The data is a structured dataset pull from the sapa.com database with a few important features that can be used to predict customer response to marketing campaigns. The data sample has been split into train and test with a volume of 1568 and 672.

Files available for download

• train.csv: contains the target. This is the dataset that you will use to train your model.
• test.csv- resembles train.csv but without the target-related columns. This is the dataset on which you will apply your model to.
• sample_submission.csv: shows the submission format for this competition, with the ‘ID’ column mirroring that of test.csv and the ‘target’ column containing your predictions. The order of the rows does not matter, but the names of the ID must be correct.

Variable definitions

• ID: Unique identifier for each User
• Year_of_Birth: Year of birth
• Education_Level: The highest level of education attained by the User
• Marital_Status: Marital status
• Disposable_Income: Yearly User’s household disposable income
• No_of_Kids_in_home: total count of children in the user’s home
• No_of_Teen_in_home: Number of teenagers in the User's household
• Date_User: Date of User's enrollment with the company
• Recency: Number of days since User's last purchase
• Discounted_Purchases: Counts of purchases made by the user using coupons
• WebPurchases: Counts of purchases made by the user through the company’s website
• CatalogPurchases: Counts of purchases made by the user using a catalogue
• StorePurchases: Counts of purchases made by the user directly in stores
• Amount_on_Wines: Total amount user spent on wine and drinks within the last 3 years
• Amount_on_Fruits: Total amount user spent on fruity food within the last 3 years
• Amount_on_MeatProducts: Total amount user spent on meat products and livestock within the last 3 years
• Amount_on_FishProducts: Total amount user spent on fish alone within the last 3 years
• Amount_on_SweetProducts: Total amount user spent on sweets and chocolates within the last 3 years
• Amount_on_GoldProds: Total amount user spent on golden products within the last 3 years
• WebVisitsMonth: The number of times the user of visits to company’s website within the last 4 weeks
• Cmp3Accepted: 1: Offer was accepted after the third campaign, 0 otherwise
• Cmp4Accepted: 1: Offer was accepted after the fourth campaign, 0 otherwise
• Cmp5Accepted: 1: Offer was accepted after the fifth campaign, 0 otherwise
• Cmp1Accepted: 1: Offer was accepted after the first campaign, 0 otherwise
• Cmp2Accepted: 1: Offer was accepted after the second campaign, 0 otherwise
• Any_Complain: 1 if the user has a compliant history with the platform in the last 3 years, 0 otherwise
• User_Response: 1: indicates the acceptance of offer and 0 otherwise