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Sunborn USA Customer Attrition Data
Data Science and Analytics
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About
Data captures customer activity and demographic details specifically related to churn within the USA market. This information originates from Sunborn, a global Finnish corporate group recognised for its high-quality real estate and operational businesses. This set of 100,000 distinct records provides a foundational resource for developing analytical models, training predictive algorithms, and executing strategic initiatives aimed at forecasting and mitigating customer attrition. The data is static, representing a snapshot of usage and billing metrics.
Columns
- CustomerID: A unique identification key assigned to each of the 100,000 records.
- Age: The customer's age, spanning a range from 18 to 70 years, with the typical mean age registered at 44.
- Gender: Indicates the customer’s gender, which is split evenly with 50% Female and 50% Male entries.
- Location: Geographical markers for the customer base within the USA. Significant concentrations are found in Houston (20%) and Los Angeles (20%), while the remaining 60% are grouped into other locations.
- Subscription_Length_Months: Measures the duration of the customer's subscription, ranging from 1 to 24 months, with an average length of 12.5 months.
- Monthly_Bill: The fixed recurring charge to the customer, represented by values between 30 and 100, with a calculated mean of 65.1.
- Total_Usage_GB: The cumulative usage measured in gigabytes, varying from 50 GB up to 500 GB. The average usage stands at 274 GB.
- Churn: The binary target variable, where 1 signifies that the customer has left the service, and 0 indicates they remain active. The division is nearly equal, with 50,221 records showing no churn and 49,779 records indicating churn.
Distribution
The structure of the data includes 9 distinct columns and precisely 100,000 valid customer records. The file is labelled as
customer_churn_large_dataset.csv and measures 5.38 MB. Quality checks confirm high data integrity, with 100% validity across all measured fields, showing no mismatched or missing values. The expected update frequency for this resource is 'Never', indicating its static nature.Usage
The data is ideally suited for predictive modelling, allowing users to build machine learning algorithms capable of forecasting customer attrition risk. It can facilitate detailed segmentation analysis based on combined demographic, usage, and billing variables. Furthermore, the dataset supports business intelligence initiatives aimed at reporting on retention rates across specific geographical regions and optimising subscription policies based on observed usage patterns.
Coverage
The geographical scope is restricted to the Sunborn operation within the USA location. Demographically, the records span individuals aged 18 to 70 and exhibit an equal balance between genders. While the data is a static snapshot, the maximum recorded subscription period is 24 months.
License
CC0: Public Domain
Who Can Use It
- Data Scientists: For developing supervised machine learning models to identify key predictors of attrition.
- Product Managers: To refine service tiers and feature offerings by correlating subscription length and usage habits with customer retention.
- Business Intelligence Professionals: To generate focused performance dashboards on retention in key areas like Houston and Los Angeles.
Dataset Name Suggestions
- Sunborn USA Customer Attrition Data
- B2C Churn Prediction Metrics
- US Customer Behaviour Analysis Set
Attributes
Original Data Source: Sunborn USA Customer Attrition Data
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