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Analyzing Customer Churn And Its Impact On Revenue

Exploring Patterns and Trends

@kaggle.thedevastator_analyzing_customer_churn_and_its_impact_on_reven

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About this Dataset

Analyzing Customer Churn And Its Impact On Revenue

Analyzing Customer Churn and Its Impact on Revenue

Exploring Patterns and Trends

By [source]

About this dataset

This dataset contains customer data from multiple sources that can be used to predict customer churn and analyze its effect on revenue. We'll use this data to gain insights into customer behavior, such as when customers are likely to churn, how their behavior affects revenue and what patterns of behavior can help us better understand customers. This dataset features several different attributes for each customer: their unique identifier, total charges paid over time, contract information and more. Additionally, we can use the predictive analytical models based on this data to identify at-risk customers that may be more likely to churn in the near future. By gaining deep insight into which customers are most likely to leave and why they are leaving, businesses will be better equipped with tools necessary for taking proactive measures against potential revenue losses due to customer churn

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How to use the dataset

This dataset is an excellent tool for businesses to understand what factors are associated with customer churn and its impact on revenue. It can provide insights into which customers are most likely to leave, and how companies can prevent them from leaving.

To use this dataset, here are the steps businesses can follow:

  1. Understand each of the data points available in the dataset and what they represent - For example, CustomerID is a unique identifier for each customer, Churn indicates if a customer has left the company or not, gender denotes what gender the customer is etc.
  2. Analyze any trends or patterns in your data – Look out for correlations between different variables like OnlineSecurity usage and Churn rate or MonthlyCharges and tenure to determine how these variables affect customers’ decisions to stay with a company or leave it etc.
  3. Use machine learning models on your dataset – Utilize supervised learning algorithms such as logistic regression on this dataset to determine which variable most closely correlates with loyalty of customers i.e., which variable will decide whether a particular customer will stay with your company or not?
  4. Explore various ways of increasing retention rates – Think about ways you could incentivize customers who might be considering leaving their current provider (for example, offer discounts, free trials etc.). You could try different strategies like A/B testing too see which incentive works best for churn prevention/retention rate increase etc.
    5.. Test out strategies before implementing them - Once you have decided on incentives that might work well, run small scale tests to check if they generate desired results before investing resources into full rollout programs .The systems based on machine learning algorithms allows you to quickly test assumptions efficiently without large investments in time & money prior committing these changes fully operational processes

Research Ideas

  • Using customer data to identify and target customers who are at a high risk of churning to counter this effect with relevant customer service initiatives.
  • Analyzing the effects of promotional campaigns and loyalty programs on customer retention rates and overall revenue.
  • Machine learning models that predict future chances of customer churn which can be used by businesses to improve strategies for better retention & profitability

Acknowledgements

If you use this dataset in your research, please credit the original authors.
Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: dataset1.csv

Column name Description
CustomerID Unique identifier for each customer. (Integer)
Churn Whether or not the customer has churned. (Boolean)
gender Gender of the customer. (String)
SeniorCitizen Whether or not the customer is a senior citizen. (Boolean)
Partner Whether or not the customer has a partner. (Boolean)
Dependents Whether or not the customer has dependents. (Boolean)
tenure Length of time the customer has been with the company. (Integer)
PhoneService Whether or not the customer has phone service. (Boolean)
MultipleLines Whether or not the customer has multiple lines. (Boolean)
InternetService Type of internet service the customer has. (String)
OnlineSecurity Whether or not the customer has online security. (Boolean)
OnlineBackup Whether or not the customer has online backup. (Boolean)
DeviceProtection Whether or not the customer has device protection. (Boolean)
TechSupport Whether or not the customer has tech support. (Boolean)
StreamingTV Whether or not the customer has streaming TV. (Boolean)
StreamingMovies Whether or not the customer has streaming movies. (Boolean)
Contract Type of contract the customer has. (String)
PaperlessBilling Whether or not the customer has paperless billing. (Boolean)
PaymentMethod Payment method the customer is using. (String)
MonthlyCharges Amount the customer is charged each month. (Float)
TotalCharges Total amount the customer has been charged. (Float)

