Customer Service Dataset Generator

The Best Way to Practice Analyzing Customer Support Data.

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The Ultimate Customer Service Dataset Generator

Tired of practicing your data analysis skills with simplistic, single-sheet data? Building a realistic help desk dashboard, analyzing agent performance, or tracking ticket resolution times requires a rich, interconnected set of customer service data—something that’s incredibly hard to find.

Until now.

Welcome to the PNRao Customer Service Data Generator, a powerful tool designed to create a complete, enterprise-grade ITSM (IT Service Management) dataset with a single click. Whether you’re an analyst practicing how to calculate First Response Time, a student learning about customer support operations, or a manager building a business case for a new knowledge base, this generator provides the data you need.

Move beyond simple ticket lists and start working with datasets that reflect the complexities of a real-world customer support department.

Why This Dataset is a Powerful Learning Tool

Learning customer service analytics with abstract numbers can be challenging. This generator provides a realistic context that makes complex concepts easier to grasp.

  • Builds a Narrative: You can step into the role of a data analyst for the PNRao support team. Your task could be to identify which ticket categories take the longest to resolve, analyze customer satisfaction (CSAT) scores, or understand which agents are the top performers. This narrative-driven practice helps solidify your understanding.
  • Makes Concepts Concrete: When you see a Ticket Log table linked to Agents and Customers, abstract concepts become tangible. This makes metrics like Average Resolution Time, First Contact Resolution, and CSAT easier to understand because you can see how they are built from the ground up.
  • Encourages Realistic Analysis: The rich context inspires more creative and insightful analysis. You might build a dynamic agent performance dashboard in Power BI or create a report in Excel to identify trends in customer issues. This allows you to practice not just the technical skills, but also the art of data storytelling.

Designed for Real-World Service Desk Analysis

This dataset isn’t just a random collection of tables. It has been carefully crafted to mirror the data structures you will find in actual help desk and CRM systems, making it the perfect tool to develop practical, job-ready skills.

  • Reflects Core Service Operations: Every support department deals with tickets, customers, agents, and feedback. The tables in this generator represent the core of what you will encounter professionally. By understanding how these tables relate to each other, you are learning the fundamental blueprint of service desk data.
  • Focus on a High-Demand Skillset: Analyzing support operations is a critical function in every business. The skills you build here—calculating resolution times, tracking agent productivity, and analyzing customer satisfaction—are directly transferable to the tasks and challenges you will face in a real data analytics or operations job.
  • Covers a Wide Range of Concepts: The structure of this data is intentionally designed to be a comprehensive playground for learning. With this single resource, you can practice:
    • Excel/Sheets Functions: Use VLOOKUP or XLOOKUP to connect ticket records with agent details, SUMIFS and COUNTIFS to create summary reports, and PivotTables to analyze ticket volume by category.
    • Time-Series Analysis: Analyze ticket creation trends by day or month to practice forecasting support volume.
    • Data Cleaning: Use the “messy data” option to practice cleaning and validating ticket logs and customer feedback.
    • Advanced Analysis: The interconnected tables are perfect for practicing relationship-building in Power BI or writing SQL JOIN queries to combine data from multiple sources for a complete analysis.

In short, learning with this dataset ensures you are not just practicing abstract concepts, but preparing yourself with the practical knowledge and experience valued by employers.

Tables Overview

The generator produces a wide array of datasets across different customer service functions. Each dataset has a unique structure, as detailed below.

Case & Ticket Management

Table Name Description Columns
Ticket Log The main fact table for all support tickets. TicketID, CustomerID, AgentID, ProductID, Channel, Priority, Status, DateCreated, DateClosed, FirstResponseTime_Hours, ResolutionTime_Hours
Ticket Details & Updates A log of all updates and comments on a ticket. DetailID, TicketID, UpdateTimestamp, UpdateText, UpdatedBy
Ticket Tags Tags applied to tickets for categorization. TaggingID, TicketID, Tag

Customer & Product Data

Table Name Description Columns
Customer Master A list of all unique customers. CustomerID, FullName, Email, JoinDate, Country
Product Master A list of all company products. ProductID, ProductName, Category
Customer Owned Products Links customers to the products they own. CustProdID, CustomerID, ProductID, PurchaseDate

Agent & Team Performance

Table Name Description Columns
Agent Master A list of all support agents. AgentID, FullName, Team, HireDate
Agent Performance Summary Monthly performance metrics for each agent. AgentID, AgentName, TicketsClosed, AvgResolutionTime_Hours, Avg_CSAT_Score

Customer Feedback

Table Name Description Columns
CSAT Surveys Customer Satisfaction survey results post-ticket. SurveyResponseID, TicketID, CustomerID, SurveyDate, CSAT_Score
NPS Surveys Net Promoter Score survey results. NPS_ID, CustomerID, SurveyDate, NPS_Score

Knowledge Base

Table Name Description Columns
KB Articles A list of all help articles. ArticleID, Title, Category, DatePublished
KB Article Views Log of customer views on knowledge base articles. ViewID, ArticleID, CustomerID, ViewDate

How to Use This App

  1. Select a Table to Preview: Use the “Select Table to Preview” dropdown menu to choose the type of data you want to inspect.
  2. Specify the Number of Tickets: Enter the desired number of support tickets. This is the main driver; a higher number will generate more related records in all other tables.
  3. Configure Advanced Options (Optional): Click on Advanced Options to expand the menu.
    • Date Range: Select a Start Date and End Date to constrain the generated data to a specific time period.
    • Data Quality: Choose the quality of your dataset (Clean, Slightly Messy, or Very Messy).
  4. Generate the Data: Click the “Generate All Datasets” button. The application will process your request and display a preview of your selected table.
  5. Download Your Data:
    • Preview: To quickly download just the data shown in the preview table, click “Download Preview (CSV)” or “Download Preview (Excel)”.
    • All Related Tables: Click “Download All Tables (Excel)” to download a single Excel file with every table on a separate, clearly named sheet. This is the best option for relational analysis.

How to Use This Data

  • For Data Analysts & BI Professionals:
    • Help Desk Dashboards: Use the Ticket Log, Agents, and CSAT Surveys tables to build an executive-level dashboard in Tableau or Power BI.
    • Performance Analysis: Analyze ticket resolution times, first response times, and customer satisfaction scores by agent or team.
    • Practice SQL: Load the tables into a database and practice writing complex JOIN queries to combine ticket, customer, and agent data.
  • For Students & Educators:
    • Create realistic case studies for business operations, customer relationship management (CRM), and data science courses.
    • Use the data as a foundation for assignments on calculating key support metrics like ticket volume, backlog, and agent utilization.

Feedback & Suggestions

This tool is built for you. If you have an idea for a new customer service table or an improvement, please leave your feedback in the comments section below.