Analyzing Customer Churn And Its Impact On Revenue by Kaggle | Finance and Economics

About this Dataset

Analyzing Customer Churn And Its Impact On Revenue

Analyzing Customer Churn and Its Impact on Revenue

Exploring Patterns and Trends

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:

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.

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.

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?

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

71.12 KB
3000 rows
21 columns


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

71.12 KB
3000 rows
21 columns


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

39.7 KB
1000 rows
22 columns


CREATE TABLE dataset1 (
  "unnamed_0" BIGINT,
  "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

39.8 KB
1000 rows
22 columns


CREATE TABLE dataset2 (
  "unnamed_0" BIGINT,
  "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

39.7 KB
1000 rows
22 columns


CREATE TABLE dataset3 (
  "unnamed_0" BIGINT,
  "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

39.85 KB
1000 rows
22 columns


CREATE TABLE dataset4 (
  "unnamed_0" BIGINT,
  "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

15.86 KB
43 rows
22 columns


CREATE TABLE dataset5 (
  "unnamed_0" BIGINT,
  "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

32.5 KB
750 rows
6 columns


CREATE TABLE finalresult (
  "unnamed_0_1" BIGINT,
  "unnamed_0" BIGINT,
  "totalcharges" DOUBLE,
  "customerid" BIGINT,
  "churn_prob" DOUBLE,
  "customer_worth" DOUBLE
);

Finalresult2

@kaggle.thedevastator_analyzing_customer_churn_and_its_impact_on_reven.finalresult2

18.79 KB
750 rows
4 columns


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

3.15 KB
16 rows
3 columns


CREATE TABLE logit (
  "unnamed_0" VARCHAR,
  "n_0" DOUBLE,
  "n_1" DOUBLE
);

Maildataset

@kaggle.thedevastator_analyzing_customer_churn_and_its_impact_on_reven.maildataset

3.3 KB
3 rows
4 columns


CREATE TABLE maildataset (
  "name" VARCHAR,
  "email" VARCHAR,
  "company" VARCHAR,
  "promocode" VARCHAR
);

Predictionresult

@kaggle.thedevastator_analyzing_customer_churn_and_its_impact_on_reven.predictionresult

3.61 KB
11 rows
4 columns


CREATE TABLE predictionresult (
  "unnamed_0" BIGINT,
  "pred_prob" DOUBLE,
  "count" BIGINT,
  "true_prob" DOUBLE
);

Test Churn

@kaggle.thedevastator_analyzing_customer_churn_and_its_impact_on_reven.test_churn

33.87 KB
750 rows
22 columns


CREATE TABLE test_churn (
  "unnamed_0" BIGINT,
  "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
);