File: dataset2.csv

Column name Description
CustomerID Unique identifier for each customer. (Integer)
Churn Whether or not the customer has churned. (Boolean)
gender Gender of the customer. (String)
SeniorCitizen Whether or not the customer is a senior citizen. (Boolean)
Partner Whether or not the customer has a partner. (Boolean)
Dependents Whether or not the customer has dependents. (Boolean)
tenure Length of time the customer has been with the company. (Integer)
PhoneService Whether or not the customer has phone service. (Boolean)
MultipleLines Whether or not the customer has multiple lines. (Boolean)
InternetService Type of internet service the customer has. (String)
OnlineSecurity Whether or not the customer has online security. (Boolean)
OnlineBackup Whether or not the customer has online backup. (Boolean)
DeviceProtection Whether or not the customer has device protection. (Boolean)
TechSupport Whether or not the customer has tech support. (Boolean)
StreamingTV Whether or not the customer has streaming TV. (Boolean)
StreamingMovies Whether or not the customer has streaming movies. (Boolean)
Contract Type of contract the customer has. (String)
PaperlessBilling Whether or not the customer has paperless billing. (Boolean)
PaymentMethod Payment method the customer is using. (String)
MonthlyCharges Amount the customer is charged each month. (Float)
TotalCharges Total amount the customer has been charged. (Float)

File: dataset3.csv

Column name Description
CustomerID Unique identifier for each customer. (Integer)
Churn Whether or not the customer has churned. (Boolean)
gender Gender of the customer. (String)
SeniorCitizen Whether or not the customer is a senior citizen. (Boolean)
Partner Whether or not the customer has a partner. (Boolean)
Dependents Whether or not the customer has dependents. (Boolean)
tenure Length of time the customer has been with the company. (Integer)
PhoneService Whether or not the customer has phone service. (Boolean)
MultipleLines Whether or not the customer has multiple lines. (Boolean)
InternetService Type of internet service the customer has. (String)
OnlineSecurity Whether or not the customer has online security. (Boolean)
OnlineBackup Whether or not the customer has online backup. (Boolean)
DeviceProtection Whether or not the customer has device protection. (Boolean)
TechSupport Whether or not the customer has tech support. (Boolean)
StreamingTV Whether or not the customer has streaming TV. (Boolean)
StreamingMovies Whether or not the customer has streaming movies. (Boolean)
Contract Type of contract the customer has. (String)
PaperlessBilling Whether or not the customer has paperless billing. (Boolean)
PaymentMethod Payment method the customer is using. (String)
MonthlyCharges Amount the customer is charged each month. (Float)
TotalCharges Total amount the customer has been charged. (Float)

File: dataset4.csv

Column name Description
CustomerID Unique identifier for each customer. (Integer)
Churn Whether or not the customer has churned. (Boolean)
gender Gender of the customer. (String)
SeniorCitizen Whether or not the customer is a senior citizen. (Boolean)
Partner Whether or not the customer has a partner. (Boolean)
Dependents Whether or not the customer has dependents. (Boolean)
tenure Length of time the customer has been with the company. (Integer)
PhoneService Whether or not the customer has phone service. (Boolean)
MultipleLines Whether or not the customer has multiple lines. (Boolean)
InternetService Type of internet service the customer has. (String)
OnlineSecurity Whether or not the customer has online security. (Boolean)
OnlineBackup Whether or not the customer has online backup. (Boolean)
DeviceProtection Whether or not the customer has device protection. (Boolean)
TechSupport Whether or not the customer has tech support. (Boolean)
StreamingTV Whether or not the customer has streaming TV. (Boolean)
StreamingMovies Whether or not the customer has streaming movies. (Boolean)
Contract Type of contract the customer has. (String)
PaperlessBilling Whether or not the customer has paperless billing. (Boolean)
PaymentMethod Payment method the customer is using. (String)
MonthlyCharges Amount the customer is charged each month. (Float)
TotalCharges Total amount the customer has been charged. (Float)

File: dataset5.csv

Column name Description
CustomerID Unique identifier for each customer. (Integer)
Churn Whether or not the customer has churned. (Boolean)
gender Gender of the customer. (String)
SeniorCitizen Whether or not the customer is a senior citizen. (Boolean)
Partner Whether or not the customer has a partner. (Boolean)
Dependents Whether or not the customer has dependents. (Boolean)
tenure Length of time the customer has been with the company. (Integer)
PhoneService Whether or not the customer has phone service. (Boolean)
MultipleLines Whether or not the customer has multiple lines. (Boolean)
InternetService Type of internet service the customer has. (String)
OnlineSecurity Whether or not the customer has online security. (Boolean)
OnlineBackup Whether or not the customer has online backup. (Boolean)
DeviceProtection Whether or not the customer has device protection. (Boolean)
TechSupport Whether or not the customer has tech support. (Boolean)
StreamingTV Whether or not the customer has streaming TV. (Boolean)
StreamingMovies Whether or not the customer has streaming movies. (Boolean)
Contract Type of contract the customer has. (String)
PaperlessBilling Whether or not the customer has paperless billing. (Boolean)
PaymentMethod Payment method the customer is using. (String)
MonthlyCharges Amount the customer is charged each month. (Float)
TotalCharges Total amount the customer has been charged. (Float)

