Synthetic Customer Feedback and Satisfaction Dataset

Dataset Features:

• CustomerID: Unique identifier for each customer.
• Age: Age of the customer in years.
• Gender: Gender of the customer (e.g., "Male," "Female").
• Country: Country of residence (e.g., "USA," "Canada").
• Income: Annual income of the customer in USD.
• ProductQuality: Rating of product quality on a scale from 1 (lowest) to 10 (highest).
• ServiceQuality: Rating of service quality on a scale from 1 (lowest) to 10 (highest).
• PurchaseFrequency: Number of purchases made by the customer within a specified period.
• FeedbackScore: Categorization of customer feedback (e.g., "Low," "Medium," "High").
• LoyaltyLevel: Loyalty tier assigned to the customer based on feedback and behaviour (e.g., "Bronze," "Silver," "Gold").
• SatisfactionScore: Overall satisfaction score calculated based on various factors, ranging from 0 to 100.

Distribution:

Usage:

• Customer Segmentation: Analyzing demographic and behavioral patterns to group customers by loyalty or satisfaction levels.
• Predictive Modeling: Building models to predict customer satisfaction or loyalty based on quality ratings and demographic information.
• Sentiment Analysis: Understanding customer sentiment through feedback scores and satisfaction ratings.
• Service Improvement: Identifying gaps in product and service quality to enhance customer experience.

Coverage:

License:

Who Can Use It:

• Businesses: To simulate and analyze customer satisfaction and feedback trends.
• Students and Educators: For practising data analysis, visualization, and predictive modelling.
• Data Scientists: To develop and test machine learning models related to customer satisfaction and loyalty prediction.