Conversation Insights application delivers Inferred CSAT scores to measure service interactions, with underlying factors that improve CSAT actionability.
Traditional surveys often reflect extreme opinions and low response rates. Post-interaction feedback delays insights resulting in lagging indicators and lastly they lack actionable insight behind CSAT scores.
Inferred CSAT solves this by using AI to estimate CSAT for all conversations instantly, based on full conversation transcript. This eliminates bias and reliance on explicit survey feedback only. CSAT scores are generated immediately after the interaction enabling faster detection of issues and trends. CSAT factors like Resolution, Empathy, Effort, and so on explain user satisfaction or dissatisfaction, helping you to target improvements.
Inferred CSAT augments survey feedback with deeper AI-based score. Inferred CSAT framework provides an estimated score computed using AI in real time by analyzing the entire sequence of the conversation.
CSAT factors like Resolution, Confusion, Effort, Empathy, Next Steps, Frustration, Transfers, and Escalations provide explainability to the Inferred CSAT scores.
Natively integrated into AI Agent analytics. Other conversational analytics applications can also leverage the Inferred CSAT framework and Conversation Insights [sn_aci_insights] table linked to the Conversation [sys_cs_conversation] table to create adhoc dashboards and workflows.
- New
- Changed
- Fixed
- ACLs on some tables were changed to avoid failures in other apps, for example, External Content Connector crawl jobs.
- Removed
Requires one of the Now Assist products like Now Assist for ITSM, Now Assist for CSM, Now Assist for HRSD, and so on to be activated.