Customer Segmentation (Data Science)

May 6, 2022
Customer Segmentation (Data Science)

Overview

A retail shop had seen a surge of online orders post covid. The client was interested in studying the data to profile their customers into various segment to understand the pattern of their purchase. The management decided to set the analytics department and needed help with it.

Challenge

Setting up a department from scratch was the major challenge in itself. Looking for the right hires was a challenging task. In the meantime, the freelancer faced another challenge of collating the data as they were scattered in multiple systems.

Implementation

A data analyst was hired to extract and collate the data scattered in various source systems. Also, a few laptops of our employees as few of the datasets were not added into the ERP’s or storage systems. The data analyst helped us build a central repository system from which any data could be extracted. Based on this data, customer segmentation bases on age, gender, location, behaviours were created. Each of which produced a report generating insights enabling the decision making in the management.

Benefits Achieved

  • Automation and centralised repository of 16 products
  • Customer segmentation success- helped in increasing revenue.
  • Time saving by at least 3 hours per day.
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