The problem that the retail industry often encounters in customer operations is that consumers often make only one purchase, and it is difficult to convert them into closely-connected loyal members. Therefore, it is hoped that consumers' willingness to buy back can be strengthened through marketing activities, so that the connection between merchants and members will be deeper and more stable. We will use the accurate marketing methods reached by data science to carry out accurate campaign launches, so that the marketing campaigns can achieve their goals more effectively and accurately.
train.csv: the original training data set, including the ID of the member and the corresponding characteristics. It contains the prediction target (target), which corresponds to whether to repurchase in the translation.
test.csv: the original test data set.
transaction.csv: member transaction records, including member ID, merchant ID, transaction amount, item and other information.
Based on the historical data of some members, predict who in another group of members will buy back products.
User data in the retail industry, including personal information, transaction records, etc., can help operations or marketing strategies
