Customer Satisfaction Summary and Transforming Data Using Bold Data Hub

In this article, we will demonstrate how to import tables from a CSV file, generate a customer satisfaction summary through transformations, and move the cleaned data into the destination database using Bold Data Hub. Follow the step-by-step process below.

Sample Data Source:

Sample CSC Data

Creating Pipeline

Learn about Pipeline Creation

Apply Transformations

Learn more about transformation here

Customer Satisfaction Summary

Overview

Measuring customer satisfaction helps evaluate service quality, agent performance, and regional trends. This query calculates the average satisfaction score (or NPS) by region, agent, and ticket category.

Approach

We aggregate Customer Satisfaction Scores for resolved tickets using:

• By Region → Understand satisfaction trends across locations
• By Agent → Assess individual agent performance
• By Ticket Category → Identify service types needing improvement

SQL Query for Customer Satisfaction by Region

SELECT 
    Region, 
    AVG(Customer_Satisfaction) AS Avg_Satisfaction_Score 
FROM {pipeline_name}.sample_csc_data 
WHERE Ticket_Status = 'Resolved' 
GROUP BY Region 
ORDER BY Region;

SQL Query for Customer Satisfaction by Agent_ID

SELECT 
    Agent_ID, 
    AVG(Customer_Satisfaction) AS Avg_Satisfaction_Score 
FROM {pipeline_name}.sample_csc_data 
WHERE Ticket_Status = 'Resolved' 
GROUP BY Agent_ID 
ORDER BY Agent_ID;

SQL Query for Customer Satisfaction by Ticket_Category

SELECT 
    Ticket_Category, 
    AVG(Customer_Satisfaction) AS Avg_Satisfaction_Score 
FROM {pipeline_name}.sample_csc_data 
WHERE Ticket_Status = 'Resolved' 
GROUP BY Ticket_Category 
ORDER BY Ticket_Category;