File: FinalResult.csv

Column name Description
CustomerID Unique identifier for each customer. (Integer)
TotalCharges Total amount the customer has been charged. (Float)

File: FinalResult1.csv

Column name Description
CustomerID Unique identifier for each customer. (Integer)

File: FinalResult2.csv

Column name Description
churn_prob Probability of customer churning. (Float)
customer_worth Estimated worth of the customer. (Float)

File: d.csv

Column name Description
Churn Whether or not the customer has churned. (Boolean)
gender Gender of the customer. (String)
SeniorCitizen Whether or not the customer is a senior citizen. (Boolean)
Partner Whether or not the customer has a partner. (Boolean)
Dependents Whether or not the customer has dependents. (Boolean)
tenure Length of time the customer has been with the company. (Integer)
PhoneService Whether or not the customer has phone service. (Boolean)
MultipleLines Whether or not the customer has multiple lines. (Boolean)
InternetService Type of internet service the customer has. (String)
OnlineSecurity Whether or not the customer has online security. (Boolean)
OnlineBackup Whether or not the customer has online backup. (Boolean)
DeviceProtection Whether or not the customer has device protection. (Boolean)
TechSupport Whether or not the customer has tech support. (Boolean)
StreamingTV Whether or not the customer has streaming TV. (Boolean)
StreamingMovies Whether or not the customer has streaming movies. (Boolean)
Contract Type of contract the customer has. (String)
PaperlessBilling Whether or not the customer has paperless billing. (Boolean)
PaymentMethod Payment method the customer is using. (String)
MonthlyCharges Amount the customer is charged each month. (Float)
TotalCharges Total amount the customer has been charged. (Float)

Acknowledgements

If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit .

Tables

D

@kaggle.thedevastator_analyzing_customer_churn_and_its_impact_on_reven.d
  • 72.83 kB
  • 3,000 rows
  • 21 columns
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CREATE TABLE d (
  "churn" VARCHAR,
  "gender" VARCHAR,
  "seniorcitizen" BIGINT,
  "partner" VARCHAR,
  "dependents" VARCHAR,
  "tenure" BIGINT,
  "phoneservice" VARCHAR,
  "multiplelines" VARCHAR,
  "internetservice" VARCHAR,
  "onlinesecurity" VARCHAR,
  "onlinebackup" VARCHAR,
  "deviceprotection" VARCHAR,
  "techsupport" VARCHAR,
  "streamingtv" VARCHAR,
  "streamingmovies" VARCHAR,
  "contract" VARCHAR,
  "paperlessbilling" VARCHAR,
  "paymentmethod" VARCHAR,
  "monthlycharges" DOUBLE,
  "totalcharges" DOUBLE,
  "customerid" BIGINT
);

Data

@kaggle.thedevastator_analyzing_customer_churn_and_its_impact_on_reven.data
  • 72.83 kB
  • 3,000 rows
  • 21 columns
Loading... 
CREATE TABLE data (
  "churn" VARCHAR,
  "gender" VARCHAR,
  "seniorcitizen" BIGINT,
  "partner" VARCHAR,
  "dependents" VARCHAR,
  "tenure" BIGINT,
  "phoneservice" VARCHAR,
  "multiplelines" VARCHAR,
  "internetservice" VARCHAR,
  "onlinesecurity" VARCHAR,
  "onlinebackup" VARCHAR,
  "deviceprotection" VARCHAR,
  "techsupport" VARCHAR,
  "streamingtv" VARCHAR,
  "streamingmovies" VARCHAR,
  "contract" VARCHAR,
  "paperlessbilling" VARCHAR,
  "paymentmethod" VARCHAR,
  "monthlycharges" DOUBLE,
  "totalcharges" DOUBLE,
  "customerid" BIGINT
);

