Name: Superstore Marketing Campaign Dataset
Creator: Kaggle
License: https://creativecommons.org/publicdomain/zero/1.0/

About this Dataset

Superstore Marketing Campaign Dataset

Context- A superstore is planning for the year-end sale. They want to launch a new offer - gold membership, that gives a 20% discount on all purchases, for only $499 which is $999 on other days. It will be valid only for existing customers and the campaign through phone calls is currently being planned for them. The management feels that the best way to reduce the cost of the campaign is to make a predictive model which will classify customers who might purchase the offer.
Objective - The superstore wants to predict the likelihood of the customer giving a positive response and wants to identify the different factors which affect the customer's response. You need to analyze the data provided to identify these factors and then build a prediction model to predict the probability of a customer will give a positive response.

Tables

Superstore Data

@kaggle.ahsan81_superstore_marketing_campaign_dataset.superstore_data

82.24 KB
2240 rows
22 columns


CREATE TABLE superstore_data (
  "id" BIGINT,
  "year_birth" BIGINT,
  "education" VARCHAR,
  "marital_status" VARCHAR,
  "income" DOUBLE,
  "kidhome" BIGINT,
  "teenhome" BIGINT,
  "dt_customer" TIMESTAMP,
  "recency" BIGINT,
  "mntwines" BIGINT,
  "mntfruits" BIGINT,
  "mntmeatproducts" BIGINT,
  "mntfishproducts" BIGINT,
  "mntsweetproducts" BIGINT,
  "mntgoldprods" BIGINT,
  "numdealspurchases" BIGINT,
  "numwebpurchases" BIGINT,
  "numcatalogpurchases" BIGINT,
  "numstorepurchases" BIGINT,
  "numwebvisitsmonth" BIGINT,
  "response" BIGINT,
  "complain" BIGINT
);