A recent Gong outage caused synchronization to stop for several days without any proactive notification to administrators. The connector remained in an "active" state even though meeting data was no longer being ingested. The root cause was eventually determined to be invalidated Gong credentials following the outage, but there was no visibility into this condition from within Gainsight.
As a result:
• Admins were unaware that synchronization had stopped.
• The connection appeared healthy despite being unable to retrieve data.
• There was no proactive alerting mechanism for systemic failures.
• Recovery required manual reauthentication even though the connection status never indicated a problem.
• Validation of missed records required manual reconciliation between Gong and Gainsight.
These gaps create operational risk and erode trust in the platform because customer-facing teams may unknowingly operate on incomplete conversation data.
Even though we are currently still on the “old” Gong connector, I’ve been told by Gainsight support that the alert/notification/triage experience with the “new” Staircase-based AI Follow-Up for Gong (and other tools) still has similar gaps.
Requested Enhancements
1. Proactive Failure Notifications
Administrators should be able receive alerts when:
• No meetings have been successfully processed for a configurable period.
• Authentication failures exceed a threshold.
• Upstream provider outages impact synchronization.
• A connector remains connected but is no longer successfully ingesting data.
Notifications/visibility should be configurable/selectable and be delivered through mechanisms such as:
• In-app notifications
• Slack/Teams integrations
• Admin dashboards
2. Connector Health Monitoring
Provide a clear health status that goes beyond "Connected."
Examples:
• Healthy
• Degraded
• Authentication Failure
• Provider Outage
• Processing Backlog
• No Data Received
The system should distinguish between:
• Connection status
• Authentication status
• Data ingestion status
• Processing status
3. Sync Gap Detection
Automatically identify when expected meeting activity is not being received.
Examples:
• User had Gong meetings but none were imported.
• Meeting volume drops significantly from historical norms.
• Large processing backlogs accumulate.
4. Root Cause Visibility
Provide diagnostic information directly within the product.
Examples:
• Last successful sync time
• Last successful authentication
• Most recent error
• Failed meeting count
• Authentication token status
• Impacted users
This would reduce dependency on Support and Engineering for common triage activities.
5. Missing Record Reconciliation
Provide tooling/reporting natively in Gainsight CS to identify records that should have synced but did not.
Examples:
• Compare source-system meeting counts to imported counts
• List missing meetings
• Replay processing for selected meetings
• Bulk reprocess affected date ranges
7. AI Follow-Up Operational Dashboard
For the Staircase-based AI Follow-Up architecture, provide an operational dashboard showing:
• Meetings received
• Meetings processed
• Meetings failed
• Meetings awaiting transcript delivery
• Retry activity
• System-wide health indicators
Even if the architecture is event-driven rather than batch-driven, administrators still need a way to identify systemic stoppages.
Business Impact
Organizations increasingly depend on AI-generated meeting insights for customer success workflows, adoption tracking, executive visibility, and risk management.
When ingestion silently fails:
• Customer interactions are missed.
• Timeline data becomes incomplete.
• AI insights become unreliable.
• Teams lose confidence in the platform.
• Administrators spend significant time performing manual audits and reconciliation.
Improved monitoring, notification, and troubleshooting capabilities would increase trust, reduce support burden, and make AI Follow-Up a more robust enterprise-ready solution.