AN AFFINSYS PRODUCT
Why traditional surveys fall short
Static surveys often interrupt the journey, take time to complete and generate limited context. Digital interactions are dynamic, so feedback collection should be conversational, relevant and timed to the customer journey.
AI-powered conversational surveys
Conversational surveys can combine quantitative metrics such as CSAT, CES and NPS with qualitative responses. Machine learning, NLP and text analytics can organize the feedback and surface recurring themes, sentiment and friction points.
Quantitative feedback
CSAT can measure satisfaction with a specific interaction, CES can measure the effort required to resolve an issue, and NPS can indicate advocacy. Tracking these measures over time helps teams identify changes in experience quality.
Qualitative feedback
Open-ended, exit and churn questions reveal why customers feel a certain way. Sentiment analysis can distinguish positive, neutral and negative responses and highlight language associated with frustration.
Where conversational surveys help
- Agent performance after a live handoff.
- Channel performance across web, social, messaging and voice.
- Virtual assistant performance and unresolved intents.
- Product and journey feedback after onboarding or claims.
How Agentic AI elevates this use case
Agentic AI can treat feedback as an operational signal. It can identify the issue, reason about its likely cause, prioritize the most important intervention, create a task for the right team, and measure whether the change improved the next customer interaction.