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Customer Support Ticket Data
Data Science and Analytics
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About
This dataset includes customer support tickets for various tech products, capturing inquiries related to hardware issues, software bugs, network problems, account access, and data loss, among other support topics. It provides key information about the customer, the product purchased, ticket type, channel, status, and other relevant details. This dataset is valuable for a range of analysis and modelling tasks in the customer service domain, aiding in the identification of common issues, improvement of support processes, and automation of ticket handling.
Columns
- Ticket ID: A distinct identifier for each individual ticket.
- Customer Name: The name of the customer who submitted the ticket.
- Customer Email: The email address of the customer; domain names are intentionally masked for privacy.
- Customer Age: The age of the customer at the time of the ticket submission.
- Customer Gender: The gender of the customer.
- Product Purchased: The specific tech product the customer bought.
- Date of Purchase: The date when the product was acquired.
- Ticket Type: The classification of the ticket, such as technical issue, billing inquiry, or product inquiry.
- Ticket Subject: The main topic or subject of the ticket.
- Ticket Description: A detailed account of the customer's problem or inquiry.
- Ticket Status: The current state of the ticket, for example, open, closed, or pending customer response.
- Resolution: The solution or action taken to resolve closed tickets.
- Ticket Priority: The assigned urgency level of the ticket, such as low, medium, high, or critical.
- Ticket Channel: The method through which the ticket was initiated, including email, phone, chat, or social media.
- First Response Time: The duration taken to provide the initial response to the customer.
- Time to Resolution: The total time elapsed to resolve the ticket.
- Customer Satisfaction Rating: The customer's satisfaction rating for tickets that have been closed, on a scale of 1 to 5.
Distribution
The dataset is provided in CSV format and has a size of 3.95 MB. It contains 17 columns and includes 8469 unique records for most core fields. However, some fields have notable proportions of missing values: "Resolution" (67% missing), "Time to Resolution" (67% missing), "First Response Time" (33% missing), and "Customer Satisfaction Rating" (67% missing).
Usage
This dataset is suitable for various applications, including:
- Customer Support Analysis: Examining ticket trends, pinpointing frequent issues, and refining support operations.
- Natural Language Processing (NLP): Utilising ticket descriptions to train NLP models for automated ticket categorisation or sentiment analysis.
- Customer Satisfaction Prediction: Developing models to forecast customer satisfaction based on ticket details.
- Ticket Resolution Time Prediction: Constructing models to estimate the time required to resolve a ticket using various influencing factors.
- Customer Segmentation: Dividing customers into groups based on their ticket types, issues, or satisfaction levels.
- Recommender Systems: Building systems that suggest relevant solutions or products in response to customer inquiries.
Coverage
The dataset covers purchase dates from 1 January 2020 to 30 December 2021. Customer demographic information is included, with customer ages ranging from 18 to 70 years (average age 44) and gender distribution showing approximately 34% male, 34% female, and 32% identified as 'Other'. Customer email addresses have anonymised domain names for data privacy. There is no specific geographic scope mentioned.
License
CC0: Public Domain
Who Can Use It
This dataset is ideal for:
- Data analysts and data scientists focused on customer service operations.
- Machine learning engineers developing predictive models for business metrics.
- Natural Language Processing researchers and practitioners.
- Customer experience managers aiming to identify pain points and improve service delivery.
- Product managers seeking insights into product-related issues.
Dataset Name Suggestions
- Customer Support Ticket Data
- Tech Product Service Logs
- Customer Query Dataset
- Digital Product Help Desk Records
- Support Ticket Analytics Data
Attributes
Original Data Source: Customer Support Ticket Data
QUALITY