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Purchasing Behaviour Analysis Dataset
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About
This dataset analyses customer behaviour by providing detailed profiles and purchasing habits. It includes customer demographics, income levels, purchasing amounts, and loyalty scores. The primary purpose is to facilitate customer segmentation and loyalty trend analysis, making it suitable for various machine learning and data analysis tasks related to understanding market research and consumer actions. Please note, this dataset consists of imaginary data created solely for user improvement purposes and does not reflect real-world information.
Columns
- customer_id: A unique identifier for each customer. These IDs range from 1 to 238.
- age: The age of the customer in years, ranging from 22 to 55.
- annual_income: The customer's yearly income in US Dollars, spanning from $30,000 to $75,000.
- purchase_amount: The total amount, in US Dollars, spent by the customer on purchases, with values between $150 and $640.
- purchase_frequency: The number of times a customer makes purchases annually, ranging from 10 to 28 times per year.
- region: The geographical area where the customer resides, categorised as North, South, East, or West. Approximately 33% of customers are from the North, 32% from the South, and 35% from other regions (East/West combined).
- loyalty_score: A score indicating customer loyalty, measured on a scale from 3 to 9.5.
Distribution
The dataset is provided in a CSV format and has a file size of 7.27 kB. It contains 7 columns and comprises 238 valid entries across all fields. There are no mismatched or missing values within the dataset.
Usage
This dataset is ideal for:
- Performing customer segmentation to identify distinct customer groups.
- Analysing and predicting customer loyalty trends.
- Developing machine learning models for customer behaviour prediction.
- Conducting data analytics and data visualisation exercises.
- Exploring concepts related to linear regression and machine learning ethics.
- Market research and understanding consumer purchasing patterns.
Coverage
The dataset covers demographic information including customer age (22-55 years) and annual income ($30,000-$75,000). Geographic scope includes four distinct regions: North, South, East, and West. A specific time range for data collection is not provided, though purchase frequency is stated as an annual measure. It is important to reiterate that all data points are hypothetical.
License
CC0 Public Domain
Who Can Use It
- Data analysts looking to practice segmentation and behavioural analysis.
- Data scientists for building predictive models on customer purchasing and loyalty.
- Market researchers for simulating consumer trends and behaviours.
- Students and educators for learning and teaching data analytics, machine learning, and statistical concepts.
Dataset Name Suggestions
- Customer Purchasing Habits Dataset
- Consumer Behaviour and Loyalty Metrics
- Customer Profile and Transaction Data
- Purchasing Behaviour Analysis Dataset
Attributes
Original Data Source: Purchasing Behaviour Analysis Dataset
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