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Answers for CX leaders

Direct answers to the questions CX, support and VoC teams ask about AI agents, customer feedback and the metrics behind them. Updated weekly.

3 answers · Updated November 2026

AI agents

Resolution, handover, testing and measurement for AI agents in customer service.

Voice of Customer

Turning reviews, tickets, surveys and calls into fixes someone owns.

CX metrics

CSAT, NPS, effort and resolution, and what the numbers really tell you.

Quality assurance

Scoring every conversation, human or AI, against your own rubric.

Pricing, ROI and rollout

What AI in customer service costs, returns and takes to go live.

Security and governance

Data, access, audit trails and the questions security teams ask.

Voice of Customer

How do you measure customer sentiment?

Score every conversation, call, chat, ticket, review, and comment as positive, negative, or neutral, then tag it by topic and journey stage. That's how to measure customer sentiment that teams can act on: calculate net sentiment per topic, track it against a baseline, and read the conversations behind any shift.

CX metrics

What is a good CSAT score?

A good CSAT score typically falls between 75 and 85 percent for transactional support, with anything above 85 percent considered strong, though that range is a convention rather than a fixed standard. What is a good CSAT score for your team depends on industry, channel, and contact reason, so your own trend matters more than any published benchmark.

Quality assurance

How do you improve call center agent performance?

You improve call center agent performance by running a loop: build a rubric tied to outcomes, score every conversation against it, calibrate reviewers, trace low scores to specific behaviors, coach using the agent's own calls, support them live, then re-score. Handle time stays context, not the target.