Technical Support Dataset
Analyzing Technical Support KPIs for Enhanced Efficiency and Resolution
@kaggle.suvroo_technical_support_dataset
About this Dataset
Technical Support Dataset
In today’s business landscape, companies of all sizes depend on technology for their day-to-day operations. Efficient technical support is vital in ensuring these systems run smoothly. This month’s challenge offers a real-world scenario for you to dive into—analyzing the performance of a technical support center. It’s a valuable opportunity to collaborate with peers, sharpen your analytical skills, and expand your professional experience.
Data Analysis Focus Areas:
You are free to choose your analytical approach, but consider the following key questions based on Technical Support Center Key Performance Indicators (KPIs):
Ticket Volume Trends:
- Analyze daily, weekly, and monthly ticket volumes
- Compare ticket volumes on workdays versus weekends
- Study ticket distribution during work hours versus after hours
- Identify peak times for ticket creation
Ticket Content and Resolution:
- Spot trends in ticket topics
- Assess first response and resolution times against SLAs
- Compare performance across support channels (chat, phone, email)
- Examine ticket submissions geographically for trends or product issues
Performance Metrics:
- Measure agent adherence to SLAs for first responses and resolutions
- Review customer satisfaction rates across agents, topics, and other factors
- Analyze the speed at which tickets are resolved
| Term | Description |
|---|---|
| Status | Ticket status within the support pipeline (Open: new ticket awaiting processing, In Progress: being addressed by an agent, Resolved: solution provided, Closed: ticket confirmed closed by the customer). |
| Ticket ID | Unique ticket identification number. |
| Source | Channel through which the request was made (chat, phone, email). |
| Priority | Urgency of the ticket (low, medium, high). |
| Support Level | Ticket difficulty level (Tier 1, Tier 2). |
| Product group | The product group related to the customer’s request. |
| Topic | Subject matter of the customer's inquiry. |
| Agent Group | Group to which the agent belongs (1st level support, 2nd level support). |
| Agent Name | Name of the agent currently handling the ticket. |
| Created time | Timestamp indicating when the ticket was received. |
| Expected SLA to first response | Deadline for providing the initial response. |
| First response time | Timestamp of when the initial response was given. |
| SLA For first response | First response compliance status (Within SLA, SLA Violated). |
| Expected SLA to resolve | Deadline for resolving the ticket. |
| Resolution time | Timestamp when the ticket was resolved. |
| SLA For Resolution | Resolution compliance status (Within SLA, SLA Violated). |
| Close time | Timestamp when the ticket was closed. |
| Agent interactions | Total number of agent interactions per ticket. |
| Survey results | Customer satisfaction score on a scale of 1 to 5. |
| Country | Country of origin for the customer creating the ticket. |
| Latitude | Latitude coordinates of the customer’s country. |
| Longitude | Longitude coordinates of the customer’s country. |