---
module: analytics.incidents
title: Incident Trends
tab: Customer
order: 10
audience: customer
---

See how incidents across your ATM fleet are trending over time, which kinds of problems happen most, when they cluster, and which machines keep failing. Use this screen to spot patterns and get ahead of recurring issues.

## 📈 30-Day Incident Trend
A line chart showing how many incidents were raised each day over the last 30 days.

- Rising line = incidents are climbing; falling line = things are settling down.
- The date labels along the bottom mark the timeline.

> If there isn't enough history yet, you'll see "Not enough data."

## 🗂️ Event Category Breakdown
A ranked bar chart of incidents grouped by the type of problem, largest first.

- Categories include **Hardware**, **Network**, **Cash**, **Power**, **Auth**, **System**, and **Operations**.
- The number on the right is how many incidents fall into that category.

## 🔥 Peak Hours Heatmap
A grid of the week (Mon–Sun down the side, hours 0–23 across the bottom) showing when incidents happen most.

- Darker cells mean quiet periods; brighter red cells mean busy ones.
- Hover a cell to see the exact day, hour, and count.
- Use this to plan maintenance and staffing around your busiest windows.

## 🔁 Recurring Failures
A table of ATMs that keep hitting the same issue.

- **ATM** — the machine's ID.
- **Event Type** — the specific fault it keeps reporting.
- **Count** — how many times it's recurred. The badge turns yellow at 3+ and red at 5+, so high-repeat problems stand out.

> Good to know: a machine near the top of Recurring Failures is usually worth a closer look or a service visit — repeated faults often point to a root cause that a single fix can clear.
