Health checks

Proactive monitoring routines to keep your agent running smoothly.

Regular health checks help you catch issues before they impact customers.

Smart Analyst can accelerate every routine below. Its deep sampling analyzes up to 500 conversations per query — use it to surface patterns, identify failure reasons, and prioritize fixes without manually reviewing calls.

Schedule overview

Routine	Frequency	Time required	What to check
Daily check	Every day	10-15 min	Dashboards, recent errors, handoff rate
Weekly review	Every week	30-60 min	Trends, unhandled queries, sample calls, test sets
Monthly deep dive	Every month	2-4 hours	Month-over-month metrics, knowledge audit, function optimization
Pre-deployment	Before each promotion	20-30 min	Test sets, manual testing, integration checks
Post-deployment	After each promotion	30 min	Live calls, key metrics, function logs

Daily check

Spend 10-15 minutes each morning:

1. Review the Standard dashboard — check call volume, handoff rate, and latency against your baseline
2. Scan recent errors in Analytics > Conversations filtered to last 24 hours
3. Spot-check handoff reasons for new patterns — or ask Smart Analyst: “What are the top handoff reasons from the last 24 hours?”
4. Verify integrations — look for API errors in function logs

Red flags

Stop and investigate if you see:

• Handoff rate > 50% (or 20% above baseline)
• Average latency > 3 seconds
• Error rate > 5%
• Call volume drop > 30%

Weekly review

Spend 30-60 minutes each week:

1. Compare this week’s metrics to last week (call volume, containment, duration, latency)
2. Review unhandled queries in dashboards — prioritize knowledge gaps
3. Run a Smart Analyst deep sampling query to surface trends across hundreds of conversations at once — for example: “What are the top 5 reasons calls are handed off this week?” or “What knowledge gaps are causing containment failures?”
4. Listen to 5-10 calls flagged by Smart Analyst (mix of successful and unsuccessful)
5. Check test set results for regressions
6. Plan improvements for the following week based on Smart Analyst insights and test results

Monthly deep dive

Spend 2-4 hours at month end:

1. Compare all key metrics month-over-month
2. Use Smart Analyst deep sampling for a comprehensive analysis — sample up to 500 conversations to break down containment by handoff reason, identify recurring failure patterns, and surface sentiment trends. Try: “Analyze the top transfer reasons and containment blockers over the last 30 days with percentage breakdowns.”
3. Audit all Managed Topics for outdated content — use Smart Analyst to identify knowledge gaps: “What questions are we not handling well?”
4. Review function performance — optimize or refactor slow functions
5. Maintain test sets — add new scenarios, remove obsolete ones
6. Review version history — document major changes

Pre-deployment check

Before promoting any version to Pre-release or Live:

1. Run all test sets — investigate any failures before promoting
2. Manually test critical user journeys and edge cases
3. Test all external API integrations
4. Check voice quality and pronunciations
5. Compare to the current Live version using diffs
6. Have a rollback plan ready (identify last known good version)

Promote if: All tests pass, no critical bugs, performance is acceptable. Do not promote if: Test failures exist, performance degraded, or integrations are failing.

Post-deployment monitor

After promoting to Pre-release or Live:

First 30 minutes:

• Watch Conversation Review in real time
• Monitor latency, error rate, and handoff rate
• Verify function logs show no errors
• Be ready to rollback

First 24 hours:

• Check metrics every 2-4 hours against baseline
• Review handoff reasons for new patterns

First week:

• Analyze full week of data vs. pre-deployment baseline
• Document lessons learned

Rollback triggers

Rollback immediately if:

• Error rate > 10%
• Handoff rate doubles
• Critical function failures
• Customer complaints spike

Tips

• Start small — if you can’t do everything, prioritize daily checks and pre-deployment checks (highest ROI)
• Let Smart Analyst do the heavy lifting — instead of manually reviewing calls, use Smart Analyst deep sampling to analyze hundreds of conversations in minutes. It’s especially effective for weekly and monthly reviews where you need to spot patterns across large volumes of data.
• Automate — use test sets for regression testing and the Alerts API for anomaly notifications
• Adjust frequency — high-volume or mission-critical agents need tighter monitoring; stable agents can relax the schedule