Mapping User Journeys Using Bold Data Hub

In this article, we will demonstrate how to import tables from a CSV file, create customer journey map using transformations, and move the transformed 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

Applying Transformation

  • Go to the Transform tab and click Add Table.

  • Enter the table name to create a transform table for customer satisfaction summary.

Tranformation Use Case

Note: The data will initially be transferred to the DuckDB database within the designated {pipeline_name} schema before undergoing transformation for integration into the target databases. As an illustration, in the case of a pipeline named “customer_service_data”, the data will be relocated to the customer_service_data table schema.

Learn more about transformation here

Creating a Customer Journey Map

Overview

A customer journey map helps to visualize and understand each customer’s experience by analyzing their interaction history. By aggregating data from various touchpoints, such as support tickets, we can track a customer’s path from their first interaction to the most recent one. This analysis helps identify patterns and improve customer experience.

Approach

We aggregate the support tickets based on Customer_ID, ordered by Ticket_Creation_Date to analyze the sequence of interactions. This allows us to track the customer’s journey over time and identify recurring issues or improvements.

SQL Query for Creating a Customer Journey Map

SELECT 
    Customer_ID, 
    Customer_Name, 
    MIN(Ticket_Creation_Date) AS First_Interaction, 
    MAX(Ticket_Creation_Date) AS Last_Interaction, 
    COUNT(Ticket_ID) AS Total_Tickets, 
    AVG(Resolution_Time) AS Avg_Resolution_Time, 
    AVG(Customer_Satisfaction) AS Avg_Satisfaction 
FROM {pipeline_name}.sample_csc_data 
GROUP BY Customer_ID, Customer_Name 
ORDER BY Last_Interaction DESC;