Customer churn or customer turnover is the loss of clients or customers. Telecommunication companies often use customer attrition analysis and customer attrition rates as one of their key business metrics because the cost of retaining an existing customer is far less than acquiring a new one. Use churn prediction models that predict customer churn by assessing their propensity of risk to churn.
CreditScore
Geography
Gender
Age
Tenure
Balance
NumOfProducts
HasCrCard
IsActiveMember
EstimatedSalary
Exited
502
France
Female
42
8
159661
3
1
0
113932
1
822
France
Male
50
7
0
2
1
1
10062.8
0
549
France
Female
25
5
0
2
0
0
190858
0
587
Spain
Male
45
6
0
1
0
0
158685
0
582
Germany
Male
41
6
70349.5
2
0
1
178074
0
556
France
Female
61
2
117419
1
1
1
94153.8
0
550
Germany
Male
38
2
103391
1
0
1
90878.1
0
Click to expand Features Informations:
1. customerIDCustomer ID
2. gender Whether the customer is a male or a female
3. SeniorCitizen Whether the customer is a senior citizen or not (1, 0)
4. Partner Whether the customer has a partner or not (Yes, No)
5. Dependents Whether the customer has dependents or not (Yes, No)
tenureNumber of months the customer has stayed with the company
6. PhoneService Whether the customer has a phone service or not (Yes, No)
7. MultipleLines Whether the customer has multiple lines or not (Yes, No, No phone service)
8. InternetServiceCustomer’s internet service provider (DSL, Fiber optic, No)
9. OnlineSecurity Whether the customer has online security or not (Yes, No, No internet service)
10. OnlineBackup Whether the customer has online backup or not (Yes, No, No internet service)
11. DeviceProtection Whether the customer has device protection or not (Yes, No, No internet service)
12. TechSupport Whether the customer has tech support or not (Yes, No, No internet service)
13. StreamingTV Whether the customer has streaming TV or not (Yes, No, No internet service)
14. StreamingMovies Whether the customer has streaming movies or not (Yes, No, No internet service)
15. ContractThe contract term of the customer (Month-to-month, One year, Two year)
16. PaperlessBilling Whether the customer has paperless billing or not (Yes, No)
17. PaymentMethodThe customer’s payment method (Electronic check, Mailed check, Bank transfer (automatic), Credit card (automatic))
18. MonthlyChargesThe amount charged to the customer monthly
19. TotalChargesThe total amount charged to the customer
20 Churn Whether the customer churned or not (Yes or No)
MindsDB Code example
importmindsdbimportpandasaspdfromsklearn.metricsimportaccuracy_scoredefrun():mdb=mindsdb.Predictor(name='employee_retention_model')mdb.learn(from_data='dataset/train.csv',to_predict='Churn')test_df=pd.read_csv('dataset/test.csv')predictions=mdb.predict(when_data='dataset/test.csv')predicted_val=[x.explanation['Churn']['predicted_value']forxinpredictions]real_val=list(map(str,list(test_df['Churn'])))accuracy=accuracy_score(real_val,predicted_val)#show additional info for each transaction rowadditional_info=[x.explanationforxinpredictions]return{'accuracy':accuracy,'accuracy_function':'accuracy_score','backend':backend,'prediction_per_row':additional_info}if__name__=='__main__':result=run()print(result)