Problem Statement

The client needed to analyse the patterns of customer that lead to buying a product by them. In this the main task was to find out the the average transaction value + If there was a significant difference between spend in different store types.

Solution Approach

  1. First of all we dig in the the customer data-set that contained various parameters  related to customer background and buying details.
  2. Followed by feature selection to extract important features and then trained our model with supervised machine learning algorithm to find the probability of a user clicking on a particular content on website.

Solution Output

We created a production system to deliver the most relevant content card to the user on the website.

Technologies Used

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