Ensemble Techniques : Bagging Classfiier, Boosting Classifiers, AdaBoost, Gradient Boosting, XGBoost, Stacking, Hyperparamter tuning
You are a Data Scientist for a tourism company named "Visit with us". The Policy Maker of the company wants to enable and establish a viable business model to expand the customer base. A viable business model is a central concept that helps you to understand the existing ways of doing the business and how to change the ways for the benefit of the tourism sector. One of the ways to expand the customer base is to introduce a new offering of packages. Currently, there are 5 types of packages the company is offering - Basic, Standard, Deluxe, Super Deluxe, King. Looking at the data of the last year, we observed that 18% of the customers purchased the packages. However, the marketing cost was quite high because customers were contacted at random without looking at the available information. The company is now planning to launch a new product i.e. Wellness Tourism Package. Wellness Tourism is defined as Travel that allows the traveler to maintain, enhance or kick-start a healthy lifestyle, and support or increase one's sense of well-being. However, this time company wants to harness the available data of existing and potential customers to make the marketing expenditure more efficient.
You as a Data Scientist at "Visit with us" travel company has to analyze the customers' data and information to provide recommendations to the Policy Maker and Marketing Team and also build a model to predict the potential customer who is going to purchase the newly introduced travel package.
To predict which customer is more likely to purchase the newly introduced travel package.
- CustomerID: Unique customer ID
- ProdTaken: Product taken flag
- Age: Age of customer
- TypeofContact: How customer was contacted (Company Invited or Self Inquiry)
- CityTier: City tier
- Occupation: Occupation of customer
- Gender: Gender of customer
- NumberOfPersonVisited: Total number of person came with customer
- PreferredPropertyStar: Preferred hotel property rating by customer
- MaritalStatus: Marital status of customer
- NumberOfTrips: Average number of the trip in a year by customer
- Passport: The customer has passport or not
- OwnCar: Customers owns a car flag
- NumberOfChildrenVisited: Total number of children visit with customer
- Designation: Designation of the customer in the current organization
- MonthlyIncome: Gross monthly income of the customer
- PitchSatisfactionScore: Sales pitch satisfactory score
- ProductPitched: Product pitched by a salesperson
- NumberOfFollowups: Total number of follow up has been done by sales person after sales pitch
- DurationOfPitch: Duration of the pitch by a salesman to customer