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California Telecom Customer Attrition Data
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About
This data product is centred on identifying and analysing the factors leading to customer attrition within a home phone and Internet service provider. It serves as an essential resource for modelling customer loyalty and predicting which individuals are most likely to churn. By integrating detailed demographic, service usage, payment, and satisfaction information, the dataset enables sophisticated analysis of the drivers behind subscriber decisions.
Columns
The collection includes information categorised across several files:
- CustomerID: A unique identifier for each subscriber record.
- Gender, Age, Senior Citizen, Married, Dependents: Core demographic and household status variables.
- Number of Dependents: The count of dependents residing with the customer (ranging from 0 to 9).
- Location Data: Includes Country, State, City, Zip Code, Total Population, Latitude, and Longitude of the residence.
- Service Subscriptions: Boolean and categorical data covering services like Phone Service, Internet Service (DSL, Fiber Optic, Cable), Online Security, Online Backup, Device Protection Plan, Premium Tech Support, Streaming TV, Streaming Movies, and Streaming Music.
- Payment Details: Includes Contract type (e.g., Month-to-Month, One Year), Paperless Billing status, Payment Method, Monthly Charge, Total Charges, Total Refunds, Total Extra Data Charges, and Total Long Distance Charges.
- Tenure in Months: The duration (in months) the customer has been with the company.
- Referral Data: Whether the customer Referred a Friend and the Number of Referrals made.
- Offer: The last marketing offer accepted by the customer (e.g., Offer A, Offer B, None).
- Status Analysis: Includes Satisfaction Score (1 to 5), Customer Status (Churned, Stayed, or Joined), Churn Label (Yes/No), Churn Value (1/0), and Churn Score (0-100 likelihood index).
Distribution
The data is structured for use in analytics platforms, commonly delivered in CSV file format. It contains records for 7,043 unique customers. The mean age of customers is approximately 46.5 years, with ages ranging from 19 to 80 years. Approximately 16% of the customer base qualifies as a senior citizen.
Usage
This dataset is ideal for building machine learning models aimed at customer churn prediction. Analysts can use it to identify patterns in service usage and payment behaviour that correlate with high attrition risk. It is also suitable for targeted marketing campaigns designed to increase retention and for deep-dive exploratory data analysis into customer segmentation.
Coverage
The data pertains to customers residing within California, United States. The records represent customer status at the end of Q3 (Quarter 3). The demographic scope is broad, capturing customers across all adult age ranges (19 to 80), balanced gender distribution (50% Male, 50% Female), and various marital and dependent statuses.
License
CC0: Public Domain
Who Can Use It
Data Scientists: For developing and testing advanced predictive models, particularly classification models for churn.
Business Intelligence Analysts: For reporting on customer health metrics, analysing service profitability, and identifying high-risk segments.
Marketing and Strategy Teams: For determining the effectiveness of various service offerings and payment options, and for designing specific retention incentives.
Dataset Name Suggestions
- Telco Customer Churn Analysis Data
- Telecommunications Subscriber Behaviour Q3
- Customer Loyalty and Retention Prediction Set
- California Telecom Customer Attrition Data
Attributes
Original Data Source: California Telecom Customer Attrition Data
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