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Data Mining on e-Commerce Behavior Data from Multi-category Store

About Dataset

This dataset contain behavior data on October 2019 from a large multi-caltegory online store. There are 9 columns and 42,448,764 rows in this dataset. The dataset can be found on Kaggle.

Project Description

This project focus on 5 questions below:

  • What are the most popular categories and brands?
  • What are the most purchase categories and brands?
  • Who are the most customers with the highest number of purchase?
  • How about daily visitor of this month?
  • How about costumer activity?

Conclusion and Recommendation

Based on the data mining activities that have been carried above:

  • Provide discounts on products that aren’t selling well, so its can be sold right away.
  • Give a promotions at the beginning and end of the month to attract or increase website visitors.
  • Because many customers just view the products, rewards can be given to customers who make frequent transactions in order to increase the number of transactions. This will encourage more customers to make transactions.

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Behavior data on October 2019 from a large multi-category online store.

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