Review support threads and turn them into product insights

An agent can scan support conversations, coach handlers, and collect recurring complaints for the product team.

Done with Grok Bot· Intermediate

What they did
Grok Bot was linked to the team’s ticketing tools, along with Linear and Datadog. It checked conversations from both staff and automated responders, wrote coaching notes, and sent any case that ping-ponged more than three times up for management to look at. It also posted a daily Slack digest and sorted customer comments into recurring topics for engineering.
How it went
The team says it distills over 20,000 individual pieces of product feedback from tickets every day. They also said ticket volume climbed 175% without hiring more people. No accuracy numbers were shared for the review or coaching work.
Tips
A safer rollout is to begin with internal summaries, then require approval before any write step, and only later let the agent act directly with customers. Keep a human check in place before anything is sent, changed, or closed.

Try it yourself with Grok Bot

Look at yesterday’s support conversations in [helpdesk]. Review items handled by both [team members] and automated agents, note coaching points, and flag any thread that required more than 3 replies to resolve. Prepare a brief report for [Slack channel] and group repeated customer issues into product themes for [engineering team]. Stop and ask for my approval before you send, change, close, delete, or submit anything.

Fill in the [brackets]. Agents can make mistakes, so review anything before it is sent, paid or deleted.

Read the original on x.ai ↗

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