This dataset represents a collection of 20 thousand customer support cases from DELL, detailing various aspects of customer interactions and product support inquiries. Each record in the dataset corresponds to a unique support case, capturing information such as the time and date of case creation and closure, the method of contact, and details about the product and issue at hand. The data includes several encoded identifiers for different tags and descriptions, indicating the type of issues or products involved. Additional information like the country of the customer, the age of the system or product, the number of interactions, and warranty status is also included. This rich dataset provides a comprehensive overview of customer support journeys, offering insights into the efficiency and effectiveness of the support process, as well as customer satisfaction. The ultimate goal of analyzing this dataset is to understand and improve customer service experiences by identifying patterns and key factors that contribute to successful or unsatisfactory customer journeys.

1. Perform in-depth Exploratory Data Analysis
2. Train Customer Support Journey embeddings to identify journeys with similar characteristics.
3. Develop a Customer Journey Score to differentiate between highly satisfactory and unsatisfactory customer journeys.
4. Identify potential improvements in customer support workflows to enhance customer satisfaction.