telco_classification_project

Project Goals:

• Find out why customers are churning at Telco.
• Construct classification models to predict customer churn.

Initial questions of the data:

• Q1: Does contract type affect whether someone churns?
• Q2: Are high monthly charges causing customers to churn?
• Q3: Is a customer having fiber optic internet related to a customer churning?
• Q4: Is a customer having manual payments related to a customer churning?

Project planning:

• Planning:

• Aquire data

  Pull telco data utilizing get_telco_data function from Codeup mySQL database.

• Prepare data

  Clean data and split data into train, validate, test, utilizing prep_telco and splitting_data functions.

• Explore data

  Explore data by using Univariate, Bivariate/multivariate analysis.

• Model data

• Preprocessing to encode our values.
• Establish a baseline.
• Build models.
• Evaluate models.
• Select best models.
• Test models.

Data Dictionary

Feature	Definition
Monthly Chaerge	Amount a customer is charged monthly
Total Charges	Cumulative amount a customer has paid
Gender Male	If a customer is male or female, 0 = Female, 1 = Male
Has Partner	If a customer has a partner, 0 = No, 1 = Yes
Has Dependents	If a customer has dependents, 0 = No, 1 = Yes
Has Phone Service	If a customer has phone service, 0 = No, 1 = Yes
Has Paperless Billing	If a customer has paperless billing, 0 = No, 1 = Yes
Has Tech Support	If a customer has tech support, 0 = No, 1 = Yes
Has Online Security	If a customer has online security, 0 = No, 1 = Yes
Has Online Backup	If a customer has online backup, 0 = No, 1 = Yes
Has Streaming TV	If a customer has streaming tv, 0 = No, 1 = Yes
Has Streaming Movies	If a customer has streaming movies, 0 = No, 1 = Yes
Has Device Protection	If a customer has device protection, 0 = No, 1 = Yes
Has Dependents	If a customer has dependents, 0 = No, 1 = Yes
Has Multiple Lines	If a customer has multiple lines, 0 = No, 1 = Yes
Contract	Type of contract customer has, 0 = Month-to-month, 1 = One year, 2 = Two year
Internet Service	Type of Internet Service customer has, 0 = No internet service, 1 = DSL, 2 = Fiber optic
Has Automatic Payment	If a customer has automatic payment, 0 = No, 1 = Yes
Churn (Target Variable)	If a customer has churned, False = No, True = Yes

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To Reproduce Findings:

• Clone this repository (telco-classification-project)
• Create env file with username, host, password credentials to access Codeup mySQL telco-churn database.

Key Findings:

• Month-to-month contract, higher monthly payments, fiber optic internet, and manual payment type were among the biggest causes of churn.

Recommendations:

• Push for customers to sign up for one or two year contract as opposed to month-to-month with either a price incentive or including a free perk such as free tech support or online backup.
• Push for DSL internet instead of fiber optic or include a free perk with fiber optic.
• Give incentives for signing up for automatic payments instead of manual.

Next Steps:

• Dig deeper into the monthly payments to see what point customers are most likely to churn so we can incentivize them to stay prior to that point.
• Find out what other factors are leading to the high rate of churn with fiber optic internet customers.