How do I find out what is driving a spike in support tickets with iDBQuery?
Ask iDBQuery what is driving a support-ticket spike and its Analyst agent breaks the volume down by topic, product area, customer segment and time to find the cause. It returns a cited explanation, so support and product teams can fix the root issue instead of just clearing the queue.
A sudden jump in support tickets is a symptom; the value is in finding the cause fast, before it overwhelms the team. iDBQuery investigates it from a plain-language question.
- It breaks ticket volume down by topic, category, product area, segment and time
- It pinpoints whether a spike is one issue or many, new or ongoing
- It correlates the spike with events like a release, an outage or a campaign when the data allows
- It returns a cited narrative with the numbers behind it
Ask *support tickets jumped 40 percent this week, what is driving it?* The Analyst agent might come back with *most of the increase is login errors, concentrated in customers on the latest app version, starting the day of the release.* That points straight at a fix.
Because iDBQuery builds one live model across your support desk, product and release data, it can connect a ticket spike to its cause rather than stopping at the count. Cited answers let support raise a specific, evidenced issue with engineering instead of a vague complaint. Support and product teams use this to stop recurring problems at the source, reduce ticket volume for good, and protect both the team and the customer experience from avoidable pain.
Updated 2026-06-22