Dataset1

@kaggle.thedevastator_analyzing_customer_churn_and_its_impact_on_reven.dataset1
  • 40.65 kB
  • 1,000 rows
  • 22 columns
Loading... 
CREATE TABLE dataset1 (
  "unnamed_0" BIGINT  -- Unnamed: 0,
  "churn" VARCHAR,
  "gender" VARCHAR,
  "seniorcitizen" BIGINT,
  "partner" VARCHAR,
  "dependents" VARCHAR,
  "tenure" BIGINT,
  "phoneservice" VARCHAR,
  "multiplelines" VARCHAR,
  "internetservice" VARCHAR,
  "onlinesecurity" VARCHAR,
  "onlinebackup" VARCHAR,
  "deviceprotection" VARCHAR,
  "techsupport" VARCHAR,
  "streamingtv" VARCHAR,
  "streamingmovies" VARCHAR,
  "contract" VARCHAR,
  "paperlessbilling" VARCHAR,
  "paymentmethod" VARCHAR,
  "monthlycharges" DOUBLE,
  "totalcharges" DOUBLE,
  "customerid" BIGINT
);

Dataset2

@kaggle.thedevastator_analyzing_customer_churn_and_its_impact_on_reven.dataset2
  • 40.76 kB
  • 1,000 rows
  • 22 columns
Loading... 
CREATE TABLE dataset2 (
  "unnamed_0" BIGINT  -- Unnamed: 0,
  "churn" VARCHAR,
  "gender" VARCHAR,
  "seniorcitizen" BIGINT,
  "partner" VARCHAR,
  "dependents" VARCHAR,
  "tenure" BIGINT,
  "phoneservice" VARCHAR,
  "multiplelines" VARCHAR,
  "internetservice" VARCHAR,
  "onlinesecurity" VARCHAR,
  "onlinebackup" VARCHAR,
  "deviceprotection" VARCHAR,
  "techsupport" VARCHAR,
  "streamingtv" VARCHAR,
  "streamingmovies" VARCHAR,
  "contract" VARCHAR,
  "paperlessbilling" VARCHAR,
  "paymentmethod" VARCHAR,
  "monthlycharges" DOUBLE,
  "totalcharges" DOUBLE,
  "customerid" BIGINT
);

Dataset3

@kaggle.thedevastator_analyzing_customer_churn_and_its_impact_on_reven.dataset3
  • 40.66 kB
  • 1,000 rows
  • 22 columns
Loading... 
CREATE TABLE dataset3 (
  "unnamed_0" BIGINT  -- Unnamed: 0,
  "churn" VARCHAR,
  "gender" VARCHAR,
  "seniorcitizen" BIGINT,
  "partner" VARCHAR,
  "dependents" VARCHAR,
  "tenure" BIGINT,
  "phoneservice" VARCHAR,
  "multiplelines" VARCHAR,
  "internetservice" VARCHAR,
  "onlinesecurity" VARCHAR,
  "onlinebackup" VARCHAR,
  "deviceprotection" VARCHAR,
  "techsupport" VARCHAR,
  "streamingtv" VARCHAR,
  "streamingmovies" VARCHAR,
  "contract" VARCHAR,
  "paperlessbilling" VARCHAR,
  "paymentmethod" VARCHAR,
  "monthlycharges" DOUBLE,
  "totalcharges" DOUBLE,
  "customerid" BIGINT
);

Dataset4

@kaggle.thedevastator_analyzing_customer_churn_and_its_impact_on_reven.dataset4
  • 40.8 kB
  • 1,000 rows
  • 22 columns
Loading... 
CREATE TABLE dataset4 (
  "unnamed_0" BIGINT  -- Unnamed: 0,
  "churn" VARCHAR,
  "gender" VARCHAR,
  "seniorcitizen" BIGINT,
  "partner" VARCHAR,
  "dependents" VARCHAR,
  "tenure" BIGINT,
  "phoneservice" VARCHAR,
  "multiplelines" VARCHAR,
  "internetservice" VARCHAR,
  "onlinesecurity" VARCHAR,
  "onlinebackup" VARCHAR,
  "deviceprotection" VARCHAR,
  "techsupport" VARCHAR,
  "streamingtv" VARCHAR,
  "streamingmovies" VARCHAR,
  "contract" VARCHAR,
  "paperlessbilling" VARCHAR,
  "paymentmethod" VARCHAR,
  "monthlycharges" DOUBLE,
  "totalcharges" DOUBLE,
  "customerid" BIGINT
);

