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🎫 Documentation: Help Desk

Omnichannel tickets with SLA & AI. What it is, how it works and how to use it — explained step by step.

🎫 Definition — Help Desk

The Help Desk turns every customer request —by phone, SMS, WhatsApp or email— into a ticket the agent handles and replies to through the same channel. Each ticket carries its SLA (response times) and AI helps classify and draft the reply.

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OmnichannelTickets are created automatically from phone, SMS, WhatsApp and email.
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Reply on their channelThe reply goes out on the customer channel; or leave an internal note.
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SLA traffic lightOn time, due soon, overdue or met (first response and resolution).
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AI + quick repliesClassifies, suggests a reply and uses templates and the knowledge base.
Satisfaction surveyOn solve, the customer rates the service (Good, Fair or Poor) on their channel; results are shown by agent and category.

🗺️ Diagram — how it works

The message comes in, a ticket with SLA is created, the agent (with AI) replies on the channel and it is resolved.

📥Channels📞 SMS · WA · ✉️ingest🎫TicketSLAhandle🤖Agent + AIrepliesclosesResolvedSLA

Knowledge base: articles help resolve faster and feed the AI suggestions.

📘 Explanation (step by step)

  1. In Help Desk → Tickets open the ticket; tickets are created automatically from phone, SMS, WhatsApp or email.
  2. Write the reply and keep “Send to customer via [channel]” checked; or mark Internal note to keep it private.
  3. Use a quick reply (fills variables) or AI: Classify suggests category/priority and Suggest reply drafts using the thread and knowledge base.
  4. Watch the SLA (traffic light) and prioritize those “due soon” or “overdue”; change the status and the assignee.
  5. When you mark the ticket Solved, the customer gets the satisfaction survey on their channel (if enabled in Settings); their answer —Good, Fair or Poor— and comment show on the ticket.
  6. In Analytics, click any row to see those tickets and review the aging queue.

The customer gets the reply where they wrote; you measure times with SLA and analytics.