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Client Car Purchase Data
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About
This dataset captures client purchase decisions regarding cars. It contains details for 1,000 customers who intended to buy a car, primarily considering their annual salaries. The dataset's purpose is to indicate whether a client ultimately purchased a vehicle. It is valuable for understanding and modelling car buying behaviour [1].
Columns
- User ID: A unique identifier for each client [2].
- Gender: Indicates the client's gender, either Male or Female [2].
- Age: The client's age in years [3].
- Annual Salary: The annual salary of the customer [3].
- Purchase Decision: A binary indicator (0 = No, 1 = Yes) showing whether the client bought a car [1, 4].
Distribution
The dataset is typically provided as a CSV file [5] and includes 1,000 customer records with 5 columns [1, 2]. All columns have 1,000 valid entries, indicating no missing data [2-4].
- User ID: Ranges from 1 to 1,000, with a mean of 501 and a standard deviation of 289 [2].
- Gender: Features 52% female and 48% male clients [2, 3].
- Age: Ages range from 18 to 63 years, with an average of 40.1 years and a standard deviation of 10.7 years [3].
- Annual Salary: Ranges from £15,000 to £153,000, with an average of £72,700 and a standard deviation of £34,500 [4].
- Purchase Decision: Out of 1,000 clients, 598 did not purchase a car (0), and 402 did (1) [4].
Usage
This dataset is ideal for various analytical applications, including:
- Building binary classification models [1].
- Implementing logistic regression to predict purchase likelihood [1].
- Developing decision tree models for segmentation and prediction [1].
- Analysing factors influencing car purchase decisions.
- Market segmentation and targeting strategies.
Coverage
The dataset covers 1,000 individual customers [1], providing demographic information such as age (18 to 63 years), gender (52% female, 48% male), and annual salary (£15,000 to £153,000) [2-4]. The sources do not specify the geographic location or time range for this data.
License
CC0: Public Domain
Who Can Use It
- Data Scientists and Analysts: For developing and testing predictive models on consumer behaviour [1].
- Marketing Professionals: To identify target demographics for car sales campaigns and refine marketing strategies.
- Researchers: For academic studies on consumer psychology, purchasing patterns, and economic behaviour related to large purchases.
Dataset Name Suggestions
- Car Purchase Decision Dataset
- Customer Vehicle Acquisition Data
- Automobile Buying Propensity Dataset
- Client Car Purchase Data
Attributes
Original Data Source: Client Car Purchase Data
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