Dataset5

@kaggle.thedevastator_analyzing_customer_churn_and_its_impact_on_reven.dataset5
  • 16.25 kB
  • 43 rows
  • 22 columns
Loading... 
CREATE TABLE dataset5 (
  "unnamed_0" BIGINT  -- Unnamed: 0,
  "churn" VARCHAR,
  "gender" VARCHAR,
  "seniorcitizen" BIGINT,
  "partner" VARCHAR,
  "dependents" VARCHAR,
  "tenure" BIGINT,
  "phoneservice" VARCHAR,
  "multiplelines" VARCHAR,
  "internetservice" VARCHAR,
  "onlinesecurity" VARCHAR,
  "onlinebackup" VARCHAR,
  "deviceprotection" VARCHAR,
  "techsupport" VARCHAR,
  "streamingtv" VARCHAR,
  "streamingmovies" VARCHAR,
  "contract" VARCHAR,
  "paperlessbilling" VARCHAR,
  "paymentmethod" VARCHAR,
  "monthlycharges" DOUBLE,
  "totalcharges" DOUBLE,
  "customerid" BIGINT
);

Finalresult

@kaggle.thedevastator_analyzing_customer_churn_and_its_impact_on_reven.finalresult
  • 33.28 kB
  • 750 rows
  • 6 columns
Loading... 
CREATE TABLE finalresult (
  "unnamed_0_1" BIGINT  -- Unnamed: 0.1,
  "unnamed_0" BIGINT  -- Unnamed: 0,
  "totalcharges" DOUBLE,
  "customerid" BIGINT,
  "churn_prob" DOUBLE,
  "customer_worth" DOUBLE
);

Finalresult2

@kaggle.thedevastator_analyzing_customer_churn_and_its_impact_on_reven.finalresult2
  • 19.24 kB
  • 750 rows
  • 4 columns
Loading... 
CREATE TABLE finalresult2 (
  "customerid" BIGINT,
  "churn_prob" DOUBLE,
  "customer_worth" DOUBLE,
  "email" VARCHAR
);

Logit

@kaggle.thedevastator_analyzing_customer_churn_and_its_impact_on_reven.logit
  • 3.23 kB
  • 16 rows
  • 3 columns
Loading... 
CREATE TABLE logit (
  "unnamed_0" VARCHAR  -- Unnamed: 0,
  "n_0" DOUBLE  -- 0,
  "n_1" DOUBLE  -- 1
);

Maildataset

@kaggle.thedevastator_analyzing_customer_churn_and_its_impact_on_reven.maildataset
  • 3.38 kB
  • 3 rows
  • 4 columns
Loading... 
CREATE TABLE maildataset (
  "name" VARCHAR,
  "email" VARCHAR,
  "company" VARCHAR,
  "promocode" VARCHAR
);

Predictionresult

@kaggle.thedevastator_analyzing_customer_churn_and_its_impact_on_reven.predictionresult
  • 3.7 kB
  • 11 rows
  • 4 columns
Loading... 
CREATE TABLE predictionresult (
  "unnamed_0" BIGINT  -- Unnamed: 0,
  "pred_prob" DOUBLE,
  "count" BIGINT,
  "true_prob" DOUBLE
);

Test Churn

@kaggle.thedevastator_analyzing_customer_churn_and_its_impact_on_reven.test_churn
  • 34.69 kB
  • 750 rows
  • 22 columns
Loading... 
CREATE TABLE test_churn (
  "unnamed_0" BIGINT  -- Unnamed: 0,
  "churn" VARCHAR,
  "gender" VARCHAR,
  "seniorcitizen" BIGINT,
  "partner" VARCHAR,
  "dependents" VARCHAR,
  "tenure" BIGINT,
  "phoneservice" VARCHAR,
  "multiplelines" VARCHAR,
  "internetservice" VARCHAR,
  "onlinesecurity" VARCHAR,
  "onlinebackup" VARCHAR,
  "deviceprotection" VARCHAR,
  "techsupport" VARCHAR,
  "streamingtv" VARCHAR,
  "streamingmovies" VARCHAR,
  "contract" VARCHAR,
  "paperlessbilling" VARCHAR,
  "paymentmethod" VARCHAR,
  "monthlycharges" DOUBLE,
  "totalcharges" DOUBLE,
  "customerid" BIGINT
);

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