Growth Engineering Playbook · Wave 2

What are your support tickets actually telling you?

Support tickets are not a queue to burn down — they're customer intelligence. This mines the fictional Northstar Outfitters support corpus into operational decisions: theme clusters, sentiment and urgency, product-category friction, content gaps, support-risk customers, automation candidates, and an owner-routed action queue. The expert move is turning recurring tickets into fixes and automations, not counting ticket volume. Deterministic keyword/theme rules, client-side, synthetic identifiers only.

Loading support, customer, order & product data…

Theme Clusters

Volume, sentiment mix (red = negative), and urgency. Click a theme for detail.

Product / Category Heatmap

Where friction concentrates — returns, size advice, warranty, care. Click a row.

Content Gaps

Recurring questions a better page would deflect — with the owner who fixes it.

Automation Opportunities

Ticket patterns that a workflow or bot could handle end-to-end.

Action Queue

The insights turned into owner-routed, prioritised next actions.

Support-Risk Customers

Repeat contacts, negatives, and returns — with a lifecycle recommendation. Click a customer.

Insight Detail

Example ticket snippets and why the selected signal matters commercially.