation data strengthens it.

Conversation analytics analyzes customer conversations at scale to surface topics, trends, quality and outcomes. Here is how it works and where it fits.

Sentiment analysis automatically detects the emotional tone of a conversation, positive, negative or neutral, from text or speech. Here is how it works.

Text analytics is the automated analysis of written text such as tickets, chats and emails to extract topics, sentiment and intent for support QA and CX.

Speech analytics is the automated transcription and analysis of voice calls, examining words, sentiment and silence to surface insight at scale.

Conversation intelligence is software that automatically analyzes customer chat, email and voice conversations to surface quality and insight at scale.

AI-powered quality assurance uses AI to score customer conversations automatically against a scorecard, replacing manual sampling with full coverage.

100% QA coverage means scoring every customer conversation, not a 2% to 5% manual sample. Here is what full-coverage QA changes for teams.

LLM-as-a-judge uses a large language model to grade text or conversations against defined criteria. Here is how it works and why evidence matters.

Ticket auto-scoring is software grading every support ticket against your QA scorecard automatically, with each score linked to the evidence. Here is how.

An AI agent is autonomous software that handles customer interactions end to end. Here is how it works and why its quality still needs to be measured.