Escalate overdue support tickets

Add SLA monitoring and SLA tracking to your support queue, catching tickets left unresolved past your threshold and sending SLA alerts with status, assignee, and priority to the right team.

Useful for
Customer support teams and support operations responsible for managing ticket queues and coordinating with internal stakeholders.

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On an hourly schedule, the automation checks [support ticketing system, e.g. Zendesk, Jira Service Management] for tickets still unresolved past a defined time threshold, captures the ticket ID, status, assignee, priority, and the team it is waiting on, and posts an alert with those details to that team's channel in [team chat platform, e.g. Slack, Microsoft Teams] while notifying the assignee directly.

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Problem

Support leads manually scan the queue for tickets stuck waiting on other teams and chase each one by hand. Unresolved support tickets often sit in the queue waiting on input from other teams, leading to missed deadlines, stalled progress, and a poor customer experience due to lack of timely follow up.

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Solution

On an hourly schedule, the automation checks the support ticketing system for tickets still unresolved past a defined time threshold, captures the ticket ID, status, assignee, priority, and the team it is waiting on, and posts an alert with those details to that team's chat channel while notifying the assignee directly.

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Impact

Tickets waiting on other teams get unblocked before deadlines pass, so customers stop waiting on stalled requests and service commitments are kept.

Benefits 

Who is this for? 

Customer support teams and support operations responsible for managing ticket queues and coordinating with internal stakeholders.

Success stories

Adapt at speed with 
visual-first automation and AI 

Make drives efficiencies, solves problems, and speeds innovation by breaking down silos across your business.

Similar use cases 

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Resolve support inquiries from knowledge base

When a customer sends a question through the support chatbot, an AI agent determines how to resolve it, querying the internal knowledge base to find relevant documentation, and deciding when the available knowledge is insufficient and a web search is needed to enrich its response. The agent adapts its research approach based on the nature and complexity of each inquiry rather than following a fixed lookup sequence, then replies to the customer in the chat.

Resolve support inquiries from knowledge base

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Route support tickets to specialists

When a new ticket arrives from any channel, the automation captures the ticket content and customer context, uses AI to categorize the issue type and complexity level, routes the ticket to the appropriate team or agent using predefined assignment rules, then uses AI to analyze the ticket against the knowledge base and previous resolutions to suggest the most relevant articles or solutions that match the issue, delivering these suggestions directly to the assigned agent.

Route support tickets to specialists

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Collect satisfaction feedback on resolved tickets

When a support ticket's status changes to resolved in the helpdesk, the automation reads the customer's name, email, ticket ID, and assigned support agent, then emails the customer a satisfaction survey with a link tied to that ticket. It records the survey send on the ticket and adds a row to a feedback tracking sheet with the ticket details and send date.

Collect satisfaction feedback on resolved tickets