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Vehicle Customer Behaviour Analysis
Retail & Consumer Behavior
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About
This dataset is designed to assist an automobile company with its strategy for entering new markets. The company plans to launch its existing products (P1, P2, P3, P4, and P5) into these new territories. Market research has indicated that customer behaviour in these new markets is similar to their existing customer base. In the existing market, the sales team successfully segmented customers into four distinct groups (A, B, C, D) and applied tailored outreach and communication strategies. The primary purpose of this dataset is to enable the prediction of the correct customer segment for 2627 new potential customers, allowing the company to replicate its successful segmented marketing approach.
Columns
- ID: A unique identifier for each customer.
- Gender: Indicates the customer's gender, either Male or Female.
- Ever_Married: Denotes the customer's marital status, typically true or false, with some missing values.
- Age: Represents the customer's age, ranging from 18 to 89 years.
- Graduated: A boolean indicator showing whether the customer is a graduate, true or false, with some missing values.
- Profession: Describes the customer's professional field, including categories like Artist, Healthcare, and various others, with some missing values.
- Work_Experience: Details the customer's years of work experience, ranging from 0 to 14 years, with a notable number of missing values.
- Spending_Score: Categorises the customer's spending behaviour as Low, Average, or Other.
- Family_Size: Specifies the number of family members for the customer, including themselves, ranging from 1 to 9 members, with some missing values.
- Var_1: An anonymised categorical variable providing additional customer classification, with values like Cat_6 and Cat_4, and some missing values.
Distribution
The dataset is typically provided in a CSV file format and is approximately 133.1 kB in size. It comprises 10 columns and contains 2627 valid records for new potential customers. While most columns are fully populated, several columns have missing values: 'Ever_Married' (50 missing), 'Graduated' (24 missing), 'Profession' (38 missing), 'Work_Experience' (269 missing), and 'Family_Size' (113 missing).
Usage
This dataset is ideally suited for predictive modelling and classification tasks. Its primary application is to predict the appropriate customer segment for individuals in new markets. It can be used for multiclass classification and clustering to understand customer groupings. The insights derived from this dataset can directly inform targeted outreach and communication strategies for sales and marketing teams entering new automotive markets.
Coverage
The dataset focuses on the demographic characteristics of customers, including their gender, age, marital status, education level, profession, work experience, spending habits, and family size. While the dataset is intended for application in "new markets," specific geographic or time-range coverage is not detailed. The data availability for different groups is based on the provided column distributions and counts, noting percentages for various categories within each feature.
License
CC0: Public Domain
Who Can Use It
This dataset is particularly valuable for data scientists, machine learning engineers, and business analysts involved in customer segmentation and market entry strategies. It is also highly relevant for marketing managers and sales teams seeking to refine their customer engagement tactics. Use cases include developing predictive models for customer classification, understanding key customer attributes, and strategising personalised marketing campaigns for automotive product sales.
Dataset Name Suggestions
- Automotive Customer Segment Predictor
- New Market Customer Profiling
- Vehicle Customer Behaviour Analysis
- Customer Segmentation for Market Expansion
Attributes
Original Data Source:Vehicle Customer Behaviour Analysis
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