analysis · Gemini · free
Cluster my support tickets into themes and rank them by product impact. Tickets: [PASTE — subject + first message per row is enough] Product area: [WHAT PART OF THE PRODUCT] Volume period: [WEEK / MONTH / QUARTER] Deliver: 5 10 theme clusters with % of ticket volume For each theme: root cause hypothesis (bug / UX / docs / onboarding / expectation gap) Cost per theme: est. support hours × ticket count Deflection potential: which themes could be killed by a docs / UX fix vs need engineering Top 3 fixes ranked by (impact × ease) One theme I'm probably ignoring that has strategic weight (churn signal, ICP mismatch) What the support team should now escalate differently Don't dress up whining as insight.
#support #themes #customer-feedback