Read Transcripts and Threads
Conversation Analytics relies on the text of the conversation: - for calls: the transcript - for chats/emails/tickets: the message thread
Understanding how to read this content will help you interpret AI insights correctly.
Call transcripts (voice)
What you’ll usually see
- speaker labels (Agent / Customer)
- timestamps (optional)
- the spoken text
- sometimes: confidence indicators or redaction (depending on settings)
Practical tips
- Scan the opening and closing first. Many insights (CSAT, outcome, next actions) are strongly influenced by the end of the call.
- Watch for transfers. A handoff can change the outcome; the transcript may show multiple agents.
- Look for resolution language. Phrases like “That fixed it”, “Thanks”, or “I’ll have to call back” are key to satisfaction/outcome metrics.
Common transcript limitations
- Automatic speech recognition (ASR) can make mistakes (names, numbers, accents, overlapping speech).
- Very short calls often have too little evidence for reliable scoring.
- Background noise and crosstalk can reduce quality.
If something looks wrong, compare the transcript to any available audio playback (if your role has access).
Chat, email, and ticket threads (text)
In text channels, the AI typically analyzes the full thread (or a defined portion), including: - customer messages, - agent responses, - timestamps, - sometimes: internal notes (depending on your configuration).
Practical tips: - Confirm context: In tickets, a “conversation” may span hours/days. Insights may reflect the full thread, not one message. - Check for quoted content: Emails often include quoted prior threads; ensure you understand what content is new vs quoted.
Redaction and privacy
Your organization may redact sensitive data (PII/PCI). Redaction can: - improve compliance, - but sometimes reduce the evidence available for certain insights.
If redaction is enabled, treat: - credit card numbers, - addresses, - personal identifiers, as intentionally hidden and not "